The AI-Powered Consumer: Why Use Is Surging While Sentiment Slides

Consumer AI use is skyrocketing. But enthusiasm? It’s quietly heading in the other direction.

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The AI-Powered Consumer: Why Use Is Surging While Sentiment Slides

Consumer AI use is skyrocketing. But enthusiasm? It’s quietly heading in the other direction.

Prophet’s latest AI-Powered Consumer Study, based on roughly 2,000 consumers in China, Germany, Singapore, U.K. and the U.S., reveals just how mainstream this technology has become and AI’s growing influence in everyday life as consumers’ deep and personal advisors. 

Yet, as usage surges, new questions and complexities are emerging. Our new research reveals we’ve arrived at a fascinating moment: While consumers are embracing AI’s capabilities, they are also seeking greater trust, value and human connection from these innovations. This signals a landscape of enormous possibility, where the real challenge is harnessing AI to deliver both breakthrough utility and experiences that truly resonate.

What We Learned:

01

AI usage is exploding in ways nobody predicted.

About 73% of consumers are now using GenAI, up from 45% in 2024. And they are not just using it for search but for tasks like uploading medical records for health advice or simulating future versions of themselves to predict how their purchase decisions will affect them over time. More than half view autonomous agents taking action on their behalf (e.g., making smart purchases) as genuinely helpful.

02

But at the same time, enthusiasm is falling.

Despite growing use, overall excitement about GenAI has declined. As AI becomes part of daily life, consumers fear a loss of the human experience, with the majority of consumers anxious about losing human connection and concerned about AI driving decision-making that requires human judgment.

03

The next frontier is already becoming visible.

Consumers want AI that understands them deeply and simply works in the background on their behalf – proactive, ambient and emotionally intelligent. Two-thirds want AI that anticipates their needs without being asked. The era of prompt engineering has given way to something more intuitive and human-like, and we already see the major AI platforms innovating in this area.

What does this mean for businesses?

AI agents will soon know your consumers on a deep and personal level, naturally embedded into their daily lives as key advisors and decision-makers. Today’s businesses need to win with both consumers and their agents to drive growth and create experiences that deliver both indispensable utility and emotional connection. 

Consumers Are Using GenAI in Ways That Were Previously Unimaginable. And They Are More Than Ready for Agents.

Consumer GenAI use jumped from 45% to 73% from early 2024 to 2026 and has grown in every market. But what’s even more striking is the incredibly varied nature of how AI is being used. Before they shop, people are searching for product recommendations, making pre-purchase search the top use case across all five markets, cited by 61% of consumers. When it comes to new product discovery, 41% of consumers use AI to discover products they didn’t even know existed but have the potential to solve problems in their lives.  

GenAI adoption surges across generations with millennials continuing to lead​

Gen-Z adoption increased from 50% in 2024 to 79% in 2026; Millenials are leading with an increased adoption of 82% in 2026 vs 53% in 2024; Gen X had an adoption of 42% in 2024 and are not far behind Gen-Z with a 74% adoption in 2026. Lastly, baby boomers doubled their adoption from 24% in 2024 to 49% in 2026

Base: General population, 18+ years old. Gen-Z 18-27 (863), Millennials 28-43 (1733), Gen-X 44-59 (1520), Baby Boomers 60+ (1319)

But the story doesn’t stop at pre-purchase. Consumers are using AI throughout the entire journey. At purchase, for example, 29% say they use AI to monitor discounts and make purchase decisions. Post-purchase, 37% use AI to create product reviews. We also see consumers using AI in ways that many of us may never have predicted from the average consumer. Examples include:  

31%

are using AI to build their own custom tools that meet their needs vs. access generic ones provided by brands.

“I’ve set up a specific prompt sequence in Gemini that helps me plan my trip itineraries and find more local spots instead of just the usual touristy malls.”

–Gen Z, Singapore

27%

are simulating future versions of themselves to predict the impact of their purchase decisions.

“I’ll use Claude or ChatGPT to run through “what-if” scenarios when I’m weighing a big purchase. When I was debating a VR headset, I had AI help me weigh the long-term utility versus initial excitement. It helped me stay grounded and avoid impulse buys.” 

– Millennial, U.S.

13%

providing personal medical information to get personalized health advice.

“I recently used AI to upload my X-ray results and asked for an interpretation – it helped me prepare for when my physician gave me a call later that day.” 

– Boomer, U.S.

AI use is more personal and sophisticated than many expected, and people are increasingly willing to share deeper, more personal data when the value is clear. This shift challenges brands to keep pace as consumers turn to AI for meaningful, data-driven experiences that go beyond the traditional engagement models most brands are currently delivering. 

When it comes to agentic AI – the systems that take autonomous action on a consumer’s behalf – consumer appetite is real, with 54% of people already viewing these agents as helpful. Here are the top five use cases consumers want, reflecting the demand for agentic AI, particularly in the commerce space. 

Top 5 Agentic Use Cases Consumers Want

Discount monitoring and purchasing tops the list at 60%, followed by practive customer service prevention and experience coordination each sitting at 54%. Automatic needs-based purchasing follows at 53% and offer negotiation sits at 49%

“I can’t imagine using a search engine again. AI seems to anticipate what I want and need”

– Boomer, UK

“I can’t imagine using a search engine again. AI seems to anticipate what I want and need.”

– Boomer, U.K. 

Brands face a real threat. The risk of disintermediation is rising, with AI agents increasingly positioned to own more of the consumer relationship and make decisions on their behalf. The landscape continues to evolve rapidly—for example, OpenAI recently pivoted to scale back native in-app purchasing, while Google continues to invest in new agentic features (e.g., DoorDash delivery through Gemini). But through this rapid change, one thing is clear: Agentic use cases such as those above present clear potential to deliver value to consumers, and therefore likely where we can expect to see innovation continue to shift.   

As AI becomes woven into daily life, businesses must design for both humans and AI agents —integrating seamlessly within consumers’ evolving agentic ecosystems. To unlock competitive advantage, leaders also need to innovate their own AI-driven businesses and experiences. Through these evolutions, success depends on evolving operating models that actively manage and empower both human and AI agents. Winning organizations will proactively upskill talent, adapt business processes, and embed dynamic human–AI collaboration at the core. 

What This Means for Marketers and Business Leaders

Design for humans and their agents. As AI agents take a greater hold in consumers’ lives, the potential impact on direct-to-consumer engagement is enormous. With consumers continuing to rely on and delegate to AI agents, who may be getting to know them on a deep and personal level, brands need to reimagine how they will attract, engage, and win with both consumers and their agents.  

Own the agent, own the relationship. Brands also need to decide where to offer their own agents to consumers, providing a critical advantage in driving full-journey engagement and data capture. 

Prioritize AI change management and shifts in operating model. Building and/or integrating with AI agents for real consumer value requires a significant organizational shift, actively rethinking roles, capabilities, and ways of working around human/AI collaboration models. 

The imperative for brands is to deliver distinctive value that meets consumers’ aspirational use cases, or risk losing direct access to their audiences. The brands and platforms able to create genuine, scalable value for consumers — and the agents acting on their behalf — will shape the next era of growth. 

But what do businesses need to do to actually deliver that distinctive value? We explore this question in the next section by examining a key tension for consumers as this technology permeates daily life. 

A Paradox Emerges – Usage Is Growing, While Enthusiasm Declines

28%


Average increase in adoption of AI use cases along the consumer journey

30%


Fewer consumers believe GenAl will be so integrated into their lives that they’ll rely on GenAl for most decisions

Here is the tension at the heart of this research: consumers are using AI more than ever, but they’re feeling less good about where it’s all heading.  

Overall excitement about GenAI has dropped approximately 7% since our previous 2024 study. More significantly, the belief that GenAI will become so integrated into daily life that consumers will rely on it for most decisions has fallen by a striking 30%, signaling a meaningful shift in consumer psychology.   

This trend signals that GenAI has entered what Gartner calls the “trough of disillusionment,” the natural dip in enthusiasm that follows inflated expectations in any technology cycle. But with AI, there’s a specific emotional driver that makes this moment distinct: people feel anxiety over the impact that AI might have on humanity and fear the loss of the human experience.

71% of consumers are concerned about inaccurate information from AI driving decision-making; 63% of consumers are worried that over-reliance on AI could cause a loss of human skills; 61% of consumers are anxious about losing human connection

71% of consumers are concerned about inaccurate information from AI driving decision-making; 63% of consumers are worried that over-reliance on AI could cause a loss of human skills; 61% of consumers are anxious about losing human connection

“I use AI to help me track and set alerts on price shifts – but I do wonder if I’m now losing out on actually enjoying the experience of shopping. It’s also a fear of losing the ability to be spontaneous, without a screen telling me the best time to click buy. I don’t want to reach a point where I can’t make a simple decision without asking the app first.“

– Singapore, Gen-Z

A mistake would be to interpret this data as a reason to slow down AI investment. AI brings enormous benefits to consumers, as shown by the accelerated adoption we observe. But what this data does signal is the need to redirect AI investments, from delivering yet another chatbot focused on efficiency to innovation that speaks to this core tension for consumers, offering real value with both functional and emotional benefits.

The brands winning right now are doing just that, deploying AI to solve genuine pain points while elevating trust and empathy in the brand relationship through the experience delivered. 

Some favorite examples:

ASOS

ASOS recognized that online shopping can be high-anxiety and isolating, with uncertainty around fit, style, and self-expression creating real barriers. Its AI features address not just the transactional side, but the emotional experience too. Virtual Try-On lets shoppers upload a photo or choose from 20 diverse AI-generated models spanning a range of body types, sizes, and skin tones — reducing self-doubt and making the experience more inclusive. Style Match lets users upload images of friends or creators to instantly find similar looks, transforming shopping from a solitary task into something social and culture-driven. Together, these features blend utility with empathy, earning ASOS a more meaningful place in consumers’ lives and building ongoing engagement.

BANK OF AMERICA

Bank of America’s Erica is an example of how AI can address functional consumer needs while building a more trusted, empathetic brand, using a strategy Bank of America calls “High tech, high touch.” For consumers, money is a highly emotional topic often intertwined with self-worth and identity. Erica acts as an always-on, proactive financial copilot, providing insight and guidance along consumers’ key moments of truth (e.g., proactively detecting fraud, flagging spikes in monthly bills, or recognizing a milestone toward a financial goal). Under the hood, sentiment models monitor markers of frustration, allowing AI to adjust its tone and escalate to a human specialist when needed. Interactions focus not only on executing financial management tasks but providing peace of mind, which strengthens the brand resonance and relationships.

STARBUCKS

Starbucks’ Green Dot Assist found a meaningful way to use AI to augment staff rather than displace them, improving service by elevating the human warmth that defines hospitality. These AI agents work alongside baristas, providing instant access to recipes, equipment troubleshooting and operational information. That speeds service and improves accuracy, enabling staff to focus on what humans do best — delivering genuine, emotionally resonant service.

What This Means for Marketers and Business Leaders

Do not stop at utility and efficiency — generate emotionally resonant value propositions, and invest behind the experience. Look beyond delivering yet another chatbot and focus on how AI can help solve real consumer pain points. The winning formula for agentic value propositions is both functional utility and human experience.   

Think of AI as a critical layer augmenting consumers’ ecosystem (not the whole story). Brands navigating this well are treating AI as an integrated layer within an omnichannel journey. It should augment human and community interaction, not replace it.

The Next Frontier: Emotionally Intelligent, Ambient, Anticipatory AI

We asked consumers about emerging AI capabilities that do not fully exist yet, and the responses painted a clear picture of where the next wave of consumer AI is heading. 

Three connected themes came through strongest:

Emotionally Intelligent AI.

67%

of consumers want AI that guides purchase decisions based on their personal values and preferences – not just price. 

That’s slightly more appealing than purely price-driven agent decisions (60%). Among heavy AI users, 47% already envision GenAI providing emotional support and companionship “similar to a trusted friend.” People want to feel understood.

Emotionally Intelligent AI.

67%

of consumers want AI that guides purchase decisions based on their personal values and preferences – not just price. 

That’s slightly more appealing than purely price-driven agent decisions (60%). Among heavy AI users, 47% already envision GenAI providing emotional support and companionship “similar to a trusted friend.” People want to feel understood.

Ambient AI.

62%

of consumers want AI that quietly notices things in their environment, and provides help proactively, vs. having to constantly ask the AI questions.

The next frontier for AI is one where consumers don’t need to constantly have their heads in their mobile devices, or spend time providing their AI agents with data – rather, companionship from AI agents is woven into the fabric of daily life.

Ambient AI.

62%

of consumers want AI that quietly notices things in their environment, and provides help proactively, vs. having to constantly ask the AI questions.

That’s slightly more appealing than purely price-driven agent decisions (60%). Among heavy AI users, 47% already envision GenAI providing emotional support and companionship “similar to a trusted friend.” People want to feel understood.

Anticipatory AI.

66%

of consumers want AI that can “read between the lines” to meet their real needs, not just what they literally ask for.

The prompt-response model that defines most of today’s GenAI interactions is already feeling outdated to consumers who’ve experienced more fluid, intuitive systems, mirroring what’s happening in enterprise AI. Consumers don’t want to become prompt engineers. They want AI that already knows what they need.

Anticipatory AI.

66%

of consumers want AI that can “read between the lines” to meet their real needs, not just what they literally ask for.

The prompt-response model that defines most of today’s GenAI interactions is already feeling outdated to consumers who’ve experienced more fluid, intuitive systems, mirroring what’s happening in enterprise AI. Consumers don’t want to become prompt engineers. They want AI that already knows what they need.

“If my flight to Singapore to go see my daughter gets cancelled, I don’t just want a list of flight numbers. I need AI to help understand the stress of that moment and prioritize the flight that is going to keep me most comfortable vs. just picking the fastest or cheapest option” –Boomer, Germany “I’d love my home assistant to know when I’ve had a day of back-to-back meetings, and help handle the mental load I feel. It could help order groceries or send a quick update to my wife. Maybe it could shift my environment – news summarized on the kitchen hub – drop me into the PM headspace so I can be present with the family when I’m off the clock.” – Millennial, US Together, these signals point to an AI future that is less about answering questions and more about living alongside consumers — emotionally attuned, context-aware, and proactively useful. It's these capabilities that can both help make AI more useful to consumers and bridge the critical sentiment gap we're currently observing. What This Means for Marketers and Business Leaders Build your innovation roadmap around emotionally intelligent, ambient, anticipatory-AI. The brands that anchor their next 12 to 24 months of AI development and partnership on these three themes will be the ones that lead the market in closing the sentiment gap and driving sustained growth. Prepare for a world beyond chatbots. If your AI strategy still centers on getting consumers to interact with a chatbot or type queries into a search bar, you are designing for the previous wave. The architecture of consumer AI is shifting toward systems that observe, infer and act. Start preparing your data structures, content and consumer touchpoints for that reality now.

“If a flight to Singapore I have to go see my daughter gets cancelled, I don’t just want a list of flight numbers. I need AI to help understand the stress of that moment and prioritize the flight that is going to keep me most comfortable vs. just picking the fastest or cheapest option.”
–Boomer, Germany

“I’d love my home assistant to know when I’ve had a day of back-to-back meetings, and help handle the mental load I feel. It could help order groceries or send a quick update to my wife. Maybe it could shift my environment – news summarized on the kitchen hub – drop me into the PM headspace so I can be present with the family when I’m off the clock.” 
–Millennial, U.S.

Together, these signals point to an AI future that’s less about answering questions and more about living alongside consumers — emotionally attuned, context-aware, and proactively useful. It’s these capabilities that can both help make AI more useful to consumers and bridge the critical sentiment gap we’re currently observing.

What This Means for Marketers and Business Leaders

Build your innovation roadmap around emotionally intelligent, ambient, prompt-less AI. The brands that anchor their next 12 to 24 months of AI development and partnership on these three themes will be the ones that lead the market in closing the sentiment gap and driving sustained growth.

Prepare for a world without prompts. If your AI strategy still centers on getting consumers to interact with a chatbot or type queries into a search bar, you are designing for the previous wave. The architecture of consumer AI is shifting toward systems that observe, infer and act. Start preparing your data structures, content and consumer touchpoints for that reality now.

Wrap-Up: Top Five Things to Do Right Now

AI is a moving target. But with so much at stake, growth-focused leaders can’t afford to wait and see. We recommend prioritizing:

01

Re-architect consumer journeys for human and agent ecosystems. 

Establish your brand’s role and how it will create value within consumers’ evolving ecosystems of communities, creators, and agents. Map every touchpoint and ask: how does this work when the “consumer” is an AI agent acting on someone’s behalf? Where does humanity need to be elevated?

03

Innovate AI-enabled businesses, offers and experiences that resolve consumers’ core tensions. 

Businesses that own the agents will have a structural advantage in maintaining consumer relationships, driving full-journey engagement, and capturing data. Decide where those opportunities exist for you and innovate value propositions that deliver technical utility and emotional connection.

05

Drive organizational change toward AI-human collaboration. 

New capabilities, roles, ways of working and culture will be required to manage emotionally intelligent agentic ecosystems at the speed and scale the market demands. Engaging the best talent in an increasingly automated environment requires a new approach. Driving organizational change should happen as soon as possible, while your strategy is being set. 

02

Operationalize your brand to be discoverable and resonant with AI agents and the human trust signals they rely on.

Audit your content, data, and trust signals for LLM performance. Is your content answer-driven? Are you in the conversation with communities and creators? Evolve your owned assets and influence the external signals LLMs rely on. 

04

Move from periodic to always-on consumer emotional intelligence. 

AI agents act on real-time signals and are getting to know your consumers on the deepest level  — your brand should too. Make consumer intelligence a continuous input to cross-functional decision-making and blend primary research with AI-enabled tools to create a new way of doing business. 

See Our AI Solutions

Wrap-Up: Top Five Things to Do Right Now

AI is a moving target. But with so much at stake, growth-focused leaders can’t afford to wait and see. We recommend prioritizing:

01

Re-architect consumer journeys for human and agent ecosystems. Establish your brand’s role and how it will create value within consumers’ evolving ecosystems of communities, creators, and agents. Map every touchpoint and ask: how does this work when the “consumer” is an AI agent acting on someone’s behalf? Where does humanity need to be elevated?

02

Operationalize your brand to be discoverable and resonant with AI agents and the human trust signals they rely on. Audit your content, data, and trust signals for LLM performance. Is your content answer-driven? Are you in the conversation with communities and creators? Evolve your owned assets and influence the external signals LLMs rely on. 

03

Innovate AI-enabled businesses, offers and experiences that resolve consumers’ core tensions. Businesses that own the agents will have a structural advantage in maintaining consumer relationships, driving full-journey engagement, and capturing data. Decide where those opportunities exist for you and innovate value propositions that deliver technical utility and emotional connection.

04

Move from periodic to always-on consumer emotional intelligence. AI agents act on real-time signals and are getting to know your consumers on the deepest level  — your brand should too. Make consumer intelligence a continuous input to cross-functional decision-making and blend primary research with AI-enabled tools to create a new way of doing business. 

05

Drive organizational change toward AI-human collaboration. New capabilities, roles, ways of working and culture will be required to manage emotionally intelligent agentic ecosystems at the speed and scale the market demands. Engaging the best talent in an increasingly automated environment requires a new approach. Driving organizational change should happen as soon as possible, while your strategy is being set. 

The Bottom Line

AI agents will soon know your consumers on a deep and personal level, embedded into daily life as advisors and decision-makers. A central question for every growth leader right now is how to win with both consumers and the agents acting on their behalf.

The data is clear: consumers are ready. They are using AI in ways we didn’t anticipate, and they are hungry for AI that goes further. But they are also anxious. They don’t want to lose the human connection that enriches their experiences and makes their relationships meaningful.

The brands that close that gap—evolving their organizations to deploy AI as a powerful enabler of experiences that are both highly useful and emotionally resonant—will be the ones that define the next era of consumer relationships.

Ready to understand what this means specifically for your business? Prophet’s team of growth strategy, consumer experience, and AI experts can help you translate these insights into a clear path forward and action. 

Contact us to start the conversation, or explore our AI and growth solutions to learn more.
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Authors

Chan Suh

Chan Suh
Senior Partner, Chief Digital Officer

Chiaki Nishino
Senior Partner, President

Lauren Papes
Associate Partner

Alan Worley
Principal, Insights & Analytics

Uyen Dang
Manager, Insights & Analytics

About the Research

Online Quantitative Survey

Participants N=2015 people aged 18 who used at least one AI tool in the past 6 months for personal/consumer reasons 

Fieldwork dates: Jan 2026 – Feb 2026

Markets: China, Germany, Singapore, United States, United Kingdom 

Our study included a representative sample of the general population for each country, across a wide range of AI usage and familiarity. 

Survey samples are nationally representative in each country.   

The focus of the research was unpacking consumer attitudes, behaviors, and future aspirations for generative and agentic AI.  

BLOG

Reinvention, Relevance, Growth 

Prophet’s 2025 Corporate Earnings summary with 2026 implications

Each year, we review corporate earnings reports from across regions, sectors, and sizes, distilling the learnings, strategies, guidance, and big bets into key themes for industry leaders. Giving a sense of what the last year might shape for the landscape ahead.

Which, with 331 S&P 500 companies citing “AI” during earnings calls conducted between December 15 and March 11, 2026—up from 241 in the same period last year—it’s no surprise that AI is taking up a lot of visible horizon.

Let’s get into it.

1. AI: From Building Block to Growth Engine

2025 saw unprecedented investments from those leading the AI charge. $400B+ of total AI-related capex spending from the “Magnificent 7” alone. But, with major investment comes the need to prove ROI. Questions continue to circulate across industries: How long will this take? What will make the payoff worth it? Are we doing enough?

At Davos, Uber’s CEO Dara Khosrowshahi claimed many companies are “play-acting” with AI, saying the right words without fundamentally changing how their operations function. The difference is visible between companies that added AI to existing systems versus those that rebuilt their processes around it.

First came the infrastructure. The AI data center buildout created a rising tide for anyone positioned to supply it—right place, right time, mixed with speed to market and operational efficiency. Corning’s optical segment surged 35% to $6.3B. Celestica’s Connectivity & Cloud Solutions segment grew by 64%. Caterpillar’s power generation sales jumped 44% in Q4. Vertiv surpassed $10B, a 26% increase from 2024.

Other companies have been weaving AI into the core of how they work. Duolingo used AI to launch 148 new courses in under a year. Walmart’s “Trend-to-Product” engine tracks social trends and feeds concepts directly into sourcing, while its self-healing inventory system reroutes supply before shortages appear, saving $55M+. JPMorgan Chase and Mastercard embedded AI across trading, fraud detection, and transaction scoring to transform operational tools into revenue-driving capabilities. Uber rebuilt its customer-service systems from scratch, replacing rigid rules with clear goals for AI agents.

The fatigue of talking about AI for the sake of talking about it is real. But when you look at what companies are building? The advancements are remarkable—and company leaders expect those to compound with each passing year. The challenge is extracting value and turning towards AI as a growth driver versus an efficiency play.

2. The AI Talent Restructure

As for taking a stance on the role of AI in the workforce, some have gone all in: Duolingo’s CEO Luis von Ahn boldly declared the company “AI-first,” signaling a fundamental shift in how it hires and operates. Others have moved forward similarly, only without public statements. PepsiCo promised a “record year of productivity savings” in 2026 to fund growth without once mentioning AI in their Q4 earnings, even while Coca-Cola’s incoming CEO Henrique Braun made AI and digital a defining strategic priority.

To deliver these promises, companies have led colossal workforce restructurings. Intel, UPS, Amazon, and Verizon have all made cuts in the tens of thousands. Jack Dorsey’s Block laid off nearly half its staff, framing it as becoming a “smaller, faster, intelligence-native company,” an operating model reset.

But, for the AI powerhouses, these major talent shifts aren’t merely downsizing. Companies are paying a premium for the talent that can push them ahead. Meta, OpenAI, Google, and xAI reportedly offered $20M+ equity awards — and in some cases $100M packages — to recruit elite AI researchers. Capability-building now means smaller teams, higher talent density, and a few highly leveraged technical leaders.

Culture has proven to be a driver of uncommon growth across all industries. As AI implementation continues, organizations that communicate clearly and tie AI to employee impact and values are seeing faster, more sustainable adoption.

3. Reinventing Toward Relevance

The ripple effects of AI and last year’s ‘Proceed with Caution’ economy pushed companies to reinvent. We noticed a few distinct flavors of reinvention in 2025: the pivot, the shed, and the path to platform.

The Pivot

Tesla halted Model S/X production to build Optimus robots. Lemonade is reinventing insurance offerings to incorporate new AI realities. Southwest made a massive bet by introducing bag fees, assigning seating, and removing its “never expire” flight credits.

The Shed

Some companies are aiming to get smaller and stronger in specific areas. Comcast spun off its cable networks and leaned on theme parks, and Peacock deals for revenue. Meta officially shifted its narrative from “Metaverse” to “Superintelligence,” no longer promoting Reality Labs for VR. Siemens is spinning off their Healthineers business. Medtronic announced the spin-off of its $2.7B Diabetes business to simplify operations and double down on procedural medtech, where its cardiac ablation solutions surged nearly 30%.

The Path to Platform

The companies that chose to keep adding were betting on becoming something else entirely. Robinhood evolved from meme-stock brokerage to financial super app—prediction markets, retirement, credit cards, banking, managed portfolios—with revenue up 52% to $4.5B and platform assets up 68% to $324B. The New York Times hit nearly 13 million subscribers by bundling news, games, cooking, and sports into a contained ecosystem. JPMorgan Chase continued rewiring itself as an integrated platform, backed by a $18B technology budget and the operational deployment of agentic AI.

For others, reinvention meant short-term loss for long-term potential. UnitedHealth absorbed a $1.6B restructuring charge against a backdrop of genuine turbulence and still grew full-year revenues 12% to $447.6B. The restructuring wasn’t a retreat, but a bet on what comes next.

Whether getting lean or integrating more capabilities, the underlying question remains the same: where and when will our investments pay off? We’ll see if that question drives continued reinvention in 2026.

4. M&A Outlook / The R&D Arms Race

From a muted M&A environment in 2024, deal volume and deal value were both up in 2025. There were notable acquisitions—Alphabet acquired Wiz to enhance AI-powered cybersecurity across multi-cloud environments, Verizon added fiber infrastructure through its Frontier deal, Paramount won the long battle for the premium-priced Warner Bros. Discovery, Dick’s Sporting Goods acquired Foot Locker, and Pfizer’s acquisition of Metsara brought it into the GLP conversation.

But there’s more to the story. Only about 7% of total corporate cash spending went to M&A; the rest? R&D and capex. Companies that try to buy growth are still waiting for the payoff. PE firms like Carlyle and Blackrock had successful fundraising and financial performance, yet the market still struggled to deploy capital in an environment where ROI is difficult, and AI makes future earnings less predictable.

The companies that drove growth in 2025 built it themselves. Meta is moving to own the entire AI stack, reducing reliance on NVIDIA and investing heavily in AI commerce. Palantir’s U.S. commercial revenue grew 137% year-over-year, with AIP becoming a repeatable growth engine. CrowdStrike pushed R&D spending up 38% to launch Falcon AIDR, a full AI-native security platform.

In healthcare, Eli Lilly invested $55B in manufacturing to scale GLP-1 production far beyond current demand, partnering with NVIDIA on AI-driven drug discovery to compress R&D timelines. Hims & Hers invested in proprietary telehealth infrastructure to build direct-to-consumer health at scale, and AbbVie is building a neuroscience franchise intended to rival the scale of its immunology business. The M&A window may reopen as clarity returns, but 2025 made a strong case that in an AI-driven economy, growth can be driven organically.

5. Customer Obsession: Know who You’re Serving

Despite a resilient (if but wobbly) economy in 2025, some consumers acted as if nothing stood in their way. Moody’s Analytics reported that the top 10% of households were responsible for nearly half of all consumer spending, validating Powell’s characterization of a “bifurcated economy.” The companies winning at the top are commanding premiums by delivering differentiated experiences, and those winning at the bottom are using AI to deliver more for less. The companies in the middle—the ones doing neither—are getting hollowed out.

Winning at a Higher Premium

Netflix closed 2025 with over 325 million paid subscribers, and with another premium price hike on the way, it’s proving that relentless investment in IP consumers care about makes for inelastic demand. Crocs’ Jibbitz charm revenue hit $271 million in 2024, with 3/4 buyers purchasing charms to personalize their crocs, turning a one-time shoe sale into an ongoing relationship. Colgate is pushing into premium with its Optic White Pro Series, positioning at-home whitening as a credible alternative to professional treatments.

Winning the Value

Costco raised membership fees for the first time in years, and, with a 92% renewal rate, no one flinched. Its private-label, value-driven Kirkland Signature brand continued to grow faster than the total business. DoorDash expanded well beyond food delivery into grocery, retail, and convenience, only adding value to its household name.

Stuck in the Middle

Target’s stock fell 34%. The company is investing in store remodels and trying to compete, though still not affordable enough to win the price-conscious shopper and not differentiated enough to command loyalty at the top.

Being ‘stuck’ doesn’t mean it’s over. Starbucks pivoted back to its beginnings, putting customer experience first with a $1B investment in its ‘Coffeehouse Uplift’ initiative to shift perceptions of a once dreaded destination to again being the token ‘third place.’ Even as they constantly evolve, focusing on core customers will likely be a key theme in 2026.

A special thank you to:

Editors: Hannah Anderson, Moira Allen

Research: Harry Ball, Fabienne Haase, Caitlin Shin, Gibson Campbell, Zoey Gendler, Sophie Kang

Organization & Culture

FINAL THOUGHTS

The AI conversations, reinventions, and innovations show no signs of stopping. And in this rapidly growing area of an already ever-evolving market, there’s never been more risk or opportunity for growth. Last year’s winners harnessed their own capabilities and reinvigorated their approach to drive uncommon growth—how companies respond in 2026 and beyond will determine whether they become an Uncommon Growth Company.

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REPORT

The Agentic AI Story of Value:
Transforming Digital Utility into Growth in Banking and Wealth Management

The secret to winning the next decade of AI in banking and wealth management isn’t found in your code—it’s found in how you make your clients feel. This study of individual and business clients proves that warmth, trust, and human connection are the ultimate catalysts for adoption of AI value propositions in a high-stakes world. 

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The narrative across banking and wealth management is shifting from “what do we cut?” to “what can we build?” That shift matters to brand, marketing, and experience leaders. Agentic AI is rewriting the rules for how banks and wealth managers deliver value to clients. 

In our latest research, we surveyed 1,800 banking and wealth management individual and business clients in North America to explore the following questions: 

  1. What are the prevailing models for integrating Agentic AI into a story of value? 
  2.  What drives clients to action when adopting Agentic AI? 
  3. What are the client segment considerations in positioning Agentic AI? 
  4. Which brands are most likely to experience a positive lift in reputation from Agentic AI? 
  5. What are the imperatives for Brand, Marketing and Experience Leaders? 

The findings are clear — Agentic AI isn’t just a technology layer; it’s also a brand experience decision. As new agent-centric products and services take on more visible, autonomous roles, they must be introduced with care, clarity, and emotional intelligence. 

Download a copy today.

Special thanks to contributors: Priyanka Bhagat, Rathi Ganesan, and Alan Worley

Experience & Innovation

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The Agentic AI Story of Value: Transforming Digital Utility into Growth in Banking and Wealth Management

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The Modern Marketer’s Growth Playbook

Growth is harder to earn. Trust is easier to lose. AI is reshaping the game. Secure your early access for a chapter-by-chapter blueprint to navigating the new rules of marketing.

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The Modern Marketer’s Growth Playbook

Growth is harder to earn. Trust is easier to lose. AI is reshaping the game. Secure your early access for a chapter-by-chapter blueprint to navigating the new rules of marketing.

GET NOTIFIED

Marketing is undergoing its most consequential reset in decades. At a moment when the old assumptions no longer hold, leaders are being asked to deliver against three hard things at once:

  • Deliver growth with fewer resources, and do it faster 
  • Build brands in an era of compression, where attention and trust are fragile 
  • Respond to an AI change mandate, experimenting while still delivering at scale

These forces accelerate each other and demand a fresh, system-level approach. And so, we believe a new playbook is needed. The Modern Marketer’s Growth Playbook is a chapter-by-chapter guide to help marketers deliver growth, protect your brand, and harness AI with confidence. 

If marketing must earn its keep in a high-pressure environment, this is your blueprint for what comes next.

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Experience Intelligence Redefined: Simulation for Faster, Richer CX Insights

Using predictive intelligence to bridge the gap between strategy and frontline reality to drive uncommon growth.

This article was co-authored by Cameron Fink, Co-Founder and CEO of Aaru, as part of a strategic partnership with Prophet to redefine experience intelligence through AI simulation. Read more about Aaru and their story in their recent Wall Street Journal profile.

What if you could understand your customer’s experience across a journey that spans thousands of touchpoints in just 48 hours?

That’s no longer a hypothetical. With AI simulation, Prophet and Aaru are helping brands model and action on customer journeys, particularly among hard to reach audiences.

This isn’t “synthetic research.” It’s a new form of predictive intelligence: Aaru’s simulations are built on proprietary behavioral and outcomes-based data that mirrors real-world patterns with remarkable accuracy. The result? A clearer, faster, and more granular path to understanding what customers experience, feel, and do —and how to act on it to drive loyalty and growth.

Success Story: From Impossible to Possible

Prophet and Aaru partnered with a leading healthcare company specializing in emergency care to tackle the daunting challenge of understanding the patient experience during unplanned care events. The team simulated 12,500 survey respondents, “agents,” across patients, providers, caregivers, and health system leaders — giving us a comprehensive, 360-degree view of what truly happens in these critical moments.

A simulated patient described their journey this way:

“Treatment was the strongest part of my emergency department visit. The care team was attentive even under pressure, and I felt genuinely listened to. In contrast, discharge was confusing; I left with a sense that key details were missing, which made managing at home more stressful. The journey back to routine life was neither easy nor especially difficult, but I wish the transition out of the hospital matched the quality of care I received inside.”

This engagement surfaced breakthrough insights that would have been nearly impossible to capture using traditional research methods, especially in a comparable window of time and with the same depth and granularity of insights.

Most notably, it exposed a significant disconnect within the organization: While 78% of C-suite leaders believed they had a formal patient experience strategy in place, only 19% of frontline doctors and nurses were even aware such a strategy existed. Additionally, priorities for improving the patient experience varied widely across these groups, showing a lack of consensus and alignment.

The AI-driven simulation revealed four core pillars essential to delivering an outstanding patient experience, each accompanied by actionable tactics to enhance the patient experience.

This research closed long-standing knowledge gaps and equipped the organization with tangible, cross-functional focus areas to drive patient-centered transformation at scale.

Three Game-Changing Benefits: Why AI Simulation Leads to Uncommon Growth

1. Acceleration Without Sacrifice

In a world where customer expectations and market conditions evolve at lightning speed, waiting weeks for static insights is no longer good enough. Simulation can help collapse months of work into 24-48 hours. These accelerated insights empower companies to respond to market signals, emerging risks, or new opportunities in near real-time, fueling not just quick wins but sustainable growth.

2. Access to Insights you Couldn’t get Before

The old approach relied on your ability to recruit a qualified research panel or persuade someone to take a survey. With simulation, you break free of those limits. You can now reach and analyze audiences that were once inaccessible. Whether they are emergency care patients, users of third-party risk management software, or clinical engineers, to name a few examples of engagements Aaru and Prophet have collaborated on. More importantly, audience simulation and predictive modeling unlock a new layer: understanding not just what your customers say, but modeling what they actually do across an expanding set of complex, real-world touchpoints.

3. Anticipation That Drives Action

Simulations don’t just report on the past; they illuminate the path forward. Through advanced modeling, you gain predictive insight into customer behavior — forecasting outcomes, quantifying risk, and testing “what if” scenarios before making big bets. This elevates decision-making from reflective to proactive, enabling organizations to enhance customer journeys, mitigate churn, or unlock new innovation ideas in a way traditional analytics simply cannot match.

You can now answer questions such as:

  • How will customers’ experience expectations evolve in 3 years?
  • How will changes in pricing or a new feature rollout impact different high-value customer segments?
  • Where are the breakpoints in a cross-channel journey that drive churn?

The Future: Growth Through Unlocked Intelligence

AI simulations are not merely efficiency tools. They are growth engines — providing leaders with accelerated insights, predictive models, and access to customer truths that were once off-limits. Through the Prophet / Aaru partnership, the horizon for customer experience has expanded: growth is no longer gated by the limitations of legacy research.

Business Strategy

FINAL THOUGHTS

As these technologies evolve, the best organizations won’t just move faster — they’ll see further, know their customers more deeply, and act with precision on opportunities hidden from their competitors. Don’t settle for yesterday’s answers. The future of growth starts with intelligence that was previously out of reach. Contact us for a Rapid CX Assessment using AI Simulation.

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The Middle Manager Multiplier

Why investing in the next level of leadership unlocks organizational growth.

As corporate leaders assess company performance, raises and bonus distribution, it’s imperative that they prioritise middle managers. Middle managers are the linchpins of organizational health, translating strategy into execution, culture into action and performance into results. It defies reason why these dogged workhorses climbing corporate ladders don’t get the investments they need to help them soar before they lose their footing.

In a 2024 survey, 75% of millennial middle managers reported feeling overwhelmed, stressed, or burned out — and nearly half said they were considering leaving their roles. These managers are feeling pressure from all sides: 39% cited increased pressure from senior leadership, while 37% pointed to greater demands from their teams.

Same holds true for middle managers. It’s senior leaders who get the shiny new toys. They get up to bat first when there are exclusive training programs and executive coaching sessions to be had. First to get rewarded when performance metrics are met. Front-line workers are also nurtured and groomed, given access to tools and training while they settle in and grow. Not so much for those in the middle. They’re expected to translate, deliver and execute sans the tailored support they so often need.

What a miss.

According to Gallup, 70% of the variance in employee engagement is directly attributed to the manager. McKinsey reports that companies with strong managerial capabilities deliver returns to shareholders that are 21 times greater than those with weaker managers.

So what do middle managers really need — and how can organizations better support and unleash their potential?

1. Make Their Lives Easier

Middle managers are drowning in complexity. Simplify wherever possible: streamline workflows, reduce administrative burdens and equip them with intuitive tools.

And communicate with them. It’s one of their biggest pain points. Establish dedicated manager forums or communities to serve as both peer support and direct communication channels. Make information easy to access, tailored to their needs and rooted in shared experience — not buried in intranets or lost in long email threads.

2. Give Them a Seat at the Table

Managers are uniquely positioned. They have proximity to the front line, insights into customer pain points and an intimate view of what’s working — and what’s not — on the ground. Treat them as strategic partners and reward them as such. Create intentional touchpoints between middle managers and senior leadership to foster transparency, trust and dialogue. Share how decisions are made, invite their input and — critically — close the loop by acknowledging when their feedback influences change. Visibility into impact fuels engagement and retention. And it just feels good.

3. Support Them as People Leaders

Many middle managers were promoted for being strong individual contributors but haven’t received the support to evolve into effective people leaders. They’re expected to motivate, coach and lead — but may not have the tools to do so. Invest in them and the dividends will flow.

When a healthcare client was introducing a new, simplified purpose, leadership made the strategic decision to create manager-specific summits that made the content and experience accessible to this critical level of leadership. The content and training were tailored to this audience, focused on equipping managers to bring the new organizational mantra to life through day-to-day coaching and recognition, compared to more strategically for senior leaders. Participants voiced appreciation that middle managers were trusted and engaged to lead the rollout which fuel-injected its success.

4. Empower Their Decision-Making

Managers want to lead — not just follow orders. Give them autonomy, backed by the right guardrails. Allstate introduced a decision-making model where senior leaders took on the role of “navigators,” while middle managers were cast as the “drivers.” This metaphor wasn’t just symbolic — it represented a tangible shift in accountability and empowerment.

With senior leaders as coaches, not bottlenecks, middle managers gained confidence and clarity in their decision-making.

5. Recognise and Develop Them

Middle managers carry immense weight — yet their efforts often go unacknowledged. Recognition doesn’t have to be flashy. Career development opportunities, visible appreciation and meaningful decision-making authority all go a long way.

In fact, McKinsey found that middle managers value empowerment — such as being trusted to make decisions — just as much as financial rewards. So as the year winds down, consider both intrinsic and extrinsic motivators when designing recognition strategies.

​Unilever’s FLEX Experiences, for instance, gave talent the chance to raise their hand for new internal projects across the organization. Expanding the pool for talent beyond typical structures, the AI-powered program helped align individuals on passion projects.

Organization & Culture

FINAL THOUGHTS

Middle managers serve as the vital heartbeat of any organization, and they deserve a starring role rather than a seat in the wings. By clearing away the administrative cobwebs, elevating their strategic voices and fueling their growth as people leaders, companies unlock a treasure trove of untapped potential.

If you’re curious to explore how mastering middle manager management can become your secret competitive weapon, I’d be delighted to swap ideas over coffee. Let’s turn everyday chaos into triumph together.

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Which Ads Ruled the Super Bowl? 

The good. The bad. The chaotic. Our writers break down the tape.  

Advertising’s biggest day has come and gone, and we’ve been all abuzz with what went on between game action last night (because let’s face it, anything was more exciting than that snoozefest of a game). Super Bowl LX blessed us with all types of ads, such as ads for AI, ads making fun of AI, and even ads for AI that made fun of AI. But despite the AI excess, there was still a wide range of advertising approaches — from absurdist humor and celebrity cameos that capture the cultural zeitgeist, to cinematic restraint and concept-driven storytelling.

We asked three of our writers to share their standouts — exploring how today’s brands are balancing big entertainment with uncommon brand impact.

Spencer Roth-Rose
Senior Copywriter, Campaigns

Spencer is a senior copywriter for campaigns at Prophet. As a New England native, he really misses Tom Brady right about now. 

Big Stage, Bigger Pivots 

The spotlight of the Super Bowl is a perfect excuse to double down on your brand identity. And whether it’s the annual Budweiser Clydesdale show or the latest chapter in Dove’s campaign for body confidence, this year’s edition definitely played some of the hits we’ve come to expect. But I couldn’t help but notice that it seemed like more brands than usual were pushing something new: new markets, new products, new category pivots. Is using the biggest night in advertising as a brand transformation milestone a smart play, or is it a gamble that might be regretted a year or five down the line? The following brands have a lot riding on the answer.

Fanatics

Video Source: YouTube / Fanatics

What better way to grab eyeballs for your sports betting product than during the biggest sports betting event of the year? Fanatics, better known for its sports merchandise and collectibles, showed up big on Sunday with 90 seconds of a self-aware Kendall Jenner poking fun at the “Kardashian Kurse” meme and reinforcing Fanatics as a shiny, new-ish face on the sportsbook block. It’s a bold splash, and a major bet that it can successfully leverage its existing sports fan relationships to continue making a dent in a very crowded category. Luckily, the spot itself hits, with laughs, glitz, and a single, high-concept idea (a Big Game rarity these days) that effortlessly speaks the language of the target audience — and made the less sports-inclined at the Super Bowl party sit up and take notice.

Kinder Bueno

With a $100 million spend between the Super Bowl and World Cup this year, Luxembourg-based confectioner Ferrero is making no mistake: it wants to become a household name on this side of the pond. The 30-second buy at the Super Bowl was Kinder’s biggest U.S. cultural investment to date as the company seeks to compete with Hershey and Mars in the long-entrenched American candy landscape. But did the spot itself, for the Kinder Bueno chocolate bar, pay off? Starring media personality Paige DeSorbo and Guy-Who’s-In-Stuff William Fichtner in a chaotic sci-fi disaster, it was a bit of a mess — but at least the campaign tagline “Yes Bueno” (a play on “no bueno”) nods nicely, if not accidentally, to the multicultural origins of the brand. Chocolate does, after all, taste the same in any language.

Liquid Death

Liquid Death participated in its second straight Super Bowl — just in time for its largest category expansion ever. The beverage disruptor is betting that its “better-for-you” energy drinks, which hit the market last month, can capture energy drinkers who are already loyal to the brand. But how did its irreverent brand voice translate into the hype-fueled and crowded energy drink market? Pretty well, actually. By calling out how its Sparkling Energy drinks have, well, a normal amount of caffeine versus the overloaded competitors via a fun exploding-head metaphor, Liquid Death is showing that its brand voice is deft enough to flex to a more mainstream audience — while still retaining its edge. 

Hannah Anderson
Senior Associate, Verbal Branding 

Hannah is a senior copywriter that’s been cheering on Advertising’s biggest night for years, but shamelessly flipping back to the Puppy Bowl between the “football” breaks.

Celebrity Voice, Meet Brand Voice

Much of Sunday’s ad lineup was a celebration of silliness, slapstick, and shtick, as absurdist escapism and social media-esque “brain rot” continue to infiltrate corporate strategy. And the vehicle of choice? Celebrities. Lots of celebrities.

Listening closely, I’ve noticed that the most effective shenanigans share a common thread: scripts built around the distinct personas of the celebrity(s) in the spot. When the humor aligns with their reputation, it helps justify why they’re in the ad to begin with. These spots also land best when the punchline connects back to the brand or product strategy cleverly and clearly.

Hellmann’s

Video Source: YouTube / Hellmann’s

Choosing a known-for-nonsense comedian for a full-fledged parody makes total sense, so I see where Hellman’s was going with this one. However, as I listened to Andy Samberg, AKA “Meal Diamond,” belting out punny lines like “sweet sandwich time” and “ham touching ham,” I felt the spot begin to drown in its own chaos. The product itself got lost somewhere between the joke lyrics and the escalating spectacle. By the time I reached the endline, “it’s sandwich time,” it felt as ancillary as the two-second Elle Fanning cameo. Looking back, I couldn’t help but think last year’s “When Harry Met Sally” reference depicting a mayo-fueled foodgasm “hit the spot” a little more clearly.

Bud Light

The teaser introduced its celebrity trio and established the campaign’s voice. In a wedding guest carpool, Peyton Manning, Post Malone, and Shane Gillis fall into an easy, conversational rhythm that feels more like a podcast than a commercial. It’s loose, unfiltered, and uncensored, creating humor that’s driven by personality — not plot. Post brings a breezy goofiness — “tapping the keg” — that sets the playful baseline. Shane adds comedic riffs like “a little tippy tappy,” giving the dialogue a scrappy, improvisational feel. And Peyton’s earnest, dad-next-door delivery (“my favorite part right here”) grounds the trio with a tone that’s warm rather than polished.

In the prime-time spot, “Keg,” the brand trades in bro-down banter for situational absurdity, as the entire wedding party hurls itself down a steep hill after their light beer supply. And while dialogue is minimal, personalities stay sharp: from Peyton’s sincere “First beer of the wedding” toast to Shane’s dry “I give it a week” close. The spot grounds slapstick chaos in an established chemistry that not only pays off the escalating absurdity, but makes the tone feel cohesive and unmistakably Bud Light.

Instacart

Where Bud Light’s ad felt tailor-made for its cast, Instacart’s “Half Brothers” approach to voice felt only half-natural. On one end, Ben Stiller’s character plays something like an ‘80’s-era cocktail of his Dodgeball and Zoolander personas — bold, clueless, and self-absorbed. Meanwhile, Benson Boone’s presence, though loosely tied to his sense of showmanship, feels more like a generational nod to younger viewers than a true match with Stiller’s unbridled energy. Add the accents and stage-trick flip-off, and the connection to the brand drifts even further. The message of “Choose your bananas” gets swallowed by slapstick spectacle and unrelated chaos — no matter how impressive the gymnastics might be.

Bella Courtenay-Morris
Director, Verbal Branding

Bella is a verbal branding expert at Prophet and ex-agency writer — she grew up watching rugby and only watches the Super Bowl for the halftime show and the ads.

When Less is More (Memorable)

As Hannah and Spencer noted, we saw a lot of celebrity cameos, musical performances, stunts, and shock value — often, all at once. Many brands took a maximalist approach to attention-grabbing, one that I worry prioritizes the “wow factor” over a winning message. Despite star power, color, and chaos, when you blur your eyes, it’s easy for one ad to bleed into the next. The tradeoff of this nonsensical maximalism is “attribution loss.” Viewers remember the joke or the celeb, but not the brand.

Amid the sensory overload, emotional storytelling with cinematic restraint became radical. Those who stripped away the spectacle to focus on a singular, driving concept may have a higher chance of brand recall in the days to come. Or better yet, audiences might even be compelled to make a purchase. From talking toilet lids to heartfelt intergenerational moments, a few players caught my eye — not by doing the most, but by doing less with more conviction.

Anthropic – Claude

Video Source: YouTube / Anthropic

I had high hopes for the OpenAI spot this year, but instead, its rival’s Super Bowl debut caught my attention. Anthropic chose the biggest advertising stage to poke fun at how annoying advertising can be. No celebrity or showmanship, just a clearly scripted competitive dig. The spot hinges on the simple insight that ads in AI conversations aren’t fun. In fact, they’re pretty dang disruptive. By parodying a typical chat conversation interrupted by unrelated marketing schemes, Anthropic positions Claude as the anti-ad chat service. I do wish they kept the spot to the single defiant promise from the pre-released versions, “Ads are coming to AI. But not to Claude,” rather than adding the slightly longer explanation, “There is a time and a place for ads — and AI conversations aren’t one of them.” Regardless, this spot is a great reminder that sometimes it’s just as effective to highlight what you don’t do to position your brand favorably.

TurboTax

I’m not suggesting that cameos and cinematic restraint are a tradeoff. Especially when casting makes sense for the brand. In its teaser, TurboTax led with (and repeated) a singular message: “I can handle that for you.” And in the aired spot, Academy Award-winning actor Adrien Brody brings the drama, preparing for his new role as a tax expert. But to Brody’s confusion, it’s revealed that TurboTax takes the drama out of doing your taxes. The juxtaposition of a serious drama actor trying to make sense of drama-free taxes resonated. And this core idea, central to its brand identity, is repeated in various ways (à la, “We take the pain out of taxes, remember?” or “Sorry Adrien Brody, now taxes are drama-free.”), making it stick. Will more people turn to TurboTax this tax season? I’m curious to see.

Budweiser

In my mind, Clydesdales = Budweiser. And the brand returned again to its go-to symbol in this year’s spot. While it may be expected, the brand isn’t trying to reinvent the wheel. Instead, Budweiser continues to cement its reputation for heritage, quality, and tradition as an “American Icon,” tying its own iconography to the bald eagle. Using the musical backdrop of Lynyrd Skynyrd’s “Free Bird” and a cinematic Americana aesthetic, the spot shares an emotional story of two “buds” growing up together. This unlikely friendship makes sense for the brand. And despite no copy or voiceover until 50 seconds in, the simplicity, emotional resonance, and brand fit made the “Made of America” message memorable.

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OUR FINAL HANDOFF

Interested in working with an uncommon creative partner that knows how to turn what you say and how you say it into uncommon growth for your brand? 

Reach out to our team today.

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NEW RESEARCH

Growth and Transformation: The CMO Paradox

CMO Briefing: Leading Marketing’s Next Great Reboot in the Age of AI

Marketing’s mandate has never been more complex or more critical, with CMOs simultaneously accountable for near-term growth and the transformation of the systems, skills, and structures that power it. Our latest CMO briefing report outlines the five shifts redefining modern marketing, from hyper-personalization and creator-led culture to AI-driven journeys and the collapse of the traditional funnel. 

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NEW RESEARCH

Growth and Transformation: The CMO Paradox

CMO Briefing: Leading Marketing’s Next Great Reboot in the Age of AI

Marketing’s mandate has never been more complex or more critical, with CMOs simultaneously accountable for near-term growth and the transformation of the systems, skills, and structures that power it. Our latest CMO briefing report outlines the five shifts redefining modern marketing, from hyper-personalization and creator-led culture to AI-driven journeys and the collapse of the traditional funnel. 

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The Five Shifts Rewriting Marketing 

01

Hyper-Fragmentation and Personalization 

02

Algorithm-Curated Culture 

03

The Ever-Collapsing Funnel 

04

AI is Changing the Game 

05

Brand and Performance: Escaping the Short-Term Doom Loop 

The brands that will lead are those that act now to future-proof their marketing engines by embedding AI with intent, uniting brand and performance, and investing in creativity that converts.  

The Five Shifts Rewriting Marketing 

01

Hyper-Fragmentation and Personalization 

02

Algorithm-Curated Culture 

03

The Ever-Collapsing Funnel 

04

AI is Changing the Game 

05

Brand and Performance: Escaping the Short-Term Doom Loop 

The brands that will lead are those that act now to future-proof their marketing engines by embedding AI with intent, uniting brand and performance, and investing in creativity that converts.  

What Comes Next?
Building the Reboot. 

The next era of marketing will be defined not by tools, but by leaders who apply them with imagination and resolve. Today’s CMOs sit at the intersection of growth and transformation, where human creativity meets machine intelligence to connect what drives revenue with what drives meaning.  

At Prophet, we help leaders turn disruption into direction to power modern growth.  

What Comes Next? Building the Reboot. 

The next era of marketing will be defined not by tools, but by leaders who apply them with imagination and resolve. Today’s CMOs sit at the intersection of growth and transformation, where human creativity meets machine intelligence to connect what drives revenue with what drives meaning.  

At Prophet, we help leaders turn disruption into direction to power modern growth.  

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 Growth and Transformation: The CMO Paradox

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Designing a Healthier AI Future 

How AI can enhance and create new value across the patient experience. 

AI offers significant promise to help solve long-standing challenges in the U.S. healthcare system. Some gains are already well documented, from diagnostic tools and curriculums to GenAI-powered transcription and coding solutions.  

But the U.S. healthcare ecosystem is also one of the most fragmented, complex and data-sensitive industries within which to consider effective AI implementation on a broader scale. As we step into 2026, amid the rapid evolution of AI capabilities, continued public concerns and a capricious regulatory climate, it’s necessary for healthcare leaders across systems, payers and technology solutions to identify how to use AI for lasting value, and identify the greatest areas of untapped potential in ways that make sense for patients and caregivers. 

To address this challenge, Prophet’s Healthcare team took a consumer-centered lens, starting with our global AI survey, to understand where people see opportunities for AI to add value to their healthcare experience. We then engaged AI-focused healthcare leaders to react to these consumer views and share their own perspectives on opportunities across the patient journey. 

Our research explored two key questions: 

  1. Where can AI unlock value in the consumer experience? 
  2. What must be true within organizations to realize that value ethically and effectively? 

Opportunities and Organizational Imperatives 

While there are countless potential areas for adding value, our study found that consumers across generations and demographics want AI tools in healthcare to help them personalize their experience (63% of consumers agree or strongly agree that Gen AI will help with health monitoring and proactive advice, and also save them time and money). This was balanced with clear preferences to maintain the human element of healthcare, with consumers pointing out the AI should not be the final decision maker in place of a doctor, nor should it be so intrusive that it’s always monitoring them without their control (“I really see AI as just helping us, but it’s not the final say [in medical decisions].”). Our leader interviews also revealed similar opportunities to meaningfully enhance care beyond the patient visit, improve navigation, and streamline the way people experience healthcare. These findings point to three key areas of opportunity for healthcare leaders across the ecosystem to capitalize on AI while balancing patient autonomy and dignity, which are:  

  • Guiding Care: Navigation tools that reduce system complexity
  • Personalizing Care: Personalization that respects autonomy 
  • Extending Care: Coaching models that scale support out of acute care facilities 

We also recognize that identifying the opportunity area won’t spell success without the organizational environment to succeed. Our interviews validated how leaders must understand how to translate opportunities in ways that will be most relevant for the unique populations they serve and operationalize AI tools with governance and foresight. This all means that there are critical organizational and cultural components to successful AI adoption that go beyond the data backbone and infrastructure, namely:  

  • Setting a strategic vision  
  • Implementing a governance model that can adapt 
  • Addressing change management & cultural adoption 

We explored both the consumer-focused opportunity and the organizational requirements for healthcare companies to succeed with AI. 

Opportunity 1: Guiding Care – Navigation Tools That Reduce Complexity 

Navigating U.S. healthcare is notoriously difficult, and often the most complained about pain point in healthcare, from finding care and resources to demystifying pricing and payments (Tufts). It’s also an area where patients typically don’t have the benefit of reaching a human to help them, which costs them significant time. In 2024, nearly two-thirds of physicians used AI for documentation, diagnosis, and care planning (AMA), but on the patient end, there’s a need for AI tools to similarly save time and effort. Given the capabilities for AI tools to synthesize data and summarize disparate information, this is one, if not the biggest, area for AI to enhance the patient experience, particularly in micro-moments where patients feel most burdened.  

There are good reasons why care navigation remains a clear opportunity. Patients are engaging with a deeply fragmented ecosystem that no single player in the healthcare ecosystem can solve. Healthcare leaders across providers and payers might start small, through “narrow applications to alleviate specific pain points across the journey” as one leader whom we spoke with pointed out, but over time these AI-driven solutions can serve the incredible value of empowering with options and enabling patients to make clear decisions about their health providers, treatments and costs. 

Opportunity 2: Personalizing the Experience – Personalization That Respects Autonomy 

Personalization is the cornerstone to humanizing the healthcare experience, but the U.S. healthcare system isn’t delivering (Harvard Business Review) despite consumer preferences (Human Centered AI: Culture as the Catalyst for AI-enabled Growth). With the computing power of AI there’s clear opportunity to enhance how patients feel known, heard and understood to add to moments of care, but also to add value across the entire healthcare journey in ways that have never been done before.  

When integrated into care delivery, AI-driven personalization can help redefine patient engagement and amplify the patient-provider connection, equipping providers with comprehensive patient health reports, patients’ ingoing questions and personalized therapeutic options so that patients feel known and understood. As noted by the leaders we interviewed, when AI is deployed transparently in the care setting and decision-making stays with the provider, it’s a win-win in terms of value and trust building. Outside of the doctor’s office, AI-powered personalized platforms can enable real-time personalization (and assistants) that give patients more peace of mind and control of their health management, such as we’re starting to see with Twin Health, Televox, Luma Health, Klara, and others. Capitalizing on AI-driven personalization can also extend beyond care, affording patients greater access and options to suit unique preferences, language needs and lifestyles. The opportunities for AI-driven personalization that enhance the patient experience are rich, and while much has been discussed about the limitations of data and privacy, with the right design, there’s a wealth of value in even the earliest steps forward. 

Opportunity 3: Extend It – Engagement Tools Augment Remote Care

Extending care delivery without compromising quality is an ongoing, major challenge where patients are often left without the support they need, particularly within the context of chronic care needs. Here, AI tools can provide significant value that patients feel immediately. This can include AI tools for prospective care (monitoring and anticipating risks based on patients’ lifestyle choices, adherence and activity levels), to responsive care that enables more orchestrated, complete care across the patient journey. Remote care companies are leading the charge with new AI platforms, such as Teladoc Health’s intervention-focused AI-model, and Verily’s Onduo for coordinated virtual care of chronic diseases. These platforms bring care out of the clinic in ways that go far beyond the remote models of the past decade, and there’s a significant opportunity to capitalize on this opportunity across the healthcare ecosystem.  

What It Will Take to Deliver  

As we’ve noted above, adopting AI tools for the patient experience requires a host of careful considerations about patients, their privacy and your organization, as well as examining emerging regulations and ethical guidance. The leaders we spoke with emphasized not only the opportunities, but also the challenges with organizational silos, data readiness, and cultural burnout or skepticism. As we think beyond the opportunity and start to address the organizational component to power effective AI in healthcare, most leaders are immediately focused on the infrastructure and workflow integration, which is essential. But any AI driven transformation should be focused on adding value for people so they are guided, equipped and empowered to be successful with new AI tools, particularly along the patient experience. 

At Prophet, we help organizations embed AI into their DNA, mind, body, and soul, aligning purpose, scaling skills, redesigning workflows, and deepening human connection.  

DNA: A Consumer-Backed Strategic Vision  

A successful consumer-oriented AI strategy begins with a clear vision for how AI will enhance consumers’ patient experience, which should include defined goals and targeted use cases based on clear patient and provider needs, particularly as organizations seek to balance adding sustainable value without breaching confidentiality or trust. We’ve identified three broad needs, but any AI-driven strategy will need a depth of understanding for how these needs can best be addressed in context. 

Body: Governance That Champions Transparency and Security  

Strong AI and data governance is essential to unify accountability, transparency, and security across the organization. In the context of an AI-enhanced patient experience, leaders also emphasized how governance and human oversight need to extend to the caregivers themselves, to ensure there are clear systems for active oversight. Plus, as AI tools become more broadly used, governance needs to include ongoing assessments to identify gaps in underserved populations and to monitor AI model behavior for fairness and accuracy. Clear liability structures must also be established to protect clinicians and patients, while ensuring compliance with regulatory standards and ethical guidelines. Multidisciplinary teams beyond the care setting, including data scientists and IT professionals, should be formed to support implementation and maintenance.

Soul: Employee Engagement & Cultural Adoption 

Effective employee engagement is critical to drive adoption and minimize resistance. This involves crafting a comprehensive plan that fosters engagement and collaboration across all levels of the organization. Bridging the gap between executives and frontline staff by involving both in planning and decision-making helps build trust and accelerate cultural adoption of AI technologies. 

For more read our research report, Human-Centered AI: Culture as the Catalyst for AI-enabled Growth. 

Organization & Culture

FINAL THOUGHTS

Healthcare organizations across the ecosystem are navigating a complex reality today: legacy systems, overburdened and siloed teams, and the pressure to adopt compliant AI tools that deliver on consumers’ needs. But to stand out, you’ll need to move forward, and we believe the most differentiating moves lie in a focus on improving the patient experience for value, while respecting their autonomy and building trust. When coupled with the organizational components that help people inside of the organization deliver, healthcare leaders will be able to unlock sustainable, ongoing value and steward AI adoption in ways that are not only compliant but also compassionate. 

Ready to explore what human-centered AI can do for your organization? Connect with us to discuss a kickstart workshop to help your team evaluate hypotheses and opportunities to inform your strategic vision for AI. 

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Beyond NEO Luxury: How Premium Brands Can Prepare for Radical Change 

What does a custom GPT reveal about the future? 

Every luxury brand needs a proactive approach to growth, whether that means adapting to shifting consumer attitudes, leveraging technology, or identifying new markets. One thing is certain: foresight and imagination are essential to staying ahead. 

Prophet’s Jörg Meurer has advised luxury brands for almost two decades. In this interview, we explore the concept of NEO Luxury and ask: What’s next? 

Prophet has been talking about the concept of NEO Luxury for more than five years. What does it mean? 

Brands at the premium end of the market are used to navigating major changes, most recently the rapid adoption of AI. They must constantly stay on the front foot when it comes to engaging with existing and future consumers, understanding their markets and turning innovation into profit.  

Until now, the luxury industry’s timeline can be categorized into three phases: First, classic luxury, which focused on exclusivity, ownership and craftsmanship, with tightly controlled distribution and elite audiences. Second, new luxury, which was a shift toward experiences, personalization and emotional connection, thus making luxury more accessible and lifestyle-oriented for consumers. Third, NEO luxury, a forward-thinking model for brands, integrating sustainability, technology, and purpose-driven values to redefine exclusivity and deliver ethical, experiential luxury.  

In 2019, we released a study examining the move toward NEO Luxury in collaboration with Dr. Julia Riedmeier, an international luxury brand strategist, renowned luxury expert, and the founder of Code \ Luxe. Fast forward to 2026: the big question for luxury and premium brands is what comes after NEO Luxury? 

How can brand leaders begin to anticipate what comes after NEO Luxury? 

It’s a bit more complex than simply asking ChatGPT. But, we did call upon AI to develop our initial predictions and remove some of the guesswork. 

Brands can find answers by combining structured foresight with creative hypothesis-building. So how does this work in practice? We created a custom GPT model to generate a couple of plausible scenarios for the future of luxury. We wanted each to be grounded in emerging signals but to also consider bold possibilities. These scenarios were not to be taken at face value; instead, we applied a curated, critical lens to evaluate their underlying assumptions, cultural implications, and potential business impact.  

This approach allows brand leaders to move beyond reactive thinking and into proactive innovation. By stress-testing these hypotheses and identifying accelerators, such as technology adoption, new collaboration models or shifts in consumer values, brands can chart a course toward the most promising directions, often before the market realizes they exist. 

What were the three potential futures for uxury imagined by the GPT model? 

Conscious Culture Luxury 

By 2028, luxury may be less about ownership and more about cultural and emotional intelligence. Status will come from understanding, not accumulating. Brands become “curators of meaning,” offering spaces for reflection and cultural exchange. Technology plays a quiet role, helping us slow down and connect rather than overwhelm. Think cultural travel, hybrid craft and psychological well-being shaping the experience. 

Neo Human Luxury 

With technology advancing at such speed, luxury may focus on the dignity of being human. Technology becomes a tool for empathy and well-being, not distraction. Expect bio-luxury (health tech and longevity) to be paired with radical transparency and “quiet AI” that understands rather than sells. Ownership fades as experiences and self-cultivation take center stage. Imagine studios dedicated to mental craftsmanship and mindfulness. 

Luxury Quantum 

Imagine a future where luxury isn’t confined to physical objects or digital screens but exists in a seamless blend of both. In this scenario, experiences become “phygital rituals,” combining real-world touchpoints with immersive virtual layers. NFTs evolve beyond collectibles into emotional artifacts, carrying meaning and memory, for example art pieces. The virtual world is enhanced by sensory technology, adding smell, sound, and touch for truly multisensory engagement. AI companions act as personal curators, shaping lifestyles and guiding choices. For brands, this means moving from selling products to designing entire alternative realities, spaces where identity, creativity and consciousness come together.  

Coming back to the present, what should premium brands be thinking about right now? 

Six years after we began to define NEO Luxury, the scenarios above are just the beginning of future thinking on this topic. The idea of “Luxury Quantum” may seem very futuristic, maybe even far-fetched, but we need to be open to a number of possible scenarios.  

In the near-term, luxury brands must balance heritage with innovation, embrace ethical transparency, and integrate technology thoughtfully. When creating experiences, they should prioritize cultural relevance, human well-being, and immersive engagement to stay competitive in today’s ever-changing market. 

Marketing Excellence

FINAL THOUGHTS

It’s a fascinating time for brands to be in this space, and the winners will be those who understand how to deepen customer trust and take an imaginative approach to creating long-term value.

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Five Ways GenAI Helps Turn Marketing into a Growth Driver 

How leading marketers use GenAI to sharpen decisions, strengthen brand impact, and directly drive revenue growth. 

Seventy percent of CEOs report measuring marketing performance based on revenue growth. Yet for many organizations, marketing is still treated as a cost center, not trusted as a primary growth engine. 

The tension has never been more acute. Marketing leaders are navigating tighter budgets, longer sales cycles, fragmented customer journeys, and rising expectations for personalization all while proving impact with fewer resources. At the same time, GenAI is moving from experimentation to enterprise reality. But the tendency to see GenAI as a solution for reducing marketing costs misses the real opportunity to apply it in ways that credibly drive growth. 

What we’re seeing in the market is clear: GenAI is not just accelerating how marketing work gets done, it is changing who marketers are marketing to, how decisions get made, and how growth is earned and defended. The emergence of the “AI-powered consumer” in which machines increasingly surface options while humans make meaning, demands a different approach. 

For constrained teams, the opportunity isn’t to “do more marketing.” It’s to use GenAI as leverage: to reduce risk, sharpen focus, and connect marketing activity more directly to revenue outcomes. 

Based on our work helping organizations increase their AI-enabled marketing maturity, five use cases consistently separate teams that create growth credibility from those that simply create more output. 

1. Dynamic Audience Understanding: Maintaining Decision-Ready Audience Insight in a Constantly Shifting Market 

Traditional segmentation was designed for a slower world — annual refreshes, static personas, and assumptions that held long enough to matter. That model can break down in B2B environments with long buying cycles and in mid-market organizations where missed signals are expensive. 

GenAI enables a shift from static segmentation to living audience intelligence. By continuously analyzing behavioral, transactional, and engagement data, structured and unstructured, AI can surface early demand signals before they appear in CRM or pipeline reports. It allows teams to re-cluster audiences dynamically as motivations shift, markets evolve, or new use cases emerge. 

The real advantage here is not precision for its own sake. It’s being less wrong, earlier. 

For B2B marketers, this means understanding which accounts are warming before sales see it, which buyer assumptions are eroding, and where emerging needs are forming at the edges of the market. For mid-market teams with limited research budgets, GenAI acts as a translator, extracting insight from imperfect data rather than waiting for pristine inputs that never arrive.  

Increasingly, marketing teams are augmenting their first-party data and traditional research with cultural and behavioral intelligence platforms such as Quilt.AI and HiveScience.AI, which ingest millions of digital conversations across professional communities, industry forums, social platforms, and expert networks. These tools surface how buyers frame problems, evaluate trade-offs, and influence one another long before intent appears in CRM or marketing automation systems. Rather than relying only on survey responses or owned-channel behavior, marketers gain visibility into the narratives shaping demand inside peer groups, communities of practice, and category conversations. As influence, trust, and purchasing decisions increasingly form in these distributed B2B ecosystems, this layer of intelligence helps brands design strategies, campaigns, and creative that align with how buying groups actually think, talk, and decide — keeping marketing grounded in real market momentum, not internal assumptions.  

Some organizations are taking this further by simulating customer reactions to new product ideas, value propositions, or messaging using AI-powered behavioral modeling. Others deploy those digital twins of key personas to create a shared, evolving understanding of customers across marketing, sales, and products. 

In all cases, the outcome is the same: fewer wasted bets, sharper prioritization, and more confidence in where growth actually lives. 

2. Consistent Brand Experience: Turning Brand into a Force Multiplier 

Brand governance is often misunderstood as bureaucracy – layers of approval that slow teams down. Inconsistency is far more expensive. It creates friction in sales, dilutes the effectiveness of performance marketing, and forces constant rework across decentralized teams. 

GenAI allows marketing leaders to codify brand strategy into scalable systems designed for decentralized teams. These tools can monitor brand expression across channels before assets go live, evolve storytelling across the funnel, and enable sales teams and partners to deliver on-brand experiences without constant oversight. For mid-market and B2B organizations, this reframes brand investment as efficiency, not overhead. 

When brand guardrails are built directly into workflows, teams move faster, not slower. Content is clearer. Sales conversations are more coherent. Every dollar spent downstream works harder. Marketing teams are leveraging custom GPTs and enterprise tools such as Writer.ai and Jasper.ai to enable teams and partners to leverage the brand voice and tone and create content that is consistent across the funnel while also being customized for the target audience. 

Additionally, the need for consistency is becoming more urgent as the funnel itself collapses. The journey from discovery to decision is increasingly converged and mediated by AI models, from search overviews to conversational assistants. In many cases, customers now form impressions, shortlist options, and even make decisions without ever visiting a brand’s owned channels. 

As a result, brands are losing direct control over how they show up at the moments that matter most. AI-generated summaries, featured answers, and zero-click experiences increasingly define the brand narrative, often compressing complex positioning into a few lines of synthesized output. The impact is already visible: historic drops in direct and organic traffic, declining click-through rates when AI overviews appear, and growing difficulty explaining performance shifts to executive stakeholders using traditional metrics. 

In this environment, brand consistency can no longer be managed solely through owned experiences or channel-specific guidelines. It must extend into AI-mediated discovery itself.  

That shift requires moving beyond a traditional SEO mindset optimized around keywords, rankings, and clicks to an Answer Engine Optimization (AEO) strategy designed for how AI systems interpret, select, and represent brands. As AI-mediated discovery accelerates and zero-click experiences reduce direct traffic, AEO becomes a critical growth lever, not just to protect brand consistency, but to mitigate lead erosion and revenue risk as traditional demand signals quietly disappear. 

The most effective leaders use GenAI not to control creativity, but to multiply it, enabling even the most bootstrapped teams to extract the most value from the brand across all of the moments that matter. 

3. Content at Scale: Orchestrating Insight and Creativity for Growth 

Content is where most GenAI adoption starts and where it often stalls. Producing more assets faster is easy. Producing the right content that actually moves buyers is harder. 

In an AI-saturated content environment, “more” is not a competitive advantage, difference is. When every team can generate competent copy on demand, the brand that wins is the one that creates distinctive, emotionally resonant work grounded in a sharper understanding of the buyer than competitors have. GenAI doesn’t reduce the importance of creativity; it increases the return on it. 

The real power of GenAI lies in connecting insight, strategy, and creation. By training models on customer personas, performance data, and channel context, teams can identify which topics, formats, and messages are most likely to drive value, then rapidly generate on-brand assets aligned to the funnel stage and buyer need. 

The biggest failure mode we see is not low adoption, it’s reliance on AI that produces AI-average work. GenAI is excellent at generating what is already common: category clichés, familiar narratives, and safe phrasing that passes a brand check but fails to earn attention or preference. That kind of efficiency can quietly stifle growth: it fills the funnel with content while draining the brand’s distinctiveness. 

Creativity is the counterweight. Distinctive creative work builds memory, creates meaning, and earns attention in compressed, AI-mediated journeys where buyers may encounter your brand through summaries, snippets, and secondhand interpretation. As discovery becomes more “zero-click,” the job of creative is not just to communicate, it is to stick. 

GenAI enables faster iteration, disciplined experimentation, and continuous optimization so teams can spend more time on the few ideas that will actually differentiate the brand. Content becomes a portfolio of bets, not a factory of outputs. 

Importantly, the highest-value creative inputs are still human: strategic judgment, cultural sensitivity, and the ability to introduce productive tension and say something specific enough that it excludes as well as includes. GenAI can help teams explore directions faster, but it cannot replace the brand’s point of view. The goal is not to automate creativity; it is to protect it from being flattened while scaling execution. 

When done well, creative capacity expands without diluting quality and marketing earns greater credibility by tying content directly to commercial outcomes. 

4. Always-On Insights: Ending the Quarterly Hindsight Problem 

Most marketing insights arrive too late to matter. Quarterly brand trackers, post-campaign analyses, and lagging performance reports explain what happened, but rarely when there was still time to act. 

GenAI changes this by enabling always-on intelligence systems that continuously monitor market signals, customer sentiment, competitive movement, and performance data across the funnel. Rather than waiting for formal research or reporting cycles, marketing leaders gain early visibility into shifts in perception, emerging objections, and changing expectations. While those shifts are still manageable. 

This matters deeply in B2B categories, where trust erosion often precedes pipeline decline and where sales friction shows up long before revenue does. AI-powered insight systems can model brand perception trajectories, forecast how marketing actions are likely to influence consideration or trust, and surface risks before they materialize in missed targets or stalled deals. 

But the most important shift is operational and commercial. Always-on insights make marketing performance easier to explain and defend. By unifying data across brand, demand, and sales systems, GenAI helps teams identify which KPIs connect marketing activity to revenue. It enables automated optimization loops, real-time budget reallocation, and scenario modeling that shows what is likely to happen next, not just what has already occurred. 

For leaders struggling with the cost-center perception, this is transformational. Instead of reporting past performance, marketing can recommend next actions and clearly articulate the trade-offs. Generative models allow teams to simulate future outcomes, test investment scenarios, and speak the language of finance: risk, return, and probability. Marketing evolves from an execution function into a decision partner in growth. 

The critical shift is to embed insights directly into decisions through content briefs, campaign prioritization, sales enablement, and spend allocation. For constrained teams, GenAI reduces learning costs and narrows the gap between signal and action. In an environment defined by uncertainty, speed and clarity of understanding become a durable competitive advantage. 

5. Future Back Planning: Designing Growth Around the Customer of the Future 

For many organizations, “whitespace” is still defined reactively: where competitors are weak today, where products don’t yet exist, or where demand appears underserved in current data. But in an environment shaped by GenAI, shifting buying behaviors, and accelerating category convergence, that approach is no longer sufficient. 

The most valuable whitespace opportunities sit ahead of demand, not behind it. They emerge at the intersection of how customers are evolving, how markets are fragmenting, and where competitors are structurally constrained by legacy assumptions. 

GenAI enables marketing and growth leaders to take a fundamentally different approach: identifying whitespace through a future-back view of the customer. 

Rather than asking only who our customers are today, teams can begin to answer deeper, forward-looking questions: who their customers are likely to become, what they will care about as AI reshapes work and decision-making, how their journeys will evolve, and how expectations around value, experience, and trust will shift over time. By decoding emerging market signals, early adopter behaviors, and disruptive forces, GenAI allows organizations to feed these inputs into predictive foresight models that simulate plausible futures. 

This capability is especially powerful in B2B categories, where buying decisions are increasingly shaped inside communities, peer networks, and ecosystems long before formal intent signals appear. GenAI can synthesize millions of conversations, behaviors, and signals to reveal not just unmet needs, but unarticulated tensions: where customers are struggling to reconcile old solutions with new realities, or where existing offerings no longer map cleanly to evolving jobs-to-be-done. 

From there, whitespace becomes clearer and more actionable. Teams can identify: 

  • Gaps between customer expectations and current category norms 
  • Opportunities competitors are unlikely to pursue because of their business models, capabilities, or positioning 
  • Emerging needs created by AI adoption itself — new workflows, risks, and sources of value 

This is not an abstract strategy exercise. GenAI allows organizations to simulate future customers across different scenarios, stress-test ideas before they go to market, and engage in “research” with modeled future audiences to understand motivations, trade-offs, and barriers. The output is not just insight, but clarity on what new products, services, experiences, or business models are most likely to resonate. 

The final unlock is cross-functional. When whitespace is grounded in a shared view of the future customer, marketing can help translate insight into implications for growth strategy, offering design, experience innovation, and capability building. Instead of chasing incremental differentiation, organizations align around where to place their bets and why. 

In uncertain markets, growth doesn’t come from filling gaps competitors leave behind. It comes from seeing where customers are headed next and building into that space before it becomes obvious. 

Experience & Innovation

FINAL THOUGHTS

GenAI will not turn marketing into a growth engine by itself. But it gives teams, especially those that are resource-constrained, something they have historically lacked: leverage. 

The winners will not be those who adopt the most tools, but those who apply GenAI where it reduces risk, sharpens focus, and strengthens the connection between marketing activity and business outcomes. 

For mid-market and B2B leaders under pressure to prove impact, that shift — from output to outcome — is what ultimately changes how marketing is valued. 

And in today’s environment, that may be the most important growth opportunity of all. 

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AI Is Everyone’s Luxury: Premium Brands Can’t Afford a Generational Blind Spot

How adoption is increasing across all age groups.

The biggest mistake luxury brands can make in 2026 is assuming AI only matters to younger customers. In reality, AI is reshaping consumer behavior across all generations, though its influence varies by age group. Brands must therefore keep pace with these shifts to stay relevant.  

Since 2018, we have been exploring the impact of AI on luxury brands as part of our bi-annual “Premium and Luxury Study.” Each wave surveys a representative sample of 1,000 German consumers, from Gen Z to Baby Boomers who regularly or occasionally purchase premium and luxury products.  

Our goal is to track how generational values and attitudes influence high-end buying behavior and purchasing decisions across age groups. Here are some of our findings from this year’s study. 

Search habits differ sharply across generations. Google is still firmly Baby Boomer territory, regarded as very important or important for 67% of respondents in this group, compared to only 41% of Gen Z. In contrast, 54% of Gen Z use social media for product searches, compared to only 29% of Baby Boomers.  

Millennials (40%) are the strongest users of retail platforms, such as Mytheresa and Net-a-Porter, for purchase decisions, compared to Gen Z (34%) and Gen X (38%). 

AI-Powered Convenience

The uptake of AI is making shopping much simpler, driven by the need for speed, simplicity, and ease of use. 78% of the total survey base actively uses AI regularly or daily, up from 73% in 2024. About 52% of all generations agree that AI will positively enrich their lives in the future. 

64% of Gen X and 61% of Baby Boomers say they actively follow developments and educate themselves on AI, compared to only 51% of Gen Z. One reason behind this response may be that Gen Z uses AI more intuitively. In contrast older generations feel the need to study to keep up with the changing trends. 

Convenience is a huge factor across all generations, with rapid AI adoption rates notably among older generations, being used to simplify forms and processes. Surprisingly, Baby Boomers (49.5%) value it more than Gen Z (44.5%). 

AI search driven by convenience plays a major role across all stages of the buying cycle, from inspiration to search and decision-making, and it is catching up with traditional tools. While consumers still rely on familiar channels such as brand websites (54%), Google search (55%) and social media (45%), we found a growing adoption of AI: 44% regularly use Google AI and 45% turn to platforms like ChatGPT and Perplexity. Given that search engines have dominated for over 15 years, this narrow 10% gap highlights the remarkable pace at which AI is gaining ground. 

Building Trust With Buyers

Trust plays a major role in consumer behavior. When asked which channels were most important for inspiration, research and comparison, and purchasing decisions, Baby Boomers showed the highest trust in official brand websites, with more than 60% considering them important. In contrast, Gen Z is more skeptical of official channels, with less than 50%, and prefers decentralized information on social platforms. 

When it comes to letting an AI agent make a purchase decision, there’s a noticeable openness across all generations: Gen Z (41.5%) and Millennials (42%) are almost on the same level and even among Baby Boomers, roughly one in three (32%) expresses willingness.   

Likewise, 43% of respondents trust AI in decision-making, such as using AI agents. A slight increase from 41% in 2024. Whereas, younger generations show 42% approval compared to Baby Boomers (27%).  

Both points signal reluctance but a growing interest among senior audiences, which has knock-on effects for brands.  

Since 2024, trust and data privacy concerns in AI have fallen from 51% to 45% across age groups. When asked about concerns regarding AI ethics, Millennials are the least concerned  (31%), followed by Gen Z (42%), Gen X (42%) and Baby Boomers (45%). 

One important lesson: Brands must harness AI for personalized inspiration without compromising privacy. It is also important to address ethical and data concerns proactively, as trust remains a key lever in brand leadership. 

Future-Proofing Luxury

Our analysis shows the real risk isn’t overlooking AI; it’s assuming its impact is limited to select customer segments, especially younger consumers. The implication for premium brands is that they can’t afford to dismiss AI’s universal impact. Likewise, they need to mitigate generational blind spots, as viewing AI adoption through a single generation’s lens creates a constrained understanding of how others think and engage with technology. 

With the rapid rise of AI-based search, generative engine optimization (GEO) is becoming a key driver of traffic and brand visibility. This will impact how luxury brands show up on platforms, differentiate themselves and resonate with audiences across generations.  

Marketing Excellence

FINAL THOUGHTS

In practical terms, luxury brands will also need to fully commit to integrating AI into the consumer journey from inspiration to the shopping cart. This means carefully designing customer-centric AI-based workflows, including for service experiences. 

The question is no longer if AI will influence consumer decisions, but how brands will integrate it to inspire, engage and build lasting loyalty.

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