Four Questions That Expose an M&A Brand Partner’s Real Capabilities
How to distinguish true expertise from a slick pitch.
Merger, acquisition, and carve-out activity is growing, which means more leadership teams are making brand decisions whose consequences will outlast the deal itself.
Yet when it comes to choosing an M&A partner, many default to the agency playbook: firms present their best work, the room reacts, and a shortlist emerges. That is the first mistake. Any firm on your shortlist can produce good work. What matters is everything the case study leaves out: shifting timelines, executive reversals, competing stakeholder agendas, and recommendations the firm had to defend.
So, change what you test in the room by asking the right questions. The best partner is not the firm with the best presentation. It is the firm that still adds value when the plan changes.
1. What needs to be defined before you can start this work?
Most M&A brand briefs arrive as a shopping list: a name, an identity, a Day One website, a launch film. Beneath it are unresolved questions about architecture, equity, customer risk and positioning. What looks like a design mandate is usually a strategic decision problem in disguise. Define only the outputs and you’ll get the outputs, while the real decision goes unchallenged.
A MIT Sloan study found that nearly two-thirds of large M&A deals gave brand strategy little attention, and 64% defaulted to the easiest option. Even though this study is two decades old, the pattern continues to persist: when leadership avoids a decision, expediency makes one.
A good answer identifies the unresolved decisions, distinguishes those that must be settled before design from those that can run in parallel, and sets out a path to resolution. A firm that accepts the brief and moves straight to timelines is positioning itself as a supplier. A partner will challenge the brief, uncover the decisions behind it, and help leadership make them.
2. Tell us about a deal that forced you to change course
The timetable you brief is rarely the one you live through. Deals are delayed, restructured, leaked, or reshaped by regulators. UBS acquired Credit Suisse in March 2023 and completed the migration of its roughly 1.2 million former clients only in March 2026.
Ask for the deal that went wrong. What changed? What did it cost? What would they do differently? Then ask about working before close, when clean-team restrictions, limited access to customers and employees, strict confidentiality, and a moving Day One shape every decision. Firms without that experience often reveal themselves by asking for information you cannot legally provide.
If every deal sounds smooth, keep probing. And notice whether the client is the villain in every story. In twelve months, that client may be you.
3. How would this strategic decision translate into real-world experience, and why?
This may sound like a premature question. It isn’t. You are not buying the work they show you. You are assessing whether a team can move from strategic argument to tangible expression, and back again.
That does not mean asking four firms to solve your assignment for free. Ask them to demonstrate that movement through relevant case work, a focused exercise, or a paid sprint on your actual problem.
Whatever the format, ask to see the idea where it will really be judged: the customer announcement, the first investor slide, the sales conversation in week two, the careers page. Not a logo on the side of a building. Brand decisions in an M&A deal are rarely matters of taste. If a firm cannot connect creative choices to strategy, decisions will default to hierarchy, and the most senior voice will win.
4. What if a key decision changed midway through the process?
Don’t ask this in the abstract. Every deal has shifts in the first 18 months, big or small. Choose a partner that has a framework but also the flexibility to navigate. During the presentation, introduce a real scenario and see how they react: the board rules out a new name; the CEO wants to retain the acquired brand in one market, or Day One moves forward by two months.
You are testing for two unhelpful responses at once.
The first is the firm that keeps defending its original recommendation. The second, more common and more damaging, is the firm that agrees immediately without asking what the change affects.
What you want sits between the two. A good partner starts with questions: what changed, why, and what it means for the recommendation. It can explain what it would keep, what it would change, and the impact on outcomes, not just fees.
The transaction gets you the assets. It does not get you a business that customers, employees and investors understand, or the growth the deal was justified on.
The firm you choose will be in the room when questions that shape the next five years get answered, usually faster than anyone would like and with less information than anyone would want.
Choose the M&A partner that will still be useful when the plan changes, because it will.
Using AI to Create a More Human and Hospitable Service Experience
As consumer expectations rise in the age of AI, brands must rethink service models to combine human connection, emotional intelligence, and intelligent automation in ways that feel more personal and authentic.
The Question Is How, Not If
AI adoption among brands and consumers is skyrocketing, resetting customer experience expectations around ease, immediacy, and highly personalized interactions. In most categories, incorporating AI into the customer experience is no longer a luxury, it’s essential for sustained relevance, differentiation and survival.
According to our research, while adoption is on the rise, consumer sentiment toward AI is going down. Many consumers are increasingly anxious and fear a life processed through an algorithm vs. truly lived. They want greater trust, more meaningful human connection, and added value from experiences that thoughtfully pair emotionally intelligent AI with real human interactions.
This insight has considerable implications for the future service strategy and delivery of brands, especially those focused on hospitality and front-line service. It raises the questions about:
The role of AI alongside human employees in a modern service model that builds emotional resonance, trust, and connection.
How to ensure a brand’s ethos and differentiators are amplified rather than swept aside in an AI-enabled service model.
How the service model should be designed for agents playing an increasingly prominent role in the customer service journey.
How front-line human employees can take on more meaningful and fulfilling roles through the empowerment of AI.
For brands, the question isn’t whether to deploy AI into the front-line service experience — it’s how (and where and for whom) to ensure human connection, emotional resonance and trust, along with signature brand differentiation.
Meeting Consumer Expectations for an AI-Enabled Experience
Leading with the consumer and their expectations is the starting point for brands looking to enhance or reimagine their hospitality and service experience for the age of AI.
What we’ve observed through our multi-year research on consumer behavior and sentiment around agentic AI is that consumer expectations have moved beyond the questions many brands are still debating. For consumers, it’s not a question about whether a task should be handled by a human or AI. What matters is the value delivered and quality of the experience created — with AI often making an experience feel more human by maintaining and relating to consumers’ deep and personal context.
Three expectations frame what consumers want from service and hospitality brands in the age of agentic AI: Emotionally intelligent, anticipatory, and ambient.
Emotionally intelligent: Consumers value service experiences that don’t just get it right, they demonstrate an empathetic understanding of their unique needs and circumstances. While this has always been intuitively true, AI, now makes emotional intelligence a competitive battleground. Brands can now demonstrate emotional intelligence at an unprecedented scale with agentic AI’s ability to hold persistent memory and process millions of contextual data points.
Anticipatory: Consumers want brands to anticipate their needs and address them proactively before they become issues. AI and machine learning’s predictive capabilities have enabled anticipatory interaction to reach new possibilities. Despite this, many brands are still focusing primarily on GenAI enabled chat to enhance the experience.
Ambient: Consumers value service that does the hard work in the background, creating a seamless experience. This paradigm of ambient service has been long established particularly in the luxury hospitality space. But AI is making ambient service more accessible and less costly through agentic interactions held by frontline staff or sometimes by consumers themselves.
Brands that successfully augment frontline and hospitality experiences with AI and human interactions design around these three expectations, so the results feel trustworthy, authentic, and engaging as an extension of their brand. These brands aren’t choosing between AI and human – they are thoughtfully intertwining them where it matters, reimagining key elements of the customer journey and employee’s workflows. Let’s unpack that more with some examples.
Consumer Expectations for AI-Enabled Service
Consumer Expectation
What Consumers Want
Emotionally intelligent
67% of consumers want AI that can guide them based on a deep understanding of their preferences and values — beyond just feature specs or price.
Anticipatory
66% of consumers want AI that can read between the lines and meet consumers’ unspoken needs — not just what they explicitly ask for.
Ambient
62% of consumers want AI that quietly notices conditions and context in their environment and takes action.
AI-Enabled Service Pioneers
We initially set out to identify best-in-class pioneers augmenting the front-line with AI while balancing human resonance with connectivity. What our research revealed instead was a landscape still largely in flux: companies are excelling at certain parts of the customer service journey, but a true end-to-end story has yet to fully emerge.
By looking at these examples of companies advancing key parts of the journey, we can identify patterns and best practices that bring us closer to achieving a model for truly empathetic, AI-enabled frontline services.
Verizon Wireless
In the AI age, consumers expect customer service to deliver better outcomes with lower wait times. In response, Verizon partnered with Google Cloud to bring generative AI, including Vertex AI, Gemini models, and the Customer Engagement Suite, into its frontline service operations. The goal wasn’t to automate employees out of the equation, but to hand them a smarter toolkit for higher-quality customer care.
Verizon’s Gemini-powered agents, including the “Personal Research Assistant,” predict customer needs and generate tailored solutions that customer service staff can use in live interactions. A separate “Problem Solver” agent gives frontline workers personalized, step-by-step troubleshooting guidance, eliminating manual searches, and helping associates find the right answer quickly.
Deployed across 28,000 representatives, the initiative achieved 95% comprehensive answerability for customer inquiries and a 40% increase in sales. Most importantly, Verizon was able to augment their human employees to strengthen customer relationships rather than replace them.
Marriott International
As the hospitality industry shifts from digital-first to AI-native models, Marriott International has emerged as a trailblazer by redefining service for the “agent economy,” where what LLMs answer matters as much as what humans search. Marriott is pioneering a dual-customer architecture that treats agents — including personal GPTs, corporate travel bots, and voice assistants — as a distinct and vital customer segment.
To support this shift, Marriott has made its inventory and real-time amenities machine-readable, allowing agents to negotiate complex guest preferences, such as allergies or specific gym equipment, and find – then book – the right stay. This strategic focus on the “Agent Customer” offloads the mechanical friction of search, negotiation, and transaction to seamless AI-to-AI communication, which clears the path for deeper human connection. The guest gets an invisible layer of anticipatory service that provides high-quality recommendations without the current administrative burden of travel planning — leaving more room for the “Spirit to Serve” that defines Marriott’s brand.
In addition, by making information more machine-readable, Marriott creates loyalty with AI agents early. This sets up its brand and loyalty programs to be at the forefront of how modern users search and navigate the internet. In an era where efficiency often clashes with empathy, Marriott shows that becoming agent-optimized can make a company more human-centric.
The Home Depot
As The Home Depot continues to drive growth by offering not just products, but expert project guidance customers can’t get elsewhere, GenAI is playing a critical role in how the company scales that experience.
For decades, customers have gone to The Home Depot for high-quality, hands-on advice from their iconic, orange-aproned associates. But in a world where consumers often start and end their journey interfacing with LLMs, the retailer has had to quickly develop a suite of GenAI tools and experiences for DIYers and pros that match the care and expertise that is synonymous with brand.
Two of these solutions, Magic Apron and Outdoor Assistant, help users find answers and expertise they need instantly, 24/7. Customers can ask anything, from “What aisle can I find this pressure washer in?” to “How can I build a shaded area for my back patio, and what houseplants thrive in the shade?” and receive responses that are not only correct but aligned with The Home Depot’s tone of voice and customer experience guidelines.
Rather than offering the generic chatbot responses consumers have come to expect, The Home Depot delivers an AI experience rooted in thoughtful expertise and design to give customers the confidence that even the most complex projects are achievable.
Creating A World-Class AI-Enabled Service Experience
To help brands build a more modern AI-enabled service experience, we apply Prophet’s Human Centered Experience Model in the following ways:
We start withAmbition — The Why. “What service experience vision, strategy, and principles will create the most value for your key audiences, leveraging both human and AI pathways?” This becomes the North Star, ensuring every touchpoint decision ladders up to a coherent purpose and aligns with the brand’s promise. Without ambition, you have activity without direction.
We then use the outer layer of the Human Centered Experience Model as the diagnostic backbone to assess and reimagine critical touchpoints in the end-to-end service journey, from discovery through long-term loyalty cultivation. Specifically, we address:
Audiences — Who? Who do we need and want to serve? In any critical point within the service experience, there is the customer, who may be human, machine or human with machine, but also the employee, or other stakeholders, each with specific needs and circumstances to be addressed.
Contexts — Where? What channels, products, services, and environments will we meet them with relevant, desirable experiences? Contexts have exploded in complexity — spanning mobile apps, voice assistants, wearables, and conversational AI interfaces – many of which sit outside a brand’s direct control. Without context awareness, experiences become inconsistent across touchpoints.
Expression — How? How might intuitive language, symbols, cues, gestures, and rituals bring our ambition to life? Expression is where strategy becomes tangible — through the words you use, the visual language, the micro-interactions that create emotional resonance, and needs to ensure survival through AI translation and summarization. Without coherent expression, experiences feel generic or, worse, inauthentic.
This foundational work provides the blueprint for more detailed concepting, followed by pilots and testing of these new AI-enabled service experience moments – helping brands achieve speed to impact, and create meaningful distance out ahead of competitors facing the same opportunity.
Discover how Prophet can help you create a more modern, human-centric and emotionally resonant service and hospitality experience.
Catalyst: AI Adoption Reshapes Traditional Apprenticeship and Expert Learning Models
AI is reshaping how organizations develop expertise, build judgment, and define what talent capabilities matter in the future
Evaluating AI Through a Human-Centered Lens
As part of Prophet’s 2026 Catalysts research, we’re exploring how organizations are progressing on their AI journeys through our Human-Centered Transformation Model. Rather than looking at AI adoption through a technology lens alone, the framework examines how strategy (DNA), capabilities (Mind), operating models (Body), and behavior (Soul) must evolve together to enable lasting transformation. This is our third article in a five-part series that explores what each lever means before we launch our 2026 Catalyst report. Read the Catalyst series:
Here we focus specifically on our findings under ‘Mind’. Much of the conversation around AI capability has focused on technical skills – prompt writing, tool proficiency, and AI fluency. But our research suggests that organizations are confronting a deeper challenge. As AI takes on more analytical and executional work, organizations are being forced to rethink how expertise is developed, how professional judgement is built, and how employees learn throughout their careers.
Leaders are increasingly asking a different question: what capabilities will matter when AI can perform many of the tasks that traditionally developed expertise?
What we’re seeing from the new research:
AI fluency is becoming the new baseline.
The question is no longer whether employees should learn AI. In many organizations, AI fluency is rapidly becoming a foundational workplace skill rather than a specialist competency. Organizations expect employees at every level to understand where AI fits into their work, how to use it responsibly, and when to rely on human judgement. As AI becomes embedded in daily workflows, AI literacy is shifting from a competitive advantage to a requirement.
“L&D is spearheading AI journey for employees, how they use it, how they can be fluent, understand it, and use it responsibly.”
HR Leader, Software Development
AI expertise is moving beyond prompting to managing agents.
Many organizations have invested heavily in prompt engineering and AI training, but leaders increasingly recognize that prompting is only the beginning. As AI agents become capable of executing increasingly complex workflows, employees will need to move beyond generating outputs to supervising, orchestrating, and evaluating them.
[…on the use of AI beyond prompting] “we’ve been seeing advanced AI tools in the talent attraction space today, for example Eightfold AI provides an agent that calls applications and sifts through applications at any time of the day.”
HR Leader, B2B Marketing & Sales
AI is reinventing the traditional apprenticeship model.
One of the biggest questions emerging from our research is not whether AI replaces early-career work, but how it changes the way expertise is built. AI has the potential to accelerate learning by reducing time spent on repetitive tasks and giving junior employees earlier exposure to higher-value thinking, problem-solving, and insight generation. But this won’t happen by default. Without intentionally redesigning capability-building pathways, organizations risk creating a generation that reaches answers faster without developing the critical thinking and professional judgement that traditionally came through experience. The opportunity isn’t to preserve the old apprenticeship model, it’s to build a better one.
“Apprenticeship has traditionally been with people, now you also have to apprentice the model you’re working with.”
HR Leader, Pharmaceuticals
What’s next for business leaders?
1. Move beyond AI literacy to AI judgement
Last year’s Catalyst research focused on building AI literacy across the workforce. That remains essential, but the next wave of AI adoption is shifting from just fluency to judgement. Organizations now need to focus on helping employees develop the judgement to evaluate outputs, identify appropriate use cases, challenge recommendations, and understand where AI should and should not be applied.
2. Reinvent the apprenticeship model
AI is changing how expertise is built in the workplace. As routine work is being automated, organizations can no longer rely on traditional ‘learn by doing’ alone to develop professional judgement. Leaders need to deliberately redesign early-career development, creating structured opportunities for coaching, simulation, shadowing, and guided problem-solving to develop the skills that AI cannot develop for them.
3. Make learning part of the job
Last year’s research emphasized AI training and capability-building. This year, we’re seeing that one-off courses won’t keep pace with the technology. Organizations should embed learning into everyday work by creating regular opportunities for experimentation and knowledge sharing (i.e. showcasing how teams are using AI, running innovation challenges, carving out time to test new use cases).
AI is increasingly exposing the limitations of operating models designed for a different era. The question is no longer whether organizations can deploy AI, but whether their structures, processes, and ways of working are built to support it. Those that redesign the organization alongside the technology will be best positioned to leverage the value of AI.
This is the fourth article in our Catalysts 2026 series. Continue the series as we explore the cultural and human implications of AI adoption, and stay tuned for the full Catalysts report later this year.
Brand relevance now requires more than consumer attention—it depends on Brand Energy.
For decades, brand building followed a predictable, linear playbook. Brands bought attention through paid media, controlled the narrative through ‘big moment’ campaigns, and moved consumers down a well-defined funnel. It was a stable, human-managed system where the loudest voice often won, enabling brands to directly and consistently drive relevance.
But that system is changing–people are engaging with brands and content more rapidly, across more devices, and more channels. This is leading to higher levels of discernment (and in many cases, skepticism), all of which is being dramatically accelerated by AI performance, adoption, and exchange.
Today, brand building happens within a mosaic of algorithmic feeds, micro-cultures, and AI-mediated discovery. Attention is no longer buyable in bulk; it must be earned in seconds and maintained through big and small interactions and experiences. In this new reality, the competition isn’t just other brands—it’s everything competing for consumers’ attention.
At Prophet, our research has historically shown that relevant brands significantly outperform the S&P 500 revenue growth, over the short-term and long-term. Today, achieving that relevance is harder than ever. To win, brands must now move beyond static positioning and generate what we call Brand Energy.
What is Brand Energy?
Brand Energy allows businesses to thrive in both human-driven and AI-mediated contexts. It is the combination of two distinct forces: energy that emits, which broadcasts an unmistakable point of view and shows up in culturally relevant places, creating spaces that showcase your brand and what you offer while giving people language to express who they are. And energy that attracts, which draws in communities that share your values and sparks curiosity about what comes next, making people want to be part of your world while providing a space and platform for individuals and groups to champion your brand.
Brand Energy is a substantial competitive advantage, but it needs to be created and managed with care; it’s not about being the loudest or splashiest, it’s about creating and sustaining energy that is:
Compelling: Reflecting a sharp POV that cuts through and resonates with its audience
Consistent: Delivering reinforcing signals, across touch points, that compound recognition
Coherent: Maintaining connection and alignment between story, product, experience, and culture
When brands deliver this energy, the benefits are significant and enduring. Brands build predisposition with consumers and customers, creating an advantage for future purchase decisions. This means greater:
Pricing Power: commanding a premium even (and especially) when functional benefits are comparable
Staying Power: maintaining market presence and relevance as culture evolves
Pulling Power: continuously attracting, engaging and retaining consumers and creating real, lasting loyalty and advocacy
Stretching Power: earning the right and the permissibility to enter new categories, forge new partnerships and deliver new experiences
Simply put: creating and sustaining Brand Energy is a key driver of Uncommon Growth, across multiple critical growth levers.
In a hyper-competitive, increasingly AI-mediated world, the big questions are around HOW to do this. Winning now requires new ways of thinking, working, and acting.
The Seven Modern Mandates for Driving and Sustaining Brand Energy
To cut through the noise, marketing leaders must pivot from traditional management to a more dynamic approach. Here are the seven mandates defining the next generation of brand leadership:
1. Start With an Unapologetic POV
Appealing to everyone resonates with no one. Modern winners plant a clear flag—from Anthropic’s conviction that AI should be built around human-centered safety to Tracksmith’s belief in running as a serious amateur craft, not mass fitness culture. These focused points of view help consumers and agents quickly understand what the brand stands for, attracting true believers while screening out the rest. If people cannot easily see themselves in your perspective—or reject it—it is not sharp enough to be noticed.
2. Think Beyond Your Category
You are no longer competing within a siloed industry—you are competing for a ritual, a moment, a slice of attention with consumers. The New York Times stopped thinking of itself as just a newspaper and started competing for daily “habitual attention” through games, cooking, and audio, all laddering up to a shared idea of intellectual discovery and curiosity. Define your broad domain – one that extends far beyond your core product and service.
3. Animate Brand Behavior
In a fragmented ecosystem, a brand is built by a repeated pattern of animated behaviors, not one “big bang” campaign or effort. Each touchpoint should reinforce the same distinct character, whether it’s Nutter Butter extending its surreal “Nutterverse”, Letterboxd amplifying its cinephile character across its reporting to social content, or Jacquemus carrying Mediterranean fantasy across campaigns and experiences. Actions speak louder than ads, and LLMs especially look for proof in repeated behaviors.
4. Build in Public
Winning brands are now inviting their customers into the brand-building process—earning trust through transparency (and even vulnerability). Burger King is rebuilding a fading brand in plain sight by making the turnaround itself the marketing; having its president take unfiltered customer calls to reinvigorate the brand. Transparency is an ‘always-on’ expectation.
5. Cultivate Co-Creation
You don’t own your narrative; you curate it. In a world of online remixes, stitches, influencer reactions, and click-bait news headlines, brands no longer own their narrative like they did before. Brands like LEGO and Fujifilm understand this, curating participation rather than resisting it: LEGO turns fan ideas into commercial products, while Fujifilm gives photographers the ability to share film recipes and tutorials. The result? A brand that consistently reaches customers in their feeds with high-trust, organic content, building effortless brand equity that compounds over time.
6. Win Decisive Moments
The traditional customer journey has collapsed. Discovery, proof, and purchase now happen simultaneously. Rhode wins because it embeds dermatologist co-signs and “one-tap” checkout directly into the discovery feed. Trust and transactions must be seamless.
7. Expect to Flex
Brands must treat real-time data as a creative input and act accordingly, quickly. Whether it’s Taco Bellusing comments sections as creative briefs or Vaseline turning viral TikTok “hacks” into verified brand moments, the ability to pivot at the speed of culture is the ultimate competitive advantage.
In a fragmented digital landscape, building a relevant brand is more essential than ever. In a world of infinite choice and AI-filtered information, brand is the ultimate trust shortcut. The question for leaders is no longer “How much awareness can we buy?” but “How much brand energy can we create?”
Connect with our experts to make sure your brand is generating the kind of energy it takes to win.
Catalysts: Getting More Value out of AI Means Looking Beyond Tech
The organizations creating the most value from AI are not treating it as a standalone initiative but embedding it into the business strategy and prioritizing outcomes over activity.
Evaluating AI Through a Human-Centered Lens
As part of our 2026 Catalysts research, we’re exploring how organizations are progressing on their AI journeys through Prophet’s Human-Centered Transformation Model. Rather than looking at AI adoption through a technology lens alone, the framework examines how strategy (DNA), capabilities (Mind), operating models (Body), and behavior (Soul) must evolve together to enable lasting transformation.
Here we focus specifically on our findings under ‘DNA’.
As organizations move beyond the initial wave of AI experimentation, a common challenge is emerging: many are still starting with the solution before considering the business problem that needs to be addressed. Across our Catalysts 2026 research, leaders described organizations overwhelmed by new tools, use cases, and possibilities, yet struggling to connect AI investments back to strategic priorities and measurable business outcomes.
The organizations generating the greatest value from AI are taking a different approach. Rather than treating AI as a standalone initiative, they are embedding it within broader business, brand, customer, and growth strategies.
What we’re seeing from the new research:
AI Initiatives are Operating Alongside Strategy, Rather Than Within It
Many organizations have established dedicated AI programs, roadmaps, and innovation initiatives, but these efforts are not always clearly connected to broader business objectives. Leaders described AI as a parallel workstream rather than a capability embedded within the organization’s strategic agenda.
“Don’t know that we will have an AI strategy, but we will have an AI role that is helping the larger strategy.”
Business Leader, International Food Business
Organizations are Struggling to Connect AI Investments to Enterprise Value.
As AI opportunities multiply, leaders are finding it increasingly difficult to distinguish between experimentation that creates meaningful value and experimentation that simply creates noise.
“A nose for value…there are a lot of great ideas and capabilities being developed, but we are trying to understand how we actually extract value out of it.”
HR Leader, Pharmaceuticals
AI Adoption is More Effective When Embedded Into Existing Workflows.
Organizations seeing benefit from AI are focusing on solving business and operational issues to create impact while positioning AI as part of a larger story about growth, transformation, customer experience, or operational excellence. Rather than presenting AI as a set of standalone tools, they are helping employees understand how it supports the organization’s broader direction and embedding it into or reworking existing processes and workflows.
“Customer experience is the guiding principle for us so whatever we do should be about making the customer experience better.”
Business Leader, International Food Business
What’s Next for Business Leaders?
1. Don’t build an AI strategy. Build a business strategy powered by AI.
Our 2025 Catalysts research highlighted the importance of aligning AI with organizational purpose, values and strategic direction. That finding still holds true, but the urgency has changed. Organizations can no longer afford to treat AI as a parallel innovation agenda. The leaders pulling ahead are embedding AI into the core business strategy, ensuring every AI initiative is tied to the enterprise agenda before fragmented investments become harder to align.
2. Stop measuring AI activity. Start measuring enterprise value.
In 2025, we encouraged organizations to focus AI efforts on meaningful business outcomes rather than technology deployment alone. As AI adoption accelerates, that principle becomes even more critical. The next challenge is no longer generating AI ideas, it’s making disciplined choices about where AI creates differentiated value and having the confidence to stop investing where it doesn’t.
3. Make governance an accelerator, not a gatekeeper.
Governance can no longer focus solely on responsible AI and risk management. As organizations move beyond isolated pilots, governance must become the mechanism that aligns priorities, coordinates investment and enables scale. The organizations that move fastest won’t necessarily be those running the most experiments, they’ll be the ones most effectively organizing around them.
As the opportunities around AI continue to multiply, the real challenge is not identifying where it can be applied but deciding where it can create meaningful value. Organizations that treat AI as a business capability rather than a technology initiative are likely to be better positioned to turn experimentation into sustained impact.
This is the second article in our Catalysts 2026 series. Continue the series as we explore how AI is reshaping organizational capabilities, operating models, and culture, and stay tuned for the full Catalysts report later this year.
In a world that feels constantly in crisis mode, premium and luxury consumers are looking for far more than a destination. What matters most today is stability, mental relief and, paradoxically, a renewed desire for simplicity and freedom from complexity, a notion that long seemed outdated in the luxury segment.
Prophet’s 2026 Consumer Generation Study makes one thing clear: the luxury market remains a “rock in the surf”, in other words, a resilient segment in an otherwise volatile environment. While the broader market is stagnating, 39% of premium and luxury consumers plan to increase their spending in 2026. Yet brands hoping to capture this affluent audience must recognize a fundamental shift: the definition of luxury has changed.
A New Definition of Premium Travel
In our recent study, Why Reassurance Matters More Than Status in Today’s Premium and Luxury Market, we explore how brand dependability has become a luxury in its own right during uncertain times. The latest data reinforces that trend and reveals just how profoundly perceptions of premium and luxury continue to evolve.
Today, reassurance extends beyond physical safety. It encompasses emotional well-being, reliable climate conditions, and the right balance of human interaction, offering consumers an alternative to feeling overwhelmed by anonymous technology or AI. This change is reflected in six key findings:
1. Premium and luxury consumers defy market volatility
Despite economic uncertainty, spending intentions remain remarkably resilient. Premium and luxury consumers continue to demonstrate strong willingness to spend, making this one of the most stable customer segments in 2026.
2. Mental wellness is now a core travel motivation
Travel is increasingly viewed as a pathway to emotional balance and recovery. While 56% of consumers seek physical rejuvenation, nearly as many (55%) are looking for inner balance, personal meaning, and mental restoration.
3. “Coolcations” go mainstream
Climate change is reshaping travel behavior in tangible ways. In 2026, 39% of luxury travelers deliberately choose cooler destinations or travel periods to avoid extreme heat. Among Millennials, that figure rises to 44%.
4. Luxury cruises continue to gain momentum
With 36% untapped demand potential, luxury cruises remain a significant growth opportunity, particularly among travelers over 40.
5. The package holiday is making a comeback
Especially among younger consumers, simplicity and predictability are becoming increasingly valuable. As a result, the traditional package holiday is experiencing a revival.
6. Tech & touch becomes the new standard
Affluent travelers readily embrace AI-enabled tools and digital services, yet personal interaction remains a critical source of trust and reassurance. The future belongs to brands that successfully combine technological convenience with meaningful human connection.
At the same time, sustainability remains important, but it is no longer the primary decision-making factor it once was. Since 2020, the share of premium and luxury consumers willing to pay a premium for sustainable travel options has fallen from 51% to 39%. Even more striking is the decline in consumers willing to modify their own travel behavior for sustainability reasons—from 45% to 30%.
From Insight to Action: What This Means for Travel Brands
These findings point to some clear opportunities for travel and hospitality brands. To stay relevant and competitive in 2026, companies should focus on six key priorities:
1. Understand the unique dynamics of premium and luxury consumers
In a challenging economic environment, premium and luxury consumers remain among the most resilient customer groups, with a sustained willingness to spend. Successfully engaging this audience requires a sophisticated understanding of how premium and luxury truly work—from brand storytelling and the luxury codes that signal quality, exclusivity and desirability to the many distinct expressions of luxury across generations and consumer segments.
2. Meet the growing need for mental wellness
Wellness is no longer a spa offering—it is a core demand driver. Companies must develop experiences that help travelers recharge emotionally and mentally, whether through retreats, mindfulness programs or digital detox experiences.
3. Innovate around the “Coolcation” trend
While sustainability may be losing some of its pulling power, climate concerns are influencing traveler choices in new ways. Brands should create and actively market compelling experiences in cooler regions and destinations.
4. Bring the package holiday back—differently
When everyday life feels increasingly demanding, travel should feel effortless. The package holiday needs to be reinvented as a premium convenience product—one that satisfies the growing desire for stress-free experiences and reduced complexity.
5. The luxury cruise market has untapped potential
For operators, this is a call to action to find ever newer and smarter ways to unlock that potential. And for those who are not yet active in this market, it may be a signal to reconsider that decision, possibly with an innovative offering aimed at the under-45 target audience.
6. Build hybrid models: tech & touch
The industry must find a new balance between convenience and trust. AI-powered tools drive efficiency, particularly among younger audiences where adoption rates reach 34% among Gen Z. At the same time, personal service remains highly valued by older travelers. Around half of Baby Boomers place greater importance on human interaction than Gen Z consumers do. Across generations, human connection continues to provide trust, guidance and reassurance.
Final Thoughts
The luxury travel market of 2026 is not defined by extravagance. It is defined by resilience. The brands that win will not be those that offer more complexity or more status signaling. They will be the ones that reduce friction, provide genuine emotional reassurance and help consumers navigate an increasingly uncertain world with confidence.
Catalysts: AI’s Next Challenge Isn’t Adoption, It’s Leadership
Beyond AI experimentation, the organizations pulling ahead won’t simply have the best technology, but the leaders who can navigate uncertainty and align teams across the enterprise.
For the past two years, organizations have been racing to adopt AI. Teams have experimented with pilots, automated workflows, tested use cases, and launched innovation initiatives at unprecedented speed. But in many companies, these initiatives are disconnected and AI adoption has outpaced governance, operating models, and even clear strategic direction.
As part of the seventh edition of Prophet’s Catalysts research, we’re exploring whether AI’s next challenge is no longer adoption, but leadership. Through our qualitative research, several early hypotheses are beginning to emerge that we’ll continue to test through our upcoming quantitative research.
As the initial wave of experimentation matures, a new reality is emerging: AI isn’t just changing how organisations operate; it’s changing the nature of work itself. To make the most of this opportunity, organisations must be structured, aligned, and upskilled enough to harness it.
In last year’s Catalysts research, we explored the importance of building the human infrastructure around AI, emphasizing that transformation could not simply be technical, but needed to be cultural as well. That idea still holds true. But the conversation has evolved. In other words, the challenge is no longer just adapting to AI. It is fundamentally shifting how we organize and structure our work based on a new AI-enabled paradigm.
Organizations are now moving beyond questions of readiness and adaptability toward something more fundamental: how strategy, talent, culture, governance, and operations work together as an interconnected system, and how to redesign work, not just layer AI onto outdated processes.
This demands intentional focus from leadership and points to a broader shift: competitive advantage may increasingly come from an organization’s ability to continuously adapt, rather than simply adopt. We’ll be exploring how organisations can do this across the next four blog posts.
What we’re seeing from the new research:
1. AI Leadership is becoming change leadership
To succeed in the age of AI, leaders can no longer rely on certainty, fixed answers, or static transformation maps. As AI evolves rapidly, organizations need leaders who can guide through ambiguity, align teams around moving targets, and create momentum without having complete clarity.
“You have to take into consideration all the human change management aspects.”
Business Leader, International Food Business
2. Leaders need to set the vision
The most effective leaders are starting from the business need, not the tool, asking how AI accelerates what the organization is already trying to achieve and seizing the opportunity to innovate on the systems and processes that currently exist.
“We had to create a visual of all the agents we had in existence to prevent people from building the same solution several times in different parts of the business.”
AI leader, Global Industrial Conglomerate
3. Leaders need to communicate openly
For employees to be engaged and excited around AI, leaders must build trust around it and communicate openly, about what AI can help the organization do, what it means for how people work and their jobs, and what they themselves are still learning or don’t yet know.
“We’ve had to get everyone over the AI anxiety hump because everyone was talking about AI coming to take their jobs, but what does that really mean and what skillsets and mindsets do we need to develop to keep pace with this change?”
HR Leader, B2B Marketing & Sales
What’s next for business leaders?
1. Get organized around AI, not just excited about it
In last year’s Catalysts research, we emphasized the importance of building workforce readiness and fostering human-centered AI adoption. This year, we’re seeing organizations move beyond awareness and experimentation into a new challenge: organizational coordination.
The companies pulling ahead are not necessarily the ones with the most AI tools; they are the ones creating alignment across strategy, governance, operations, talent, and leadership. The challenge is no longer simply adopting AI; it’s organizing the enterprise around it.
2. Develop leaders who can operate through uncertainty
Our 2025 research highlighted the need for leaders to build trust and create human-centered transformation environments. This year, we’re seeing leadership expectations evolve even further. Organizations increasingly need leaders who can navigate “known unknowns” without pretending to have fixed answers. Leaders that are embedding experimentation, iteration, and learning directly into how work happens, rather than treating transformation as a separate initiative running alongside the business.
3. Normalize experimentation and course correction
Organizations know they need experimentation, but many are still operating with cultures and systems optimized for predictability and risk reduction.
In our last research, we emphasized experimentation as an innovation muscle. This year, it is increasingly becoming an operational requirement. Organizations need to create environments where teams can test, learn, adapt, and share insights quickly, while still operating within clear strategic guardrails. The strongest organizations are not eliminating uncertainty. They are building the institutional stamina to move through it faster.
The imperative leaders are facing is no longer simply adopting AI. It is learning how to lead through a period of continuous change, where strategy, talent, governance, culture, and operations must evolve together. Our early research suggests that competitive advantage may increasingly come from leaders’ ability to adopt, align, and learn at a similar pace to the technological change itself.
This is the first article in our Catalysts 2026 series. Continue reading as we explore how organizations are rethinking strategy, talent, operating models, and culture to create sustained value through AI, and stay tuned for the full report later this year.
Four Conversations About the Future of Growth at Cannes Lions
What everyone was talking about at Cannes Lions this year.
Walking into Cannes Lions this year, I expected every conversation to revolve around AI. In one sense, it did.
Whether I was listening to Tiffany Rolfe and Nick Pringle at R/GA, Carla Hassan at JPMorgan Chase, Patrick O’Keefe at e.l.f. Beauty, Mark Kirkham at PepsiCo, leaders from McLaren Racing, Mars, SharkNinja, or the CMO Accelerator, AI found its way into nearly every session. But by the end of the week, I realized the technology itself wasn’t the most interesting part of the conversation.
What stood out was how consistently leaders from completely different industries were asking the same question: How do brands create growth in a world where AI is changing not only how organizations work, but how consumers discover, evaluate and engage with brands?
That shift felt remarkably consistent with what we’re seeing in our own work at Prophet and our clients. As AI becomes embedded in both enterprise operations and everyday consumer behavior, competitive advantage isn’t just about adopting new technology. It’s about rethinking how brands earn relevance, build trust and create value in an AI-powered world.
Across four days, four themes kept surfacing.
1. Judgment is becoming a competitive advantage.
One of the biggest surprises wasn’t how enthusiastic marketers were about AI. It was how disciplined they were about its limitations. At R/GA, Tiffany Rolfe and Nick Pringle challenged the industry’s fixation on outputs. As AI makes execution faster and more accessible, they argued that judgment, taste and strategic thinking become even more valuable. One line that stayed with me was their challenge to move from “making things” to “making things that make things.”
That same tension surfaced during the CMO Accelerator, where one participant observed that AI allows good marketers to produce mediocre work much faster. The challenge isn’t creating more. It’s maintaining the standards, curiosity and conviction to create work that is genuinely distinctive.
The conversation has clearly evolved. The question is no longer whether AI can generate content. It’s how organizations use AI to make better decisions, uncover better opportunities and create better work.
2. Relevance is replacing reach.
If there was one word I heard repeatedly throughout the week, it was relevance. Mars captured it perfectly: “You cannot buy relevance. You have to earn relevance.” The same idea surfaced in very different ways across the festival. Mark Kirkham, CMO of PepsiCo Beverages, argued that brands don’t create culture; they earn the right to participate in it. McLaren Racing shared how it has expanded Formula 1 beyond race day, creating opportunities for fans to engage through entertainment, fashion and partnerships. Even CeraVe’s activation around the NBA Finals succeeded because it felt native to a cultural moment people already cared about rather than interrupting it.
That feels especially relevant as consumers increasingly discover brands through AI-powered search, creator recommendations and algorithmic discovery. Visibility alone won’t create growth. Brands need to be relevant enough to be surfaced, trusted and ultimately chosen.
3. Creators are becoming strategic growth partners.
One of the biggest stories at Cannes wasn’t simply that creators were literally everywhere. It was that their role had fundamentally changed. Conversations with creators Josh Richards and Johnny Harris, Kevin Durant and Rich Kleiman of Boardroom, alongside announcements from platforms including YouTube, TikTok and Amazon, reflected a broader shift. Creators are no longer being viewed simply as media channels or campaign extensions. They’re increasingly becoming long-term partners in building communities, trust and brand ecosystems.
That has meaningful implications for CMOs. As the customer journey becomes more distributed, brands are no longer the sole authors of their story. Growth increasingly depends on designing systems where creators, employees, customers and communities actively participate in building the brand alongside the organization itself.
4. AI is accelerating the need for stronger foundations.
Perhaps the most unexpected conversations all week weren’t about technology at all. They were about organizational design. At Jim Stengel’s final CMO Accelerator, discussions focused less on AI tools than on talent, workflows, governance and operating models. One speaker made a point that echoed throughout the week: transformation doesn’t begin with technology. It begins with people, ways of working and how decisions get made.
That observation helped connect many of the conversations I’d heard throughout Cannes. AI isn’t replacing the fundamentals of growth. If anything, it’s reinforcing them. As more content is created by AI, agencies, creators and internal teams, the need for a clear brand strategy becomes even more important. As consumer journeys become more fragmented, understanding what your brand stands for becomes the anchor that keeps every touchpoint aligned. In many ways, AI isn’t creating entirely new challenges. It’s exposing the importance of solving long-standing ones.
Walking away from Cannes, I expected my biggest takeaway to be about AI. Instead, I left thinking about this new era of growth and creativity.
The conversations that stayed with me weren’t really about prompts, copilots or models. They were about judgment, relevance, creators, trust, and organizational transformation. Different industries, different speakers and different examples all pointed toward the same conclusion: AI is raising the bar for what great marketing and creativity looks like.
For Prophet, that reinforces something we’ve been exploring through our work with clients around uncommon growth. The opportunity isn’t simply to use AI to do today’s work more efficiently. It’s to rethink how brands create value for a consumer whose expectations, behaviors and decision-making are changing just as quickly as the technology itself.
That, more than any product announcement or keynote, felt like the defining conversation at Cannes Lions 2026.
How to grow in an ever-changing world? The Uncommon Growth Playbook for a New Era
There’s never been more risk to, or opportunity for growth than there is today. Today’s business leaders face a profound intersection of disruptive cultural, technological, political, and economic forces that can upend longstanding business models overnight. The traditional approach to growth and innovation that worked over the past 20 years has been upended as disruption is not just coming from new products, but new business models and cultural movements traveling at warp speed, entirely changing the rules of the game.
Our research confirms that this is not only possible amid this disruption but is already being proven. In our “Uncommon Growth in Uncommon Times” study, Prophet identified 179 S&P 500 companies that have delivered what we call Uncommon Growth. We characterize this as exceptional growth (averaging 2x their industry peers) that is sustainable (maintained over five or more years), and durable (persisting through disruption). These companies span industries, sizes, and stages. They aren’t outliers by luck. They’ve made deliberate choices that set them apart and build their growth strategy on a compelling story of value.
Through work with organizations around the world, we’ve defined five plays that enable leaders to attain Uncommon Growth. These five plays represent critical shifts in how leaders gather intelligence, frame their market, design their businesses, target customers, and build internal momentum. Together, they distinguish today’s uncommon growth leaders:
Shifting from a product and service only focus to orchestrated platforms and AI native offerings that create and capture value across every point of engagement
This is not a linear formula. It’s a new and essential toolkit that leaders can tailor to their business model, organizational maturity, and industry, and each is designed to drive speed to understanding and impact, using both analysis and embedded AI.
Throughout this playbook, you’ll find examples, measurable impact and actions to move from ambition to outcome. Uncommon growth is not a theory. It’s the disciplined execution of the right moves, at the right moment, for your unique organization.
Always-On Human Insights From Discrete Research to Agentic Intelligence
Today’s customers aren’t just changing faster—they’re living through a world that changes around them every day. New technologies, shifting expectations, cultural moments, and economic pressures continually reshape how people think, choose, and buy. For growth leaders, the challenge isn’t a lack of data. It’s developing a deep enough understanding of people to keep pace.
The opportunity for growth leaders is unprecedented—but realizing it requires rethinking how organizations build empathy with customers and translate that understanding into action.
The companies that win won’t simply collect more data. They’ll have greater organizational empathy—the ability for every product manager, marketer, strategist, and executive to more deeply understand the people they serve and create experiences that feel genuinely relevant.
To drive uncommon growth, leaders must build empathy with their customers and treat customer intelligence as a live utility — not a periodic input. This requires a fundamental shift from discrete research to market sensing and customer intelligence, executed through three core actions:
1. Go deeper to understand people more completely.
Organizations have access to richer sources of customer understanding than ever before—from first-party data to qualitative research and the broader economic, cultural, and social forces shaping people’s decisions. AI makes it possible to connect these signals into a more complete picture of customers, helping businesses move beyond knowing what people do to better understand why they do it—and anticipate what they may do next.
2. Expand insights across more people.
AI can extend trusted research methods across vastly larger populations and datasets, allowing organizations to validate ideas, uncover emerging trends, and identify opportunities with greater speed and confidence—without sacrificing rigor.
3. Put customer understanding into everyday decisions.
Insights create value only when they’re used. Instead of sitting in reports or dashboards, customer intelligence should be continuously available to the people making strategic, product, marketing, and commercial decisions. AI-powered insight agents can deliver relevant customer context at the moment decisions are made, enabling teams to act faster, with greater confidence and a stronger connection to customer needs.
Uber’s AI platform has 5K models in production, serving 10 million real-time predictions per second at peak. Uber leverages “always-on” insights and AI agents to optimize customer experience and service. The company’s first quarter of 2026 saw revenue grow by 14% to $13.2 billion with trips growing 20% year-over-year, suggesting that when insights are always-on and embedded in the product, the distance between a customer need and a business response drops to near zero.
The organizations that close the gap between insights collection and access—evolving their organizations to deploy AI as a powerful enabler of human insights —will be the ones that define the next era of consumer intelligence. Move beyond just asking what your consumers need — and start asking why they did it, what they might do next, and what you should do about it right now.
Future-Back InnovationStrategy From Category Growth to Future Markets
The biggest future growth opportunities are unlikely to sit squarely within your current category; they’re forming at the edges of it, shaped by forces most companies haven’t yet acted on. Taking share from competitors, extending product lines, entering adjacent geographies: these moves still matter. But they are increasingly insufficient to deliver uncommon growth.
The reason is structural.
CEOs spend approximately 36% of their time in reactive “firefighting” mode while devoting only 10% to 15% to long-term planning. This misalignment is exacerbated by market pressures, as 78% of financial executives admit they would reduce discretionary spending on R&D or maintenance to meet quarterly earnings targets, even if they knew it would destroy long-term value.
Consequently, the window for organizational survival is shrinking; the average lifespan of a company on the S&P 500 has dropped from 33 years in the 1960s to just 15 years today. The gap between short-term execution and long-term positioning is widening — and the companies pulling ahead are closing it deliberately.
The shift is from today’s category growth to future markets and entirely new frames of reference for the category you operate in: The imperative for future-forward growth leaders is to identify where disruption and emerging customer needs are opening entirely new markets and opportunities, and to capitalize on them with conviction. There are three critical components to understanding future markets and frames of reference that can also become an ongoing discipline within the organization:
1. Understand the drivers of change to identify future areas of demand.
Mapping the social, technological, economic, environmental, regulatory, and political forces reshaping your industry is critical, both to build an understanding of how it affects your category today and to explore emerging categories. Working deeply with subject matter experts enables growth leaders to understand the trends that define where demand is heading, not just where it sits today.
2. Define future markets and identify challenges.
An initial analysis into forces at play and demand opportunities enables growth leaders to frame future markets to dive into, mapping the competitive dynamics and customer needs.
3. Define your target destination.
Framing attractive potential markets for growth based on your business realities enables leaders to align on a target destination for sustainable business growth. With a clear picture of the business you need to become, organizations can then work backward — progressing potential business growth models through stage gates of desirability, viability, and feasibility.
Future-back innovation strategies and thinking create real friction with boards and teams focused on near-term results. But the value isn’t in the scenarios themselves — it’s in the concrete strategic bets they open to chart a sustainable and robust path to growth.
In fiscal 2018, gaming represented roughly 57% of NVIDIA’s revenue, with data centers accounting for under 20%.i NVIDIA bet early that its GPU architecture would power large-scale AI training — and committed to that destination years before the market reached critical mass. By fiscal 2026, data center revenue hit $193.7 billion — 90% of total revenue — and full-year revenue reached $215.9 billion. That transformation was the result of reading the forces of change early and building toward a future most competitors hadn’t yet recognized.
The question is not whether your category will be disrupted. It’s whether you’ll define what comes next — or arrive late to a future someone else built.
New Business Model Innovation From Products and Services to Platforms
Here’s a question most growth strategies don’t ask: what happens after the sale? For the majority of businesses, the answer is surprisingly little. The product ships, the service is delivered, and the customer relationship goes quiet until the next transaction. That silence is one of the largest untapped growth assets in business today — and the companies compounding value fastest have figured out how to fill it.
The pattern is consistent across industries: the highest-value businesses aren’t winning primarily on what they sell.
They’re winning on the depth of the relationship they maintain while customers are actively using what they’ve bought. That relationship generates proprietary data, deepens customer engagement, and creates switching costs that a lower-priced competitor simply can’t replicate. The shift is from products and services to platforms — business models that let you observe, interact with, and add value for customers during the time between one purchase and the next.
You don’t need to be a technology company. You need to create the conditions under which your business stays connected to customers during what we call the User Journey. Execution follows a four-stage progression:
1. Start with in-use visibility.
Build the ability to see what customers are actually doing with your product after the sale, which is the foundational data layer most traditional models completely lack.
2. Create interactive value.
Develop touchpoints, tools, or services that add real value during active use, deepening the customer relationship and generating behavioral signals you can learn from.
3. Personalize and grow.
Use what the platform reveals to tailor and expand the value delivered to each customer over time, which will drive increasing satisfaction and share of wallet.
4. Attract through proof.
Let the richness of the platform experience and data-validated results become a powerful acquisition tool to draw new customers through demonstrated value, not just marketing.
The biggest friction will be organizational: most businesses are structured around product sales cycles, not ongoing engagement. A platform model requires investment in data infrastructure and continuous value delivery before the financial return is fully visible.
Platform Business Model in Action: The New York Times
The New York Times evolved from a print newspaper into NYT, a multi-product digital platform — bundling news, cooking, games, audio, and sports into a single subscription. Digital-only subscription revenues grew by approximately 14% to $1.43 billion, with bundle and multi-product subscribers now representing approximately 51% of the digital base. The company didn’t grow by writing more articles — it grew by redesigning its relationship with readers across more of their daily lives.
The critical question isn’t “What new product can we launch?” It’s “How do we stay valuable to the customers we already have — and make that value visible to everyone we haven’t yet reached?”
Customer Ecosystem Management From Individual Customers to Coalitions
Most growth strategies focus on two things: acquiring more customers and keeping the ones you have. Both matter enormously. But they share a blind spot that limits how much value your business can create and capture.
The blind spot: your customers don’t exist in isolation.
Every customer is surrounded by an ecosystem of influencers, from providers to creators, advisors, and communities, who shape their decisions before, during, and after the purchase. The companies building the strongest competitive positions today aren’t just serving customers. They’re connecting the parties around them into coalitions where everyone exchanges value, and where the business sits at the center.
This is the shift from customers to customer coalitions: moving beyond a one-way value exchange between company and buyer and instead facilitating a “better together” network where participants make each other more valuable. The result: lower acquisition costs, higher lifetime value, and stickiness that a marginally better product from a competitor can’t easily break.
Executing this shift requires focusing on three areas:
1. Precision archetype scaling.
Growth in a coalition isn’t about scale for scale’s sake — it’s about the right mix of participant types: users, providers, creators, sponsors, and influencers. Identify which personas fill gaps in the ecosystem and create a self-sustaining growth loop. Are the right providers balanced to customer demand in a given market?
2. Multi-dimensional value exchange.
Look beyond the direct value your company delivers and design for the lateral value members provide to one another. When you engage the same person in multiple ways — a user who also reviews, recommends, and advocates — you drive significantly higher spend and create differentiation competitors can’t replicate.
3. Tiered ecosystem loyalty.
Move from transactional discounts to recognition systems that reward specific behaviors — quality, consistency, responsiveness — rather than just volume. This lets you capture premium needs at higher margins while remaining accessible at the entry level.
The friction here is real. Investing in peripheral ecosystem participants can feel indirect when teams are measured on near-term revenue. But the payoff is a self-reinforcing system that compounds over time.
Airbnb’s competitive advantage isn’t inventory — it’s the coalition. Guests rely on reviews, host interactions, and experience recommendations when deciding where to stay. Approximately 41% of U.S. hosts qualify as Superhosts, earning at least 29% more than standard hosts — a tiered recognition system that incentivizes quality, raises satisfaction, and drives the reviews that attract more guests. Beyond hosts, Airbnb builds a customer coalition by engaging creators and local communities to share authentic experiences, creating a network of advocates who drive trust and influence through their own voices and networks. That self-reinforcing loop helped Airbnb reach $12.2 billion in FY2025 revenue with 533 million nights and experiences booked — built not on a better product alone, but on a coalition that compounds value for every participant.
The question isn’t just “How do we serve our customers better?” It’s “Who are the parties around our customers that make the experience better — and how do we bring them together?”
Organizational Culture as Catalyst From Stated Values to Purpose-Built Culture
Every organization has written its values on a slide or poster. Very few have a culture that accelerates growth. The gap between what a company says it believes and how people inside it behave is where most growth strategies quietly die.
The evidence is consistent: research shows that approximately 70% of digital transformations fall short of their objectives.
The failure is rarely due to a flawed strategy or insufficient funding. Instead, it is most often rooted in organizational and cultural resistance — the antibodies within an organization that reject the very changes leaders are trying to implement. You can invest in the sharpest strategy and the most advanced tools, but if the culture isn’t built to absorb and act on them, the organization will default to what it already knows.
The shift is from stated values to purpose-built culture: a culture deliberately designed to champion bold bets, move with speed, and sustain momentum long after the initial energy of a new initiative fades. This isn’t about writing better values statements. It’s about rewiring how the organization operates.
Organizational Ambition
Defining a compelling ambition for the organization aligning purpose, strategy and culture — enabled by the right behaviors
Leadership Enablement
Clarifying what is expected of leaders, providing them with the skills and tools to demonstrate change and build trust with their teams
Employee Ignition
Sparking employee interest, passion, and accountability by showing them what great looks like
Executional Excellence
Unlocking people and work through systemic change in service of delivery against strategic objectives
Three moves make this real:
1. Decentralize growth ownership.
Uncommon growth cannot be a top-down mandate. Empower people at every level to identify and act on opportunities — and to challenge legacy processes that slow the organization down. When growth ownership is distributed, the company becomes a network of sensors rather than a hierarchy waiting for direction.
2. Operationalize experimentation.
Move beyond “permission to fail” toward active incentives to experiment. Reward the process of discovery, not just the outcome. If your performance reviews only recognize hitting quarterly targets on legacy products, the culture will never champion the new — no matter what the values slide says.
3. Build momentum loops.
Shift from annual planning to rolling cycles that redirect resources toward what’s working in real time. Leaders must move from managing performance to evangelizing the behaviors that produced it.
The tension is real: protecting the core business while funding the future creates friction. Culture must provide the permission to reconsider your own business when the evidence points forward — and the resilience to sustain speed without burning people out.
Organizational Culture as Competitive Advantage in Action: e.l.f. Beauty
e.l.f. marked its 29th consecutive quarter of net sales growth and market share gains, with net sales of $1.63 billion for fiscal year 2026, an increase of 25%. The company’s willingness to experiment with emerging platforms — it was one of the first beauty brands on TikTok and has since expanded to Roblox and Twitch — reflects a cultural DNA that rewards speed and experimentation over perfection. That consistency isn’t a single product hit — it’s a culture that moves at what e.l.f. calls “e.l.f. speed,” where purpose and performance reinforce each other daily.
You cannot program growth into a spreadsheet. You need a human-centered transformation model and a culture supportive of change, which can only come about through nurturing people — and cultivating the systems, skills, incentives, and norms that shape how they show up every day.
The journey to creating Uncommon Growth starts today.
Every growth move describes a shift that successful Uncommon Growth companies have already made — and that their competitors, in most cases, have not. The distance between those two groups is widening. Not because companies lack talent or capital, but because they’re still running plays designed for a world that no longer exists. None of these plays require you to rebuild your company from scratch, but each one requires you to challenge an assumption your organization has been operating on for years. The companies achieving uncommon growth aren’t waiting for perfect conditions. They’re building the capability to grow without them.
The playbook is here.The question is what you do next.
Prophet’s Uncommon Growth Playbook and practice areas are led by a multidisciplinary team of experienced growth leaders across strategy, insights, innovation, experience, and AI solutions—all with an eye on speed to impact.
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Authors
Mike Leiser Chief Transformation Officer, Senior Partner
Jay Milliken Global Lead of Growth Strategy, Senior Partner
How clear value stories can position health tech companies to earn greater trust and premium valuation.
Healthcare technology companies face a paradox: the market has never been more bullish on the sector — recent research showed that AI-enabled companies now capture 55% of all health tech funding and command a 19% premium on deal size — yet public health tech companies still trade at a meaningful discount to cloud peers, despite roughly 2x the revenue growth and free cash flow margin.
Strong businesses still lose value when the story is unclear: The gap isn’t just a business problem; it’s a narrative problem. Most health-tech companies have a brand platform in one deck, a product story in another, an investor narrative from the CFO’s team, and a sales pitch from field marketing. Individually, each is internally logical, but collectively incoherent and hard for teams to articulate. Too often, companies speak in higher-order benefits without ever making clear what they actually do, where they play, or why they should win an organization’s business.
We recently sat in a room where a health-tech company pitched its full suite of services. After they finished, our client simply asked at the vendor: “So what is it that you actually do?”
A Story of Value connects the story across audiences: What closes this gap for clients is a Story of Value: a coherent narrative spine that captures who the company is, the tension it resolves, how it creates value, and why that story justifies premium valuation. When the narrative is properly modulated for priority audience groups, it retains its core value while ensuring resonance for each audience.
Five Moves That Make a Value Story Credible
Health-tech companies that get this right will:
Define a clear frame of reference first. Before reaching for elevated positioning, companies need to answer a basic question: what do they actually do? Name the competitive set, the outcomes, and where they play. In our work with a major healthcare financial services company, the challenge was moving beyond its best-known role in facilitating payments transactions toward a broader frame: bridging gaps in the healthcare financial system, improving the financial experience of healthcare, and aligning the interests of payers, providers, and members. That shift created a stronger platform for growth.
Name where AI creates defensible economic value. Being AI-enabled may now be table stakes; it cannot be the whole story. The real question is where AI creates advantage that compounds over time and is difficult to copy. In our work with a major virtual care platform, we saw how quickly AI language can flatten into sameness: personalization, insights, integration. What created credibility was not broader AI rhetoric, but specificity — which data, improving which workflow, producing which measurable result.
Ensure the human touch is inextricably linked to AI. In healthcare, meticulous care around data is paramount, especially when it comes to AI use. In helping shape the story for that same virtual care platform, one important choice was to frame AI as an enabler of people, not a replacement for them, with clinician oversight built into the moments that matter most. The important move was not just having that governance mindset internally but making visible to the market where automation stops and expert judgment begins.
Thread a single narrative across every audience. Investors, buyers, clinicians, and patients should all recognize themselves in the same core story, with the emphasis adjusted for each audience. We saw this in our previously mentioned work for a healthcare financial services company: by anchoring the company in bridging gaps across the healthcare financial system, the story could resonate across payers, providers, and members without splintering into disconnected messages. One framework, many expressions.
Build a system of proof — and earn your claims over time. Sophisticated healthcare buyers are not rewarding ambition alone; they are asking for evidence. Large employers and health systems want proof before integrating new tools and systems, especially when AI claims are involved. In our work with a patient financial engagement platform, the strongest story was not AI for AI’s sake, but AI tied to operating outcomes: higher collections, lower cost-to-collect, faster cash flow, and fewer billing calls through intelligent support. That kind of results-backed proof makes innovation more credible because it connects technology directly to measurable value.
In the age of AI, the margin for narrative incoherence is zero. The companies that answer the market’s implicit question, “why this company?”, with one credible, evidence-grounded Story of Value will earn the multiples, the deals, and the trust, outpacing competitors without a clear articulation of what they do and why it matters.
Healthcare leaders are operating in an environment where innovation alone is not enough. To earn trust — and the premium that comes with it — companies need a narrative that is as disciplined as their strategy: clear in its frame of reference, specific in how value is created and grounded in evidence. The strongest stories do more than describe a business; they help the market understand why they should care.
Interested in pressure-testing your current story? Let’s discuss how a Story of Value can strengthen your organization’s positioning, market confidence and growth.
In Health Tech, AI Doesn’t Win Deals – Outcomes Do
In health tech, advantage comes from explaining the impact of advanced intelligence.
Every healthcare service and technology company now claims to be AI-powered. What once signaled innovation now reads as category shorthand. According to a recent McKinsey survey, 85 percent of healthcare leaders are now exploring or have adopted generative AI capabilities—making “AI-powered” closer to table stakes than a point of distinction. Meanwhile, buyer skepticism is rising in parallel: a national survey from Ohio State University and SSRS found that public openness to AI in care dropped from 52 percent to 42 percent in just two years. The presence of AI alone no longer earns attention. Buyers want to know what it actually does, where it matters, and why they should believe it will work in the environments in which they operate.
The market is saturated with undifferentiated AI claims. That shift has created a new messaging challenge. In many health-tech companies, AI is described at one of two unhelpful extremes: either as a broad aspiration that could apply to almost anyone, or as a technical capability that only product teams can decode. The result is a value gap. Companies may be making real investments in data, models, and intelligent workflows, but their market story still fails to answer the most important buyer question: why should this matter to me?
The Three Places Companies Tend to Tell Their AI Story
From our work across healthcare, data and technology businesses, we see a consistent pattern. AI messaging tends to land in three places, but only one of them creates real differentiation.
First, there is AI in the product: copilots, smart features, clinical suggestions, intelligent routing. These capabilities are increasingly expected, but rarely distinctive. Nearly every competitor either has them or claims to. Framed this way, AI becomes a feature label, not a market advantage.
Second, there is AI in the business: internal efficiency, lower cost-to-serve, faster processing, better staffing. This can be an important part of the investor story. But it is usually the wrong lead message for customers. Buyers care about whether those gains translate into better service, better economics, or better outcomes for them.
Third, there is AI as a driver of customer value. This is where differentiation begins. The message shifts from what the technology is to what it changes: which workflow improves, which decision gets smarter, which friction point is removed. In this mode, AI is not the headline. The headline is the benefit it generates.
The hardest claims to copy are not capability claims. They are claims rooted in proprietary data, embedded workflows, measurable results, and a trust model that holds up in practice.
A Simple Test for Whether Your Message is Working
We saw this clearly in a recent messaging engagement with a major virtual care platform. Like many companies in the category, it faced a familiar risk: its AI language sounded too broad to be credible and too similar to what others were already saying. Terms such as personalization, insights and integration were directionally right, but too generic to carry the story. What sharpened the narrative was greater specificity — which data made the system smarter, which moments in the care journey improved, how the technology helped care teams act sooner and engage the right people. Just as important, the company needed to show where clinician oversight remained essential and where governance was built into the system. In healthcare, trust is not supporting detail. It is part of the value proposition.
This points to a simple pressure test: if you remove the phrase “AI” from your message and it no longer says anything meaningful, you are describing the technology, not the advantage. If the story remains compelling without the term — because it communicates workflow impact, outcomes, proof, and trust — then the message is doing real strategic work.
In Healthcare, Credibility is the Differentiator
The companies standing out today follow the same discipline. They name the user and the workflow. They quantify the effect. They make clear why their data or delivery model gives them an edge. And they treat governance and responsible use as visible parts of the story, not footnotes for legal review. In healthcare, where the standard for credibility is structurally higher, vague AI rhetoric does more than blur differentiation. It can actively weaken trust.
In health tech, AI may be necessary, but it is no longer enough. The companies that stand out will not be the ones that talk about intelligence most loudly. They will be the ones who explain most clearly how intelligence creates better care experiences, stronger engagement, greater efficiency, and more credible outcomes.
If your organization is investing in AI but struggling to turn that into a story customers trust, it may be time to pressure-test the narrative. We work with healthcare services and technology companies to clarify where AI creates real value, how that value should be expressed across audiences, and what proof is needed to make the story credible in market. If that challenge feels familiar, let’s start a conversation.
AI Is Transforming Marketing in Healthcare–Is Your Team Ready?
How leading healthcare and technology brands are piloting AI to transform their marketing—and what it takes to do it right.
AI isn’t just another tool in the marketer’s toolkit. It’s fundamentally changing how brands understand audiences, create content, and drive growth. Across our recent working sessions with healthcare and health-tech organizations, one truth surfaced consistently: the brands that win with AI won’t be the ones that move fastest, but the ones that move most thoughtfully.
Today, most marketing leaders are already experimenting. Generative AI is in active use across content, analytics, and enablement, and investment is accelerating as CMOs see early ROI. But speed without strategy creates noise, not growth—especially in healthcare, where trust, accuracy, and consistency matter as much as efficiency.
The real shift isn’t just technological. It’s organizational. Marketers are evolving from storytellers to systems architects, responsible for building infrastructures that balance real-time responsiveness with long-term brand equity. AI can accelerate that evolution—but only if human judgment remains firmly in the loop.
The Shared Reality: What Healthcare Marketers Are Wrestling With
We hosted work sessions with four healthcare organizations’ marketing teams. Despite playing different roles in the healthcare ecosystem across organizations, a common set of tensions is emerging as AI moves from experimentation to scale.
Human insight versus machine output.
AI can generate content, insights, and recommendations at a speed no team can match. But machines optimize for patterns, not meaning. Ensuring that AI-generated outputs resonate emotionally, reflect lived patient experiences, and align with brand purpose remains a core challenge.
Brand consistency at speed.
As content volume explodes across channels, teams are struggling to maintain a consistent voice, tone, and visual identity—particularly in decentralized environments. The risk isn’t just inefficiency; it’s brand dilution that erodes trust over time.
Data security and privacy.
Healthcare marketers sit on highly sensitive data. Feeding proprietary or patient-related information into public models without guardrails introduces unacceptable risk. Governance, enterprise-grade tools, and thoughtful data design are prerequisites—not downstream fixes.
Internal resistance and uncertainty.
Fear is real: concerns about job displacement, confusion about where to start, and fatigue from too many tools slow adoption. Successful AI transformation depends as much on change management as it does on technology.
Why These Challenges Matter More Than Ever
Digging deeper, these tensions reveal structural issues that AI is exposing—and can help solve if addressed deliberately.
Being data-rich but insight-poor.
Many marketing teams have access to enormous volumes of data but lack intuitive ways to query, connect, and act on it. AI creates the possibility of natural-language interfaces and real-time insight generation—but only if data is clean, connected, and governed.
Scaling content without diluting credibility.
Healthcare brands are under pressure to publish more, faster, across more channels. The opportunity is scale; the risk is losing clinical rigor, thought leadership, or emotional authenticity. AI raises the floor—but only if brand standards are embedded into workflows.
Decentralization versus coherence.
Large systems often operate across hundreds—or thousands—of digital properties and contributors. AI can be a force for standardization, reuse, and quality control, but without shared frameworks, it simply accelerates fragmentation.
Knowing where to start.
Nearly every organization asks the same question: Which use cases actually matter? Leaders are increasingly prioritizing opportunities based on desirability, viability, and feasibility—then piloting quickly with small, focused teams before scaling.
The most forward-looking teams aren’t asking how AI can replace work. They’re asking how it can elevate it.
AI is not replacing the marketer. It’s redefining what great marketing looks like.
Think of AI as a multiplier. Strong strategy becomes faster. Strong creative becomes more personal. Weak foundations simply fail faster. The healthcare brands that invest now—in the right use cases, the right guardrails, and the right human–AI collaboration models—will be the ones setting the standard over the next three years.
The question isn’t whether AI belongs in your marketing strategy.
It’s whether your marketing strategy is ready for AI.
Ready to explore what human-centered AI can do for your marketing team? Connect with us to discuss a kickstart workshop to help your team identify the pilots that will be most valuable to helping you reach your brand and business goals.
