Nearly every leader has AI at the top of their agenda, with resources deployed to understand how to utilize it for efficiency gains. We’ve all heard the promises: AI has the potential to deliver massive business efficiencies from automating administrative tasks to managing customer service channels, to drafting copy for SEO, ads and product pages. But beyond efficiencies, AI can deepen customer engagement, surface strategic insights and shorten the time it takes to bring new products to market.  

We call this speed to impact — a critical component of achieving uncommon growth. Growth that is sustained and outsized versus category peers. 

In a world where AI has the potential to impact everything, leaders face the choice of where to invest to maximize value creation. As the adage goes, “we can do anything, but we can’t do everything.” Successful AI strategies require a sharpened strategic focus, with investments deployed toward growth use-cases. 

Prophet’s Uncommon Growth research shows that companies achieving growth share three core traits: Customer Obsession, Pervasive Innovation and Strong Cultures. Investing behind these pillars is key to achieving business success. Deploying AI across the pillars, done right, has the potential to supercharge growth.  

We explored how AI is accelerating impact across these three pillars in 179 companies that achieved uncommon growth. 

Customer Obsession 

Companies achieving uncommon growth are relentlessly focused on understanding and engaging their customers — often outspending peers in sales and marketing. GenAI has introduced new channels of engagement, from influencing how consumers research products to driving deeper personalization and connection.  

In Prophet’s study, The Rise of the AI-Powered Consumer, 45% of consumers reported using Gen AI in the past six months to inform purchase decisions. Highly considered purchases, like technology, automotive and beauty, are seeing the most disruption. To remain competitive means optimizing your brand, marketing and media strategy for LLM awareness and sentiment.  

The Harvard Business Review’s “Forget What You Know About Search: Optimize Your Brand for LLMs” suggests marketers should: 

• Highlight expertise
• Speak to use cases and consumer needs
• Tailor content to the processing style of dominant LLMs for their target audience 

3. Retailers and marketplaces are taking this one step further, collapsing the “choose-use journey” within GPTs. Etsy recently announced a partnership with OpenAI, enabling in-chat purchases, with Walmart just following suit. More will undoubtfully follow. 

AI allows brands to get even closer to their customers, driving engagement and winning with personalization, leading to increased purchase likelihood and CLTV.  

Example: Crocs 

Crocs has long proven that personalization fuels growth. The success of Jibbitz, the individual charms for crocs, has lifted average order values, driven repeat purchases and built deeper brand affinity. With 75% of customers purchasing Jibbitz and $271M in 2024 sales (18% of total revenue). With the launch of the ABLO AI co-design tool, Crocs is doubling down on personalization, enabling customers to design their own Jibbitz through AI-prompts and image uploads. AI prompt indicators point to greater personalization and conversion, showing how AI can deepen brand affinity and accelerate growth at scale. 

“We have Jibbitz for everyone — from teachers to gamers to healthcare workers — and we are now giving our fans the option to design one-of-a-kind charms using ABLO’s AI technology, taking customization to the next level.”

Crocs Brand President Anne Mehlman, Fast Company

Example: L’Oreal 

L’Oréal has long positioned itself as a beauty tech pioneer. Through acquisitions like ModiFace, L‘Oreal offers virtual try-ons and diagnostics that reduce hesitation in digital shopping. Its new venture Noli uses over one million skin data points to generate hyper-personalized product recommendations. Internally, its CreAItech content lab produces up to 50,000 images and 500 videos per month, allowing marketers to rapidly adapt creative assets across markets and cultures without sacrificing brand essence. AI is enabling L’Oreal to expand personalization and inclusivity at scale by strengthening emotional connection while accelerating growth.  

In January 2024, L’Oréal was the first-ever beauty company to deliver the keynote speech at the world’s most important tech event – the Consumer Electronics Show in Las Vegas. It was a highly visible stage to showcase our pioneering and leadership role in Beauty Tech and our next-generation innovations for more sustainable, personalized and inclusive beauty. These innovations included… Beauty Genius – a Gen AI-powered personal beauty assistant and HAPTA – the world’s first AI-powered makeup applicator for people with limited hand, wrist and arm mobility.

L’Oréal 2024 Annual Report

Pervasive Innovation 

Market leaders view innovation as an always-on, critical business muscle. They consistency over-invest in R&D, maintaining that discipline even in turbulent economic times. AI is accelerating the innovation process — from aggregating and synthesizing customer insights, identifying opportunities faster, to rapid concepting and prototyping and offering consumer validation through digital twins. With AI developing higher-quality innovation concepts, businesses can focus on critical routes to market activities, like securing the right distribution and getting through regulatory processes. 

Example: Moderna 

Legacy biopharma R&D is notoriously slow and capital intensive, but Moderna is proving that AI can reset the pace of innovation. Through its partnership with OpenAI, Moderna has deployed ChatGPT Enterprise across functions – from R&D to manufacturing — creating thousands of custom GPTs to trial handle trial data review, anomaly detection and documentation. These tools remove bottlenecks in data-heavy processes and allow scientists to focus on higher-order interpretation, resulting in a richer innovation pipeline. The result is compression of discovery-to-development cycles and Moderna plans to bring 15 new mRNA products to market in the next five years — from RSV vaccines to individualized cancer therapies. 

Culture as a Catalyst 

Culture is critical to achieving uncommon growth. Purpose-driven, intentionally designed cultures to enable enterprise-wide adoption of innovation, AI included. When AI adoption is fragmented across silos, momentum stalls. Prophet’s research, “Human-Centered AI: Culture as the Catalyst for AI-enabled Growth,” identified several imperatives for enterprise-scale AI adoption:

• A shared AI vision aligned company purpose, values and strategy 
• CEO and CHRO alignment on the AI vision 
• Clear expectations for AI fluency and the role of humans  
• Systems and training that enable AI adoption at scale  

Example: JPMorgan & Chase 

JPMorgan approaches AI adoption as both technological and cultural transformation. In under a year, it deployed its LLM Suite to more than 200,000 employees -embedding AI in daily workflows and building organizational fluency at scale. Tools like EEVEE and Smart Monitor (two of over 400 use cases at the firm) free teams from low-value manual work, redirecting energy toward higher-order problem-solving. The result is a workforce that sees AI not as a threat but as a partner: one that’s projected to fuel $1.5B in AI impact by 2030. JPMorgan’s bet is clear: AI will augment every role and drive growth — cultivating a culture where AI is trusted and widely used will compound in value, turning efficiency gains into a sustained competitive advantage. 

“We are setting very clear goals of success and KPIs for each one of these rollouts. We also have very good experimentation, so we can actually measure the incremental benefits by giving the tool to some agents and setting up test and control groups. We compare these results with clear metrics of success, and it helps us learn what’s working and what’s not working and what we need to do to drive adoption.”  

Katie Hainsey, Managing Director and Head of AI/ML and Data & Analytics for Digital, Marketing and Operations at JP Morgan

Example: Moderna 

Moderna recognized early that the barrier to AI adoption wasn’t just technology, but shared expectations of fluency. In 2021, it partnered with Carnegie Mellow to launch its AI Academy to drive AI fluency across the workforce, preparing employees long before generative AI went mainstream. That groundwork paid off when ChatGPT Enterprise rolled out in 2023: adoption was immediate, with nearly half of weekly active users creating their own GPTs and averaging over 100 interactions per week. By aligning purpose, values and training, Moderna turned potential resistance into active engagement, making AI a natural part of how work gets done.  

At Prophet, we’ve been exploring AI’s potential for some time—experimenting, building and learning across teams. But our biggest leap forward didn’t come from a new tool or top-down policy. It came from a collective shift in focus. 

Earlier this year, we hit pause across all 15 global offices to host our AI Learning Jam—a firmwide sprint designed to upskill, energize and unlock new ideas. We brought in outside experts, spotlighted internal pioneers already integrating AI into their work, and carved out time for hands-on experimentation. Teams tackled real client challenges using AI—and the momentum was immediate. 

Feedback from the event was among the strongest we’ve seen for a firmwide initiative. But more powerful than any metric was what it set in motion. 

We followed it with our first AI Demo Day, inviting submissions in three categories: 

• How we’re using AI to enhance current work 
• How we’re guiding clients on AI strategy 
• How we’re building AI products and solutions 

Twenty demos. Ten teams were selected to present to our executive leadership. The range of use cases was eye-opening—from custom GPTs that accelerate insights and storytelling, to AI-powered tools that generate consulting outputs, to strategic frameworks helping clients define their AI vision. We carefully considered the potential for each demo and recognized the top contributors. We are now scaling these solutions firmwide. 

One team reported a 90% time savings on market mapping tasks—freeing them to focus on strategic thinking and creativity. Another team doubled their content output using a custom GPT trained on a specific tone of voice. 

Our focus on AI solutions isn’t a one-off initiative. It’s a cultural shift—and we’re seeing it in the data. The number of custom GPTs built internally has grown exponentially. 

We’re also applying our own Human-Centered Transformation Model to this journey: 

• MIND — Enable: The AI Learning Jam built foundational knowledge and shared capabilities across the firm. 
• SOUL — Motivate: AI Demo Day showcased what’s possible and celebrated early wins. 
• BODY — Direct: We’ve embedded AI into competencies and workflows, launched a Center of Excellence and built infrastructure to support scale.