How AI is Transforming Business: Insights from Matt Britton's Nationwide Insurance Keynote
In October 2025, standing before 4,000 technology executives at Nationwide Insurance's Columbus, Ohio headquarters, consumer trends expert and CEO Matt Britton delivered a powerful message: the AI revolution isn't coming—it's already here. And those who don't adapt will be left behind.
Britton, who leads Suzy, a consumer research platform with over 300 employees, brought a unique perspective to the stage. Unlike many AI evangelists who discuss the technology theoretically, Britton demonstrated real-world applications he'd built himself—including creating a music video about Nationwide at 32,000 feet the night before his presentation.
"I made that video on the plane last night, flying in a tin cube," Britton told the audience. "Just think about that. How did I make a song with lyrics, a music video, and make the cool eagle in your logo fly off the screen? That's the world we're living in."
The Generational Shift: Understanding Gen Alpha
Britton's expertise lies in helping major brands understand emerging consumer behaviors. His career began in 2000, studying Millennials—the first generation to grow up with internet in their households. He moved on to Gen Z, the "iPhone generation" that grew up with the internet in their pockets and social media shaping their worldview.
Now, a new generation is emerging: Gen Alpha, ages 0-14, who will be known as the AI generation.
"They will never know a world where you cannot talk to technology like you talk to people," Britton explained. "It will not be foreign to them to have an intimate relationship with an AI chatbot—a concept that will freak out their parents. But for them, they don't know any other way."
This generational transformation carries massive economic implications. Britton highlighted the Great Wealth Transfer, where over $30 trillion will pass from Baby Boomers to Gen Z and Gen Alpha consumers. The spending behaviors will shift dramatically from a scarcity mindset to what Britton called a "YOLO" approach to capital.
The Personal AI Journey: Building a Health Bot
What sets Britton's presentation apart is his hands-on approach to AI adoption. Rather than immediately deploying AI across his 300-person company with 80 engineers, he decided to solve a personal problem first: staying alive as long as possible.
At 50 years old with four children (two young, two in college), Britton compiled two decades of personal health information—X-rays, MRIs, blood tests, doctor's notes from hard drives and file cabinets—and uploaded them into his own custom AI model. He trained it as if it were the leading doctor from Johns Hopkins University with one mission: keep Matt Britton alive.
His first prompt to the system: "If I'm going to die in five years, what's the most likely cause?"
Unlike searching WebMD (which "tells you we're all going to die"), this AI was trained specifically on his personal medical history. The results were eye-opening, pointing to markers in his blood from 12-15 years ago and their progression, along with actionable recommendations.
"It really changed the way I looked at my body, the way I looked at my health," Britton shared. "I started to make habits and decisions differently as a result."
This personal health bot now serves multiple purposes: answering questions about unusual symptoms, generating comprehensive dossiers for specialist appointments, and providing his allergist with complete yearly information before office visits.
The Four-Step Framework for AI Transformation
Britton's health bot journey revealed a universal framework for AI adoption that he encourages everyone to follow:
1. Identify a Problem
Start with something that matters to you personally or professionally. Britton chose mortality; others might choose financial management, diet and wellness, or work-related challenges.
2. Understand the Data
What information do you need to solve this problem? For Britton's health bot, it was his medical records. For a business application, it might be customer data, market research, or operational metrics.
3. Build Step by Step
Use AI tools like ChatGPT to create step-by-step instructions. "Tell it to not give you step two until step one is done," Britton advised. "If you have perseverance, you will be at step 37 and look back and say, 'Wow, I can't believe I actually created this.'"
4. Practice at Home First
Since most companies restrict uploading customer data to third-party AI tools (rightfully so), the best training ground is your personal life. Build health bots, financial management tools, or home automation systems using your own data without corporate restrictions.
Why This AI Revolution Is Different
Britton highlighted two factors that make AI's advancement unprecedented:
Ease of Use: Unlike previous technologies requiring specialized skills, AI only requires the ability to communicate. "If you can text your friend, you can use AI," Britton explained. His 75-year-old mother uses a custom home bot he created to manage her Netflix passwords and appliance manuals—no technical expertise required.
Rate of Change: The capabilities AI can accomplish double every seven months. "Today is the worst it's ever going to be," Britton emphasized. "If AI can do something okay today, given this rate of change, it's going to be able to do things in an incredible, almost unbelievable way before you know it."
He compared dismissing AI based on past performance to refusing to stream TV in 2025 because streaming was choppy in 2001.
The Global AI Race and Trust Gap
While most major AI companies—Nvidia, OpenAI, Google, Anthropic—are American, a concerning trust gap is emerging. China shows 72% citizen trust in AI, while only 32% of Americans trust the technology.
This matters because China is already implementing AI education for children as young as 6 years old. Beijing has rolled out mandatory AI courses to build fluency early, while the U.S. education system lags behind—reminiscent of early 2000s schools that tried blocking internet access.
"If we don't have trust in AI, if we're not bringing it into our kids' lives, we are not going to future-proof ourselves," Britton warned. "In a globalized competitive landscape, that is a real issue for our nation."
From Knowledge Economy to Creativity Economy
Britton identified a fundamental shift happening in the workplace. The knowledge economy—built on memorizing and applying specialized information—is becoming commoditized by AI.
"The power in AI is far less about how to solve the problem and far more about knowing the problem that needs to be solved," he explained. "It's about creativity, critical thinking, and problem solving. It's far less about retention of knowledge."
This threatens careers built on specialized knowledge: accountants who know how to do taxes, lawyers who know how to write contracts, radiologists who know how to read X-rays. But it also creates opportunity.
Britton cited the automotive revolution as precedent: 38,000 horse-and-carriage businesses went under when Henry Ford introduced the Model T, but 64% of all jobs created in the next decade came from the automotive industry.
The World Economic Forum's Future Jobs Survey identifies the new essential workplace skills:
Analytical thinking: Understanding what problems to solve and what data to use
Resilience, flexibility, and agility: Moving with rapid change without breaking
Leadership and social influence: Building personal brand currency
Creativity: Painting outside the lines rather than just coloring inside them
Curiosity and lifelong learning: Continuously understanding where the world is headed
The "New How" in Photography and Beyond
To illustrate this shift, Britton used photography as an example. Seven years ago, great photographers needed to develop film in darkrooms and master DSLR cameras with complex ISO and F-stop settings. Today, 99.9% of photos are taken on iPhones.
"The people who are seen as the best photographers right now are those that are just adept at where to point the camera to," Britton explained. "That specialized skill set of the knobs and dials is far less important to the problem that the camera solves."
The same principle applies across industries. The "how" of executing tasks is being automated; the "what"—knowing which problems to solve—becomes paramount.
The AI Value Chain: Four Essential Layers
Britton broke down AI into four digestible layers:
Infrastructure
GPU chips (primarily Nvidia) power AI compute in data centers. Demand for data centers is forecasted to increase 30x by 2035, with 40% of Virginia's power already consumed by them. One ChatGPT query uses 33 times the power of a Google search, driving investment in alternative energy sources like nuclear and geothermal.
Large Language Models (LLMs)
ChatGPT, Google's Gemini, and Anthropic's Claude are competing LLMs that process prompts through massive knowledge bases and generate multimodal, multilingual responses. The smartest LLM improved its IQ from 96 to 136 in just one year—imagine your "cousin Billy" transforming from forgetful to Rhodes Scholar in 12 months.
Data
"Data is the new code," Britton emphasized. While every LLM can crawl the open web, the real power lies in proprietary data. Reddit licensed its data to Google's Gemini for $50 million annually because LLMs need specific, niche information for interactive conversations.
Britton demonstrated this by building a real estate chatbot for his friend's Brooklyn brokerage that taps into NYC's open data portal, providing real-time information on traffic patterns, crime rates, new developments, and permits—creating in six hours what would have cost millions to develop years ago.
Applications
This is where AI gets "served up on a dish to consumers." Companies are building innovative products on top of LLMs to solve specific problems. The progression moves from AI tools (like ChatGPT for recipes) to AI automation (stitching processes together) to AI agents (making dynamic decisions based on inputs rather than following predetermined paths).
Multimodal and Multilingual Revolution
Unlike social media's eight-year progression from text (Twitter) to images (Instagram) to video (Snapchat), AI delivers all modalities simultaneously—text, video, images, voice, data visualization, and audio.
Britton showed the evolution of image generation from Version 1 (17 months ago, when generated people had seven fingers) to Version 5.1, which produces photorealistic images with beads of sweat and perfect detail. Version 8 is now in development.
"We are not going to know who's a real person and what is AI-generated," Britton warned, acknowledging concerns about deepfakes, elections, and fraud while expressing hope that AI will help the good guys as much as the bad guys.
Tools like ChatGPT's Image Generator 4.0, Adobe Firefly, Google's Veo, and OpenAI's Sora 2 (released the week of his presentation) enable creating any visual content imaginable—from realistic videos of government shutdowns explained to 4-year-olds to custom TV shows starring your dog Charlie.
"The gap between having an idea in your head and seeing it come to life used to involve layers and layers of resources," Britton explained. "Now it's just asking for it."
Real-World Impact on Insurance
Britton highlighted McKinsey research showing leading insurers reporting 10%+ premium growth within two years of deploying AI solutions through better customer targeting and risk assessment.
Over 55% of U.S. insurers are now in early or full adoption stages of generative AI—the highest rate among financial services groups—because insurance is fundamentally data-driven.
AI addresses longstanding pain points: manual processes, data overload, underwriting speed, and customer personalization. Britton specifically recommended that Nationwide leverage its first-party customer data for hyper-personalization.
"Every email Nationwide sends out should be completely unique DNA and thumbprint to that individual," he suggested. "You know if somebody has kids, you know if they live in the city, you know how many cars they have. You can add value by dynamically generating content unique to an individual, not to a demographic. You can target an audience of one."
The Path Forward: Four Transformation Principles
Britton concluded with four principles for personal AI transformation:
1. Be a Problem Solver: Write down problems you want to solve personally and professionally. Focus on how AI can unlock solutions for growth and efficiency.
2. Practice Perseverance: Don't give up after four failed attempts. Push through to step five, then step 37. You'll look back amazed at what you've built.
3. Leverage Data: Understand how data will drive your AI journey. Data is the way to unlock power.
4. Be Action-Oriented: Have a bias toward doing, not just ideating. The gap between conception and creation is now near-instantaneous, so bring ideas to life quickly.
Addressing the Challenges
During Q&A, Britton tackled difficult questions:
On Risk: Every technology involves tradeoffs. He chose to risk ChatGPT knowing his cholesterol rather than dying of a heart attack. Businesses must weigh data privacy against value unlocked—there's always been risk in crossing the street.
On Leadership: He's changed how he leads by cutting through bureaucracy to work directly with builders at all organizational levels, bringing people his board had never met to strategic meetings because "these are the people I'm building the future with."
On Power Consumption: The drain on electrical grids and water supplies is real and could drive up costs for everyday citizens. His hope is it accelerates alternative energy adoption. Legislation will be necessary, but innovation won't stop—80% of his audience uses ChatGPT over Google despite the 33x energy difference.
On the AI Bubble: There's a bubble in startup valuations (investors conflating AI's magic with entrepreneurs' magic), but AI's transformation of business, culture, and society is "still in the first inning."
The Stakes: Don't Be an Extra
Britton's most sobering warning concerned the future of work. With tools like Sora 2 creating photorealistic videos of people and places that don't exist, movie producers won't need to pay for extras walking around sets when facing budget pressures.
"Don't be an extra in Hollywood. Don't be an extra in the office," he cautioned. "If you have creativity or IP value, you're going to be able to leverage yourself. But if you're just going through motions, that's where we're headed."
Software development job postings are already dropping as companies realize AI can develop software—but they need people who understand what problems software should solve.
Conclusion: The Future Is Already Here
"There's a famous line: the future's already here, it's just not evenly distributed," Britton concluded. "We're kind of there already. Humans are not built to ingest this rate of change."
His advice is clear: start building today. Create personal AI tools at home where you control the data and can experiment freely. Develop problem-solving and critical thinking skills. Embrace creativity over rote knowledge. Practice perseverance through failures.
Most importantly, don't wait for permission or perfect conditions. As Britton demonstrated by creating a music video at 32,000 feet, the tools are accessible now to anyone willing to learn.
For the 4,000 technology executives at Nationwide Insurance—and for professionals across every industry—the message resonates: AI mastery isn't about understanding deep technology. It's about strategy, problem-solving, and having the courage to build.
The choice is simple: future-proof yourself now, or become obsolete. The AI revolution doesn't care which path you choose.
