The Future of AI & Finance: Insights from Matt Britton’s Las Vegas Keynote At Beyond The Black
In Las Vegas, marketing and technology leader Matt Britton delivered a keynote that captured the urgency, promise, and disruption surrounding artificial intelligence. Drawing from his experience as CEO of Suzy and decades spent analyzing consumer behavior, Britton laid out why AI is not just another technological cycle—it is a transformation that will reshape business, education, and daily life at a speed the world has never seen.
This keynote, grounded in personal anecdotes and professional foresight, explored the rise of Generation Alpha, the limits of the knowledge economy, and why business leaders must experiment with AI personally before they can apply it effectively in their organizations.
From Millennials to Gen Alpha: Understanding the New Consumer
Britton has spent his career helping global brands understand “the new consumer.” That journey began with Millennials, the first generation to grow up with the internet at home. It continued with Gen Z, defined by the iPhone and social media. And now it turns to Generation Alpha—the first cohort to grow up in a world where AI is as natural as electricity.
Millennials: Internet-native at home.
Gen Z: Smartphone and social media as extensions of identity.
Gen Alpha (Generation AI): Will never know life without AI and will communicate with machines as easily as with people.
For Britton, understanding these generational shifts is essential because every wave of consumer behavior reshapes markets. Just as brands had to rethink marketing in the era of social media, they now must prepare for a generation that views AI as a baseline utility.
Why AI Is Different From Every Other Technology
One of the keynote’s central themes was that AI is not like the internet, mobile, or social media—it represents a new paradigm in how humans interact with computing.
When ChatGPT launched, Britton initially handed it to his engineers to explore its business applications. Weeks later, nothing materialized. That inaction became his revelation: AI cannot be treated as a backend feature. It requires leaders to rethink how humans and machines collaborate.
Unlike previous tools, AI doesn’t just enable faster work. It alters the very definition of work by automating knowledge tasks, unlocking new creative potential, and forcing organizations to reconsider their operating models.
A Personal Experiment: The Healthbot Story
To understand AI’s power firsthand, Britton built something personal before building for business. At age 50, with young children, he wanted to maximize his longevity. He pulled together 25 years of medical records—blood tests, X-rays, MRIs, doctor notes—and trained a custom healthbot.
The bot, modeled after a leading Johns Hopkins physician, analyzed his personal data and delivered blunt insights without the sugarcoating of a human doctor. It surfaced anomalies from years ago, created medical dossiers for specialists, and offered actionable pathways for preventive health.
The lesson was clear: AI’s power lies in personalization and structured data. What was once scattered across files and PDFs became a coherent system that could predict risk and guide better decisions.
The Lesson for Businesses: Build Personally First
Britton urged executives to follow a similar path. Large corporations often face barriers to AI adoption—data privacy, security restrictions, and compliance rules. These limitations make it difficult for employees to freely experiment with consumer-grade tools.
The workaround? Start small and personal.
Build a family chatbot to manage schedules.
Create a password bot for elderly parents.
Organize personal finances through AI-powered dashboards.
By solving one personal problem, leaders gain the confidence and skills to later apply AI at scale in their organizations.
The AI Value Chain: From Infrastructure to Applications
Britton broke down AI into a value chain that businesses must understand:
1. Infrastructure
The foundation is compute power, especially GPUs (graphics processing units). Companies like Nvidia, Amazon, and Microsoft are racing to supply the massive energy-hungry infrastructure required for large-scale AI.
2. Large Language Models (LLMs)
ChatGPT, Claude, Gemini, and open-source models like Llama are competing to become smarter, faster, and more context-aware. LLMs transform prompts into outputs by scanning trillions of data points. Unlike Google’s search engine that delivers links, LLMs generate direct answers, making them the new interface of information retrieval.
3. Data
Data is the differentiator. As lawsuits between Reddit, Disney, and AI model builders show, ownership of data is emerging as a central battleground. Companies that structure and protect their proprietary data will hold the advantage.
4. Applications
Applications are where AI touches consumers—chatbots, text-to-video tools, image generators, and voice assistants. Progress is rapid: tools that produced crude images two years ago now deliver photorealistic content. Soon, full-length movies will be created from text prompts alone.
The End of the Knowledge Economy
Britton argued that society is leaving the “knowledge economy,” where success came from mastering information and regurgitating it for pay. Lawyers, accountants, radiologists, and coders all built careers on this model.
But in a world where AI can instantly generate knowledge, the premium shifts toward:
Creativity: Framing the right problems.
Critical Thinking: Evaluating outputs and implications.
Problem Solving: Applying insights to real-world contexts.
Education systems rooted in memorization will need to adapt. Students no longer gain advantage from knowing more facts—they gain advantage from knowing what to do with facts machines can instantly supply.
Disruption in the Workforce
Big tech companies like Meta, Amazon, and Google have already laid off tens of thousands of workers, many replaced by AI efficiency. Britton predicted this disruption will cascade into mainstream industries like retail, logistics, and finance.
The takeaway: job loss is inevitable in certain roles, but opportunity abounds for those who reposition around strategy, creativity, and AI fluency. Leaders must ensure they and their organizations are on the right side of this shift.
The Rise of AI Agents
Perhaps the most forward-looking part of the keynote was Britton’s focus on AI agents.
Unlike simple automation, which moves step-by-step through a workflow, AI agents operate dynamically. They can jump from step one to step eleven, back to step six, coordinating multiple tools to accomplish complex objectives.
Finance leaders, in particular, should prepare. Studies suggest that within three years, most finance operations will be run by agents. Few leaders fully grasp what that means, but those who build early will gain outsized advantage.
Why Data Is the Ultimate Unlock
Returning to his healthbot analogy, Britton explained that the same principle applies in business: keeping a company alive requires understanding its vital signs.
For finance professionals, this means structuring balance sheets, P&Ls, and cash-flow statements into systems where leaders can “talk to the data.” By asking natural-language questions—“What levers will most improve free cash flow?”—executives can move from raw data to strategic action instantly.
AI doesn’t eliminate finance roles. It elevates them. Instead of crunching numbers, finance leaders become interpreters of business equations that guide growth.
The Communication Revolution: Text, Video, and Voice
Britton highlighted that AI is not confined to text. Multimodal capabilities—spanning video, images, and voice—will redefine how data is communicated inside companies.
Text to Video: Platforms like Google Veo can instantly generate 4K clips from prompts. In the future, leaders may produce Hollywood-style explainers for financial data.
Voice Interfaces: Improved transcription and conversational agents will streamline audits, interviews, and compliance.
Digital Twins: Individuals will soon clone their voices and appearances, raising both opportunities (scalable communication) and risks (deepfakes and fraud).
For finance and corporate leaders, the implication is clear: effective storytelling with data will matter as much as the data itself.
Why Leaders Must Build With AI
Britton closed with a call to action: every leader must become a builder.
It doesn’t require technical training or “prompt engineering.” Curiosity and focus are enough. The key is to pick a problem, structure the data, and follow a step-by-step process with AI tools.
Those who do will separate themselves in the marketplace. Those who don’t risk obsolescence.
Conclusion: The Urgency of Now
Matt Britton’s Las Vegas keynote was more than a presentation on AI—it was a blueprint for how individuals and businesses can navigate the most significant technological shift since the dawn of the internet.
Generation Alpha will grow up in an AI-native world.
The knowledge economy is giving way to a creativity and problem-solving economy.
AI agents will soon run core business functions.
Data remains the critical differentiator for growth and resilience.
Leaders must experiment personally before they can lead organizationally.
Britton’s message was equal parts caution and optimism. AI will eliminate roles, but it will also empower those willing to adapt. The future is arriving faster than most expect, and the time to build is now.
