CES 2026: Segun Oduolowu Interviews Matt Britton on How AI Will Rewrite the 2026 Business Playbook
CES has always been a preview of what the next 12 to 24 months will demand from business leaders. Some years the headlines are hardware: streaming boxes, 3D TVs, phone accessories. CES 2026 feels different. The center of gravity has shifted to software that thinks, speaks, and acts. Every major company is positioning artificial intelligence as the core operating layer for products, marketing, and internal execution. CES itself is officially scheduled for January 6 to 9, 2026, in Las Vegas, and the timing matters because the market is moving from “experimentation” to “prove the value.” (CES)
That tension is what made the CES 2026 on-stage conversation between Emmy Award-winning journalist and CNN contributor Segun Oduolowu and Suzy CEO and author Matt Britton feel unusually direct. Oduolowu, known for his broadcast work and regular appearances on major outlets, framed the discussion with a simple, pragmatic question: how is AI changing influence, marketing, and careers right now, and what happens to those who do not adapt.
Britton’s answers were not abstract. He anchored the conversation in two realities that business leaders are now forced to hold at the same time:
AI will compress the time and cost required to produce software, content, analysis, and creative output.
AI will raise consumer and employee expectations faster than most organizations can rewire their culture, operating model, and decision systems.
This post breaks down the core ideas from the interview and translates them into a 2026-ready playbook for brands, marketing leaders, and operators.
Why this CES 2026 interview landed: AI is becoming the new front door
Oduolowu opened with Britton’s origin story: a decade ago, Britton wrote Youth Nation, arguing that social platforms shifted power from boardrooms to the street. This time, Britton’s focus is Generation AI, built around a larger claim: Gen Alpha (roughly ages 0 to 15) will never know a world without AI that you can talk to like a person. That matters because it changes the default interface for discovery, shopping, learning, and decision-making.
In plain terms, AI is becoming the first interaction layer between consumers and the world. Not a channel you “market on,” but the place where intent gets expressed and shaped.
Britton also made a crucial distinction that many executives miss: AI has been present for years in recommendation engines, like what to watch next or what to listen to next, but the ChatGPT-era shift is about accessibility. AI moved from “invisible algorithm behind the scenes” to “a tool in everyone’s hands,” with a human-like interface that makes adoption frictionless. That new interface is what forces marketing and business strategy to change.
The marketing reset: from one-to-many to one-to-one expectations
One of the sharpest parts of the interview was Britton’s view that consumer expectations will quickly outrun standard marketing workflows.
Today, much of marketing is still built around scalable sameness: one email, one landing page, one message, sent to millions. Britton argued that this will feel outdated to the next consumer, who will expect brands to treat them as an audience of one. The implication is not “more personalization tokens.” It is personalization that is actually useful and context-aware, delivered at the moment of decision, across the entire customer journey.
That is a hard shift, because it requires three things most organizations do not have in one place:
Clean, permissioned customer data
Systems that can interpret context in real time
Governance that protects trust while still enabling speed
This is where many brands will fall into a trap: they will try to layer AI on top of broken data and fragmented workflows. The result will be faster production of mediocre outputs, not better customer experiences.
Britton’s point was that AI will not simply automate marketing execution. It will redefine what “good” looks like.
“Sports doping” for marketers: how brands keep up when consumers get superpowers
Oduolowu used a smart analogy: in sports, athletes and drug makers stayed ahead of testers. If consumers get AI tools first, how do brands “stay ahead” of consumers?
Britton’s answer was not about manipulation or clever targeting. It was about meeting the new baseline of expectations: speed, relevance, and seamlessness. Consumers will use AI to compare, decide, and optimize faster than your internal process can run a weekly meeting. So the brand advantage shifts to the organizations that can:
Sense what consumers want in near real time
Turn insight into action without organizational drag
Communicate in a helpful, conversational mode rather than interruptive formats
That last point is important. The creative format is changing with the interface. A static ad unit is a weak fit for an interactive conversation.
The Suzy case study: when software becomes cheaper, data becomes the moat
Britton used Suzy’s trajectory as a case study in disruption. His claim: the “tooling layer” in software is being commoditized because modern creation tools let small teams build what used to require large budgets. When product capabilities get copied quickly, advantage shifts to what is harder to replicate: proprietary data, distribution, and trust.
For Suzy, that means leaning into the consumer insights data they have amassed for clients and turning it into decision-ready outputs, not just charts. Britton described a move from traditional research deliverables toward story-based assets that travel through organizations: visuals, infographics, even video outputs that help teams build conviction and drive internal alignment.
This is a broader lesson for every enterprise: in an AI-heavy market, your defensibility is less about features and more about your unique inputs and your ability to turn those inputs into decisions.
The end of “deterministic work”: why careers are now on the line
The interview shifted from brand strategy to personal survival in the labor market.
Britton argued that if your job is primarily “deterministic” (repeatable tasks, moving information from one place to another, waiting to be told what to do), you are exposed. Those tasks are exactly what AI automates best.
He reframed “future-proofing” as a skill shift away from knowledge regurgitation and toward thinking-based skills:
problem definition
creativity
critical thinking
initiative
building and iterating quickly
His message was blunt: if you do not move up that stack, you risk getting a short email one day telling you the role is gone.
Whether or not you agree with the tone, the direction of corporate behavior supports the thesis: companies are actively reducing layers and investing in automation to increase output per employee. Britton even referenced large-scale layoffs as a sign of flattening, with an emphasis on eliminating roles that exist to “move data around.” (The specific layoff figures and framing vary by source and time, but the directional trend toward flattening and automation is widely visible across big tech and large enterprises.)
Why many companies are stuck: AI-first slogans vs. real constraints
Britton highlighted a constraint that anyone inside a large enterprise recognizes immediately: employees cannot just download random AI tools and upload customer data. Legal, security, and privacy restrictions are real.
His workaround is practical: build projects at home where you are not blocked. Use personal data. Solve a real personal problem. Learn the process end to end.
This matters because it flips AI literacy from passive to active. Britton is not talking about “prompting.” He is talking about building a workflow or application, even a simple one, that forces you to learn:
how to define the problem clearly
what data you need and how to structure it
how to test outputs and correct errors
how to deploy into a real environment where someone actually uses it
He said directly that he does not want to hire anyone who has not built something with AI beyond basic consumer use. That is a hiring filter more companies will adopt in 2026.
How to find the “unicorns” inside your company
Oduolowu pressed on a key leadership problem: how do companies identify people who can do this.
Britton’s answer: those people may already be inside your org, buried. His own example was forming a SWAT team by finding the small group of builders who understood what was possible and giving them direct mandate and visibility. The lesson is not about titles. It is about demonstrated capacity to ship.
For leadership teams, this implies a different approach to talent:
Look for output, not pedigree
Reward initiative and shipped prototypes
Create paths for builders to influence product and process
Reduce bureaucracy that slows experimentation
Bring AI capability closer to business owners instead of central “centers of excellence”
Britton also described a structural shift: functions like insights teams may shrink as AI makes complex methods easier to access. In other words, methodology goes “beneath the hood,” and the business owner’s ability to define the right question becomes the differentiator.
A concrete example: using customer call transcripts as an operating system
The strongest “show me” moment in the interview was Britton walking through a specific internal build at Suzy.
He described starting with a single data source: recorded customer and prospect calls (transcripts). By aggregating a large corpus of real conversations, the team created multiple applications:
automated call summaries
customer sentiment scoring
alerts to managers when sentiment drops below a threshold
insights that feed product roadmap and content planning
an internal resource engine for sales enablement
He also noted a behavioral design point: adoption is hard when you introduce a brand-new tool. So he pushed outputs into Slack, where teams already work.
This is a repeatable pattern for many organizations: pick one high-signal dataset (calls, support tickets, CRM notes, emails), build a system that converts raw text into decision-ready signals, and deliver it inside existing workflows.
What happens if brands and companies do nothing
Oduolowu asked the question most executives avoid: what happens to brands that do not adopt this style of thinking.
Britton’s answer was not “AI will destroy you tomorrow.” He said timing varies by category. Software businesses are more exposed because disruption cycles are faster. Physical goods companies with distribution and shelf presence may have a longer runway. But the direction is the same: incumbents that avoid internal transformation create openings for smaller, faster competitors that start by “nibbling at the ankles” and eventually take meaningful share.
The deeper risk is not only market share. It is talent. High-agency builders will not stay in environments that block experimentation. That becomes a compounding disadvantage.
The core takeaway: start by solving one real problem and build step-by-step
At the end of the interview, Britton’s advice was consistent: stop asking what tools to use. Start by identifying the problem you want to solve.
Then he gave a practical way to execute: ask an AI system for step-by-step instructions and force it into a gated workflow: “Do not give me step two until I tell you step one is done.” That forces clarity, reduces overwhelm, and creates momentum.
He offered personal examples like building a support agent for his mother by uploading manuals and passwords, showing that even small builds train the mindset needed for bigger enterprise-grade work.
Why this matters for the 2026 business landscape
The Britton-Oduolowu exchange captured the real shift behind the CES 2026 noise:
AI is not only a productivity tool. It is changing consumer expectations and business interfaces.
The advantage is moving from “who has the best process” to “who can define the best problems and ship fastest.”
Data is becoming the primary moat as feature differentiation compresses.
Careers will reward builders and high-agency thinkers, not passive knowledge workers.
Segun Oduolowu framed the conversation through the lens of media disruption and job replacement fears. Britton reframed it as a test of initiative: you can either wait for change to happen to you, or you can build your way into the future.
