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CES has always been a preview of what is next, and with AI, Web3 and Robots all converging, it became a measure of what is becoming foundational.
Bringing together over 148,000 attendees from over 150 countries, alongside 4,500 exhibitors and 1,400 startups, the show rocked Vegas per CTA.
Artificial intelligence was everywhere, but the most important takeaway was not about smarter models or faster chips. The major theme I saw running through everything I saw was personalization, and how difficult it has become to do it well, safely, and at scale.
Across the show floor, the companies that stood out were not chasing novelty. They were building systems that adapt to people, preferences, and context. That is where Web3, Robots and AI are converging, not as buzzwords, but as infrastructure.
You may be thinking that personalization is a front end problem focused on recommendations, interfaces, and feeds. CES made it clear that personalization has become a crucial element of trust.
Per McKinsey, personalization can enhance customer satisfaction by 15 to 20 percent, increase revenue by 5 to 8 percent, and lower cost to serve by up to 30 percent when powered by AI and agentic systems.
As AI systems move into higher stakes environments, data provenance and trust matter as much as intelligence itself.
Vannadium exemplified this shift with Leap, a real time, onchain data platform designed to make AI systems explainable and auditable. By enabling high value data to be streamed onchain with full provenance and access control, Vannadium reframes blockchain as an enterprise trust layer for AI rather than a financial experiment.
In chatting with Laura Fredericks, Co-Founder and Chief Growth Officer, Vannadium, while we took a picture “onchain” she told me that “st Vannadium we believe that trusted data must be provable and persistent. Having a picture taken and stored on-chain is more than metadata. It is an immutable foothold in the digital record that future AI systems can rely on with confidence. When AI models are trained and audited against data you can verify, the personalization and decisions they enable become not just intelligent but accountable and secure.”
Identity followed a similar trajectory. Veintree demonstrated privacy first authentication using biocryptography, verifying individuals without storing biometric data. In an era of increasing regulation and declining consumer trust, proving identity without harvesting it is a powerful signal.
Trust is also becoming human, not just technical. The AI House featured The Unstoppable Women of Web3 and AI initiative (note this is a company that I work with) highlighted how reputation and credibility are turning into portable infrastructure.
In a world of AI generated content, verified human identity is becoming a differentiator.
Another clear theme at CES was the evolution of AI from tools into orchestration.
Lenovo’s immersive Sphere experience showed AI acting as a connective layer across devices and workflows rather than a standalone assistant. The emphasis was not novelty but friction reduction, with AI understanding context and coordinating work across systems.
That same idea appeared at AI House by Modev, where personalization was applied to access itself. Instead of generic content, Modev curated the right people and conversations at the right time, reinforcing that relevance is now the most valuable form of personalization.
CTGT AI approached the problem from a decision intelligence angle. Its systems prioritize actions based on role, timing, and intent. The takeaway was subtle but important. AI that simply answers questions increases cognitive load. AI that guides decisions reduces it.
In chatting with the CEO and Founder of CTGT, Cyril Gorlla, he explained to me that “Personalization and trust go hand in hand. If AI cannot be trusted to behave reliably in context-sensitive environments, it cannot scale. Our approach goes beyond surface level prompts or caching results. We give enterprises deep control over how models behave, reduce unwanted outputs in real time, and surface insights that make AI dependable for high-stakes decisions.”
One of the most quietly important moments at CES came from a company not typically associated with AI hype.
LEGO’s Smart Brick operates without an internet connection, without continuous data collection, and without an on off switch. Intelligence is embedded in behavior and interaction rather than cloud connectivity. The design prioritizes durability, privacy, and fail safe operation.
This challenges the assumption that smarter products must always be more connected. As AI becomes ubiquitous, human first personalization may depend on fewer failure points, not more data exhaust.
Personalization is also shifting from functional customization to dynamic self expression.
iPolish and Peuty approached different categories, beauty and accessories, but delivered the same message. Identity is becoming programmable. Nails that change color through software and bags that adapt visuals in real time point to a move from static products to living interfaces.
In playing with the Peuty bag, Richard Peuty, Founder and CEO of Peuty, “At Peuty we are rethinking what fashion can be when style and technology truly come together. The Infinity bag is not about being connected for its own sake. It is about using AI to make personal expression fluid and dynamic in real time. Personalization is no longer static product design. It is an adaptive style that responds to the wearer’s context, mood, and intent.”
Creative tools like Lollipop Star reinforced another shift. By combining novel hardware with personalized audio experiences delivered through bone-conduction, it hints at how AI-driven personalization may increasingly move beyond screens and into physical, sensory interactions. Instead of algorithms choosing content for users, AI becomes a co creator that enables people to actively shape what they consume.
CES also showed how personalization is moving off screens and into daily life.
Nosh demonstrated how AI can personalize cooking based on dietary needs, preferences, and routines. This is not automation for its own sake. It is a context aware service, where intelligence adapts to the individual rather than forcing standardized behavior.
That same philosophy was evident in LG’s vision for the home. LG is not treating robots as standalone novelties. Instead, it is building toward an integrated AI Home, where robotics technology is embedded across appliances and environments. This includes home robots designed for household assistance, as well as what LG calls Appliance Robots, such as robotic vacuums, and Robotized appliances, including refrigerators with doors that open automatically as a person approaches.
The goal is not to add more devices, but to reduce friction across everyday life. By distributing intelligence across appliances and home robots, LG is working toward a Zero Labor Home, where routine housework is handled by AI systems and people reclaim time for higher value activities.
“The LG CLOiD home robot is designed to naturally engage with and understand the humans it serves, providing an optimized level of household help,” said Steve Baek, president of the LG Home Appliance Solution Company. “We will continue our relentless efforts to achieve our Zero Labor Home vision, making housework a thing of the past so that customers can spend more time on the things that really matter.”
This framing matters. It positions personalization not as a feature, but as an ambient capability. AI adapts to how people live, move, and behave inside their homes, quietly reducing effort rather than demanding attention. That is what personalization looks like when intelligence becomes infrastructure.
One of the most compelling ideas at CES came from infrastructure rather than interfaces.
Superheat reimagined Bitcoin mining by capturing waste heat and repurposing it to warm homes and buildings. The innovation was not about cryptocurrency. It was about infrastructure that adapts to place and purpose, turning excess cost into functional value.
CES 2026 was not just an AI show. It was a systems show.
The companies that stood out understood that personalization is no longer a surface level feature. It is structural. Making it work requires AI for adaptation and Web3 technologies like blockchain and identity for trust, provenance, and accountability.
The next competitive advantage will not come from smarter models alone. It will come from systems that understand people, adapt to context, and earn trust by design. At CES, that was shown in how Robots, Web3 and AI are redefining personalization, and why this shift is only beginning.
