The first full week of 2026 made one thing clear: AI is no longer just a layer on top of existing systems. It is becoming the infrastructure that governs how people search, shop, and experience media, and the constraint that determines which companies can scale with credibility.
1. Google’s UCP Brings Checkout Inside AI Search
The update
Jonathan Snow’s latest breakdown details how Google is turning AI search into a full-funnel commerce surface with its new Unified Commerce Protocol (UCP).
Read: Google Introduces AI-Powered Shopping for a Streamlined Buying Process
Until now, AI shopping experiences such as Instacart’s direct checkout in ChatGPT and Perplexity’s AI shopping assistant have combined recommendations with a handoff step. UCP compresses that flow:
- AI Mode + Gemini return highly specific products (for example, a lightweight hardshell carry-on in a particular color and price range) directly inside AI results.
- Users can add items to a cart and check out without leaving Google, using Google Pay today and PayPal in the near future.
- Partners such as Shopify, Walmart, Target, Wayfair, and Etsy helped design the protocol so brands remain Merchant of Record while Google orchestrates the experience.
- Merchants configure products and offers, including AI-only discounts that appear inside AI chats and recommendations.
Why it matters
The familiar sequence of search, click, site, cart, and checkout is being reduced to a single interaction inside an assistant. That changes the underlying questions for brands:
- Where is the storefront. Visibility inside AI commerce flows will matter as much as (and in some categories more than) traditional SERPs or paid units.
- What counts as optimization. Product data, pricing, availability, and creative now need to be structured for AI summarization and ranking, not only for human browsing.
- Who controls the experience. Brands retain legal and commercial control over products, but the orchestration layer belongs to Google. Differentiation, measurement, and promotion will increasingly be negotiated within that frame.
2. The U.S. vs EU AI Reckoning Moves From Values to Governance
The update
In The U.S. vs EU AI Reckoning: Why Governance Will Decide the Winners in 2026, I outlined how last year’s “values versus velocity” debate has given way to a more practical question: which organizations can operate credibly across both systems.
In 2025:
- The United States moved from rhetoric to execution with America’s AI Action Plan. Infrastructure, procurement, and deregulation became the primary levers, signaling a clear preference for competitiveness and deployment ahead of comprehensive guardrails.
- The European Union shifted from legislating the AI Act to enforcing it. Classification, documentation, and audit preparation moved from slideware to operating reality.
- U.S. courts, rather than legislatures, set some of the most consequential global norms on copyright and training data. Those decisions now shape baseline expectations for any company building or deploying models, regardless of jurisdiction.
The perceived choice between U.S. speed and EU compliance has largely collapsed. Companies are now expected to move quickly and demonstrate control at the same time.
Why it matters
Governance has become the connective tissue that allows organizations to scale across markets:
- It is no longer a philosophical exercise or a checkbox. It sits in infrastructure decisions, data provenance, model accountability, and incident response alongside financial and cyber risk.
- Legal exposure is being defined by courts, contracts, and procurement requirements as much as by formal statutes. Boards that treated AI governance as a secondary concern in 2025 are already seeing the cost of that decision.
- Trust, credibility, and license to operate now function as strategic assets. In an environment where AI systems mediate discovery and decision-making, these are prerequisites for growth, not afterthoughts.
3. Anthropic Expands “Labs” for Frontier Claude Products
The update
Anthropic announced an expanded Labs group focused on incubating experimental products at the frontier of Claude’s capabilities.
Read: Introducing Labs
The structure is straightforward:
- Mike Krieger, Instagram’s co-founder and Anthropic’s former Chief Product Officer, joins Labs to build alongside co-founder Ben Mann.
- Ami Vora takes over the broader Product organization, working with the CTO to scale Claude experiences that already serve millions of users.
Labs is framed as the environment where work such as Claude Code (which went from research preview to a billion‑dollar product in six months) and the Model Context Protocol (MCP) (now at over 100M monthly downloads) is discovered, tested with early users, and prepared for broader release.
Why it matters
This is a signal about cadence and method more than branding:
- Frontier capabilities are likely to appear first as experiments, with limited guarantees and rapid change. Enterprise-ready products will follow behind them.
- Agentic workflows are clearly a priority. MCP is already functioning as a standard for connecting models to tools and data; Labs gives Anthropic a dedicated space to push that pattern further.
- Early adopters will shape what “Claude-native” work looks like. Organizations willing to participate in Labs-style previews can influence how future agents behave, integrate, and expose controls.
For leaders, the implication is that tooling for 2027 is being prototyped now at the edge of these Labs programs. The question is not whether to engage, but when and under what constraints.
4. Gemini Introduces Personal Intelligence That Actually Uses Your Context
The update
Google launched Personal Intelligence, a beta feature in the Gemini app that allows users to connect Gmail, Photos, YouTube, and Search so Gemini can reason across their own information, not just public data.
Read: Gemini introduces Personal Intelligence
When enabled:
- Gemini can retrieve specific details, such as a license plate number from a photo or a flight confirmation from an email, and combine them with external knowledge.
- It can plan trips, surface recommendations, and answer questions based on actual history and preferences instead of generic personas.
- Google emphasizes that connections are opt‑in, can be revoked at any time, and that Gemini does not train directly on the contents of Gmail or Photos. The model is trained on prompts and responses after filtering and obfuscation.
Why it matters
Personal assistants are moving from answering general questions to managing personal context:
- Systems that can see receipts, itineraries, and photo histories will have a durable advantage in relevance. That shifts competition from model benchmarks to data access and control.
- Privacy posture and provenance will increasingly define adoption. Users will ask not only “What can this do?” but “What does it see, and how does it handle that exposure?”
- Brand recommendations will become more contingent on a user’s real behavior and constraints. Being “generally relevant” will not be enough; content and offers will need to map to lived patterns to earn a place in these responses.
For brands, this is an early preview of assistants that behave less like search engines and more like long‑term, memory‑rich guides.
5. NBC Sports Uses AI to Let Fans Follow Individual Athletes
The update
NBC Sports is adopting viztrick AiDi, an AI-powered player tracking system developed by Japan’s Nippon Television Network, to give mobile viewers the option to focus on specific athletes during live events.
Read: NBC Sports’ new real-time player tracking lets viewers focus on their favorite athletes
The system:
- Uses facial recognition to identify and track players in real time.
- Allows operators to tap a player on screen and follow that athlete automatically.
- Crops horizontal broadcast feeds into vertical, athlete‑centric clips suitable for mobile viewing, with the potential for overlays such as names and stats.
NBC anticipates rolling this out across select broadcasts beginning this year, including coverage of the 2026 Winter Olympics in Milano–Cortina.
Why it matters
Sports have long been a proving ground for new media formats. This is the next step:
- Viewers gain control over perspective. Instead of a single canonical broadcast, they can opt into specific narratives: a star player, a national team, or a position group.
- New surfaces emerge for sponsorship and commerce. Athlete-focused feeds create more granular opportunities for brand placement, measurement, and shoppable content.
- The same mechanics will not stay in sports. Once audiences expect to choose their angle in live events, similar patterns will migrate to concerts, conferences, and other formats.
For marketers and media teams, this is a clear signal that “one feed for everyone” is aging out. AI-driven personalization will increasingly define what “watching live” means.
What This Means for Leaders and Teams
Across these developments, a few patterns stand out:
- Agents are becoming infrastructure. From UCP in commerce to Claude Labs in productivity, AI systems are beginning to coordinate full workflows rather than provide isolated outputs.
- Personal context is becoming central. Gemini’s Personal Intelligence and similar work elsewhere indicate that assistants will be evaluated on how effectively they use your data, not just on how broadly they understand the world.
- Governance is the limiting factor. Whether in U.S.–EU alignment, data access, or broadcast personalization, the question is no longer if AI will be regulated or accelerated. It is whether organizations can operate credibly in a world that demands both.
For leadership teams, the practical work lives in three places:
- Strategy and discovery. Identify where AI is already mediating your customer journeys and where that mediation is likely to deepen in the next 12–24 months.
- Operational design. Treat AI governance, data pipelines, and model interfaces as core architecture, not bolt‑ons.
- Experimentation with boundaries. Engage with frontier tools and programs such as Labs and Personal Intelligence, but do so with explicit guardrails on data, accountability, and acceptable risk.
The takeaway is not alarm, but calibration. AI is moving into the center of how markets transact and how institutions maintain trust. The companies that will be able to scale through 2026 and beyond are the ones that treat that shift as both an opportunity and an obligation.
If you want to understand how these shifts show up in your own search, shopping, and media footprint, start with the foundations:
- Explore how AI Optimization can help your brand show up credibly in AI search, agents, and new commerce surfaces.
- Talk to our experts about how to align AI visibility, governance, and communications for your specific category.
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