Loved this. One thing that stood out to me from Adobe's announcements at Cannes wasn't just the technology—it was the ecosystem. When organizations like Accenture, WPP, Omnicom, Stagwell, Microsoft, Anthropic and others are all building on the same foundation, it signals something much bigger than another AI announcement. It signals that enterprises are moving from isolated AI use cases to connected operating models. What excites me most isn't simply the emergence of AI agents. It's what happens when those agents have access to: • Trusted fan data • Unified fan profiles • Real-time behavioral signals from fans • Enterprise content supply chains • Journey orchestration • Measurement and attribution • Governance and brand controls That's where AI begins producing business outcomes—not just content. One implication I don't think gets enough attention is the role of fan data. Organizations that have invested in a real-time customer data foundation are significantly better positioned to operationalize Agentic AI. AI agents are only as effective as the context they're given. When they can reason over unified customer profiles, identity resolution, consent, and real-time behavioral signals—instead of fragmented systems—they move from generating outputs to making intelligent decisions. To me, that's why technologies like our RTCDP become even more strategic in the agentic era. The investment isn't simply about building better audiences or improving segmentation anymore. It's about creating the trusted intelligence layer that AI agents depend on to deliver personalized, governed, and measurable customer experiences at enterprise scale. In my work with sports organizations and enterprise brands, one challenge comes up repeatedly: Great ideas aren't the bottleneck. Operational complexity is. Content lives in one system. Customer data in another. Campaign execution somewhere else. Measurement often arrives too late. Agentic AI has the potential to connect those pieces together—but only when it's built on a strong data foundation. The winners won't simply have the best AI models... They'll have the best customer intelligence and the best connected systems. And they'll have the operational readiness to put AI into action responsibly. We've spent the last several years helping organizations unify customer data. The next several years will be about putting that data to work through intelligent agents that can reason, recommend, and act. Agentic AI isn't replacing the customer data foundation. It's increasing its strategic value. #Adobe #AgenticAI #AI #RealTimeCDP #CustomerExperience #DigitalTransformation #MarTech #Personalization #SportsBusiness #CustomerData

The companies pulling ahead on AI aren't running experiments. They're rebuilding how their teams work from the ground up. At #CannesLions2026, (@)Marissa Dacay of (@)Adobe joined (@)Alyssa Merwin Henderson, (@)Ekta Chopra, (@)Michelle Hillman and (@)Preeti Saini to unpack the difference between AI adoption and AI transformation, and what separates the two.

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6043voTVc #MSFTAdvocate

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6042voTzE #MSFTAdvocate

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6045voHjV #MSFTAdvocate

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6040vo2Xy #MSFTAdvocate

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6044vqzzn #MSFTAdvocate

As AI moves from experimentation to large-scale deployment, an important question remains: who benefits from the value it creates? In this Wall Street Journal interview, Satya shares why customer choice, lower costs, and broader access to AI matter for long-term innovation and growth. Learn more: https://msft.it/6047vS0p1 #MSFTAdvocate

Day 1 at the Applied AI for Distributors Conference in Chicago is officially underway! The biggest takeaway from today's opening sessions? We are officially moving past the AI hype and focusing on real-world execution. The industry is shifting from "what can AI do?" to "how do we operationalize it for ROI?" More to come over the next two days!

We’re seeing Frontier Firms move from AI experimentation to real execution. The impact is already clear: 58% of AI users say they’re producing work they couldn’t have a year ago, rising to 80% among Frontier Professionals. Explore how leading organizations are structuring work around AI to unlock new levels of impact 👉https://msft.it/6049v5nit