Brandon Ash, Director of Solution Engineering at Microsoft, shares how enterprise leaders can navigate the AI era by building governed, unified data foundations. He explains why the semantic layer is more critical than ever, how OneLake enables a "skunkworks with guardrails" approach, and why customers who embrace partners go further, faster. 

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Justin Rister, Senior Cloud and AI Specialist at Microsoft, explains why leaders should start with business pain points, not technology. He shares how Fabric unifies the analytics stack for teams of all skillsets, why Databricks and Fabric are a better-together story, and how an AI layer on unified data empowers business users to ask questions and get answers without waiting on IT. 

Tamer Farag, Global Fabric Partner Lead at Microsoft, shares how the fastest-growing analytics platform in the world is helping 31,000 customers unify fragmented data estates and unlock AI value. He highlights why you don't need to move your data to govern it, how mirroring is offered free to accelerate adoption, and what makes partners like Adastra critical to scaling Fabric globally. 

Shannon Bell, EVP, Chief Digital Officer and Chief Information Officer at OpenText, shares how “information first” thinking, simplicity, and agentic AI are reshaping how large enterprises work. She explains why most enterprises don’t have an AI problem but an information problem, how to go slow to go fast with AI, and how a blended workforce of humans and AI agents turns scarce skills and fragmented processes into scalable value. 

Crucially, she digs into change management and the future of jobs: why fear of displacement is often higher than the reality, how to position AI as a copilot rather than a competitor, and what it means to give 22,000+ employees an AI development goal so they can actively shape how their roles evolve. She also shows where agentic AI is ready now, such as search and summarize, root cause analysis, and software delivery, and why success depends on clear roles, governed data, and using HR and SRE teams as early champions to build an “AI fabric” across the enterprise. 

Kevin McCurdy, Global Partner Lead, Consumer Goods, AWS, shows how Gen AI, trusted data, and risk-based guardrails turn experiments into repeatable CPG value. He highlights AWS and partner capabilities (Amazon Bedrock, SageMaker, secure integrations) with real wins such as demand forecasting, planogram automation, and Adastra’s Mark Anthony Group solution that scales assortment optimization and auto-generates seller scripts, plus quick-win assistants, cost controls, and an enterprise AI program with clear budgets, ownership, and accountability across product, employee, and customer use cases. 

Rehan Shah, General Manager and Head of Channel and Partner Sales for US Greenfield at AWS, explains how the right mix of AI tools, trustworthy data, and strong controls turns early AI trials into real business results. He shows how AWS provides access to top models, better value, responsible AI practices, and secure ways to connect your systems. Examples include instant insights from manufacturing data and Breakthru Beverage moving hundreds of servers, plus quick AI helpers like a Sales Coach and a Legal Assistant. He also shares how to keep costs in check and set up a company-wide AI program with clear budgets and accountability. 

 Chris‑Markus “CMK” Kratz, AWS Global Director of Automotive and Manufacturing, explains how outcome‑first, customer‑obsessed transformation and ecosystem partnerships are reshaping the industry. He details the shift to software‑defined vehicles and the car as a proactive companion, how GenAI is collapsing mainframe refactoring from years to months, and what it takes to move beyond pilots to production. Kratz shares lessons from Amazon’s own “shop floor” in its fulfillment centers, why the cloud is ready for OT, and why critical thinking and change management matter as much as technology. He also covers autonomy at scale, the equalizing effect of AI for SMBs and OEMs alike, and the “better together” role of SIs like Adastra.