Show Me the ROI: What Enterprise AI Actually Delivers in Year 4 - Panel
The hype cycle is over. The pilot graveyard is full. MIT research suggests that 95% of Generative AI implementations have little to no measurable impact on P&L. So what separates the 5% that actually deliver? In this no-fluff panel, practitioners from the front lines of enterprise AI — spanning automotive, cloud platforms, and the messy middle of real-world deployment — will have a candid conversation about what's working, what consistently stalls, and what it actually takes to move from experimentation to results.
The panel will discuss:
- The use cases that outperform the hype — and the organizational conditions that make them possible,
- Why pilots die on the way to production — and how to stop losing momentum at the one-yard line
- How leaders are defining and proving ROI — what metrics matter, what's a vanity win, and how to tell the difference.
- What "AI readiness" actually looks like — versus what organizations think it looks like.
This is the conversation happening in sold-out rooms. Now it's yours.
Ken Johnston is a Founder of the AiGovOps Foundation, a nonprofit practitioner community advancing AI Governance as Code — the discipline of embedding governance controls into AI systems through engineering rigor, automation, and operational feedback loops rather than policy documents and good intentions. With over 30 years of engineering and data leadership, Ken brings rare depth across the full stack of responsible AI deployment: software quality, cloud platforms, telemetry, observability, and applied AI at scale. As a former GM and Principal Data Science Manager at Microsoft, he helped build foundational systems for A/B experimentation, product telemetry, and the M360 Business Intelligence Graph. He went on to serve as VP of Cloud Platforms and Telematics at Ford and CEO of Autonomic.ai, where he led scalable data-driven innovations in connected vehicle technology. Ken is coauthor of How We Test Software at Microsoft. His upcoming book, The Lean AI Handbook, Pierson summer 2026, captures best practices for operationalizing AI at scale. He currently serves as Advisor and VP of AI at Envorso, helping enterprise clients architect responsible, scalable AI solutions that drive measurable impact.
Bob Rapp is a data scientist who began his journey in the 1980s with VR - both military and civilian. Bob has held positions at IBM (Watson) as a VP, at MIcrosoft in industry verticals with very large data sets (including telecommunications, automotive, and finance), and at GE Healthcare where he was involved in shipping the first ML models to find certain kinds of cancer. Today, Bob continues to blaze trails within AI/ML with professional curation at GM in the AI Center of Excellence.
As part of the Data Platform & Growth organization, Ravi Vedula is the leader of the IDEAS organization which provides Data, Insights, and Personalization/Growth services across E+D and Microsoft. He leads a cross-functional team of engineers, program managers, and data scientists. Ravi and team deliver data platform and services not just for E+D, but also 600+ partners across Microsoft including the strategic data services for Security/Compliance, Azure, Xbox, Dynamics, MCAPS, MCB, SLT, as well as M365 customers. Prior to IDEAS, Ravi worked for many years as a founding engineering leader within Office 365 including Exchange Online, Service Fundamentals and Modern Support.
Rebecca Norlander is co-founder of Verific, Inc., an AI-driven business compliance solution, and a software engineering executive with over 30 years of experience across enterprise and startup environments. Previously, she served as SVP of Software Engineering at HP, CEO and co-founder of Health123, and spent nearly 20 years at Microsoft in senior technical and leadership roles. A champion for diversity in technology, Rebecca serves as a Trustee of Boston University and holds a B.S. in Computer Science from BU.