AI is no longer an experiment. It’s an expectation.

Enterprises are investing at speed, yet many are still struggling to prove value, establish accountability and scale beyond isolated wins.

The ISG AI Impact Summit focuses on what’s slowing impact including the gap between AI ambition and measurable ROI, unclear ownership in human-AI decision-making, operating models not built for autonomy and data foundations that fail under real-world pressure.

This isn’t about launching more pilots. It’s about redesigning how business gets done and delivering results that stand up in the boardroom.

WHAT YOU'LL DISCOVER

Stop celebrating efficiency. Start delivering value.

Gain a practical framework to connect AI work to real business outcomes, arm yourself with CFO-ready proof points and unlock the funding needed to scale what actually works. 

- How do you distinguish performance theater from enterprise value?
- How do you connect isolated AI wins to measurable outcomes

AI doesn’t eliminate jobs—it eliminates clarity of ownership.

Walk away with a clear governance framework for human-AI collaboration, plus decision criteria to determine when AI can act independently and when human oversight is non-negotiable.

- What does the workforce look like when the enterprise truly runs itself?
- How do you decide which decisions AI can own, which it can assist, and which must remain human-led?

AI isn't changing the price of what you buy. It's changing what you buy, and how you build.

Navigate the new landscape: GCCs versus sourcing partners, platforms versus custom builds, licensing versus consumption, and how to structure deals for an enterprise designed to operate autonomously.

- How do you structure deals and partnerships for an enterprise designed to operate autonomously?
- Are your procurement models enabling AI transformation

Your AI works in the lab. Production is a different story.

Discover what data readiness actually requires for autonomous AI, what to fix first, and how to close the gap between the data you have and the data your AI needs to act on its own.

- Is your data fit for AI-driven decision-making?
- How do you prove your data is contextualized, trusted, and ready for real-time autonomy?