The Confidence Gap: Enterprise AI Adoption vs. Reality

AI-powered development has delivered on its promise. Code is being written faster, at greater scale, across nearly every enterprise engineering organization. But velocity without visibility isn't progress — it's risk accumulating quietly in your pipeline.

The bottleneck in software delivery has shifted. It's no longer writing the code. It's reviewing it, testing it, governing it, and proving it delivered something worth paying for. Yet most organizations are discovering that their governance frameworks, cost controls, and accountability structures haven't kept pace with the volume AI is producing — and the gap is showing up in production.

In this session, we will unpack the data behind the confidence gap: the widening distance between how organizations feel about their AI readiness and what's actually happening on the ground. For CIOs, CTOs, and engineering leaders, the imperative isn't adoption anymore. It's control.

Walk away with a clearer picture of where the real risks live in your AI delivery pipeline, and what comes next as agentic AI moves from the edges of the SDLC to its center.