AI Adoption Solved. ROI Is Not.

About this session

AI adoption is no longer the hard part; proving what it changed is. Engineering teams are now running AI-native software factories where tokens, agents, prompts, pull requests, incidents, reviews, and rework all move through different systems, while finance is asked to approve bigger AI budgets with little evidence of return. In this talk, I will show how to evaluate AI investment through work evidence: which AI activity reached shipped software, which work created leverage, and which spend became rework, overhead, or waste. We will use patterns from Faros' 2026 AI Engineering Report, based on two years of data from 22,000 developers and 4,000+ teams, to explain why adoption and throughput are not the same as ROI. Attendees will leave with a practical framework for tying AI dollars to shipped work, setting ROI guardrails, and continuously monitoring whether AI is creating capital or compounding waste. If you are accountable for AI investment and need a sharper answer than "we bought more tools," this session is built for you.