In this third LinkedIn Live AI chat, Kelsey and Todd discuss how to define and prove AI ROI, arguing many AI projects fail due to poorly defined returns beyond simple time-savings. They distinguish AI activity from AI value, stressing goal-driven, iterative adoption and measurable milestones executives and CFOs can trust—typically cost savings (growth without headcount) or revenue impact (more leads, faster launches, higher win rates). They walk through ROI approaches for practical scenarios including SOP creation and searchable copilots, marketing email HTML generation, new-hire self-serve process help, AI-assisted RFP drafting, job descriptions and onboarding templates, automated revenue-report narratives, customer success call recaps, contract review prep, and meeting-to-action-item pipelines, emphasizing reduced rework, fewer dropped tasks, b ...