Connect an AI use case to a measurable business outcome

Map how an AI use case translates from a task improvement into a business outcome, and how we'd prove it. The AI use case: [WHAT AI does - e.g. "drafts first responses to support tickets"] The workflow it sits in: [DETAILS] Current baseline numbers, if known: [e.g. handle time, backlog, error rate, cost - or "unknown"] Business goals this should support: [GOALS] Who needs convincing: [e.g. my manager, finance, leadership] Build the value chain in five links, and for each give the mechanism and a metric: 1. Task - what gets faster, better, or cheaper (e.g. draft time per ticket). 2. Workflow - how the end-to-end process changes (e.g. time to first response, backlog). 3. Operating - capacity, cost, throughput, or quality at team level. 4. Customer or stakeholder - satisfaction, retention, speed, accuracy they experience. 5. People and financial - workload, engagement, revenue, cost avoided. For each link, state the assumption that must hold for the value to pass to the next link (e.g. "freed time is used on the backlog, not absorbed"). Return: 1. A value chain table: Link | What changes | Metric | Baseline | Target | Assumption. 2. The weakest link - where value is most likely to leak - and how to protect it. 3. A measurement plan: what to track, how often, who owns it. 4. A 4-sentence summary of the business case I can paste into an email or slide. Use [ADD BASELINE] wherever I haven't given a number. Do not invent figures or benchmarks.