* Section - ONE: Wake-up call - why you can deliver AI-grade insights in 1 quarter with your existing team; ** Chapter - 01: The analyst bottleneck and the AI dividend; ** Chapter - 02: Cost-of-hire vs cost-to-upgrade - A five-minute calculator; ** Chapter - 03: Skills thermometer - pinpointing gaps, fears & quick wins; * Section - TWO: Charting the new roles - drafting 90-day skills sprints; ** Chapter - 04: From dashboards to co-pilots - workflows that change in 12 weeks; ** Chapter - 05: Drafting tomorrow's job cards (competencies, pay bands, OKRs); ** Chapter - 06: Three team shapes that scale - start-up, mid-market, global hub; * Section - THREE: Equipping your "garage" - tech you can switch on this quarter; ** Chapter - 07: Minimal-viable data & AI stack (cloud, on-prem, hybrid); ** Chapter - 08: Buy, extend or build? A budget-minded decision grid; ** Chapter - 09: Hands-on with low code AutoML, vector search & prompt engines; * Section - FOUR: Momentum in 90 days; ** Chapter - 10: Six lighthouse projects for revenue, cost & risk; ** Chapter - 11: From business question to work model (regression, forecast, gen-AI); ** Chapter - 12: Explaining results non-quants believe - stories, visual, KPIs; ** Chapter - 13: Lightweight MLOps - deploy, monitor, iterate (No DevOps army required); * Section - FIVE: Responsible by design - training analysts to think governance; ** Chapter - 14: Plain-English governance - ten questions every analysts learns to ask; ** Chapter - 15: Bias, fairness and privacy checks anyone can run; ** Chapter - 16: Securing generative AI - RAG patterns, PII redaction, policy snippets; ** Chapter - 17: Governance simulations & table-top exercises; * Section - SIX: Keeping the fly-wheel turning; ** Chapter - 18: Defusing "robot anxiety" and sparking experimentation; ** Chapter - 19: Measuring impact - from hours-saved to revenue uplift; ** Chapter - 20: Learning loops, communities of practice & continuous upgrade funds;.