AI Adoption & AI Agents Operating Playbook — Pipeline to Production
Most organisations do not have an AI problem. They have twenty half-built pilots and zero production systems — scattered enthusiasm with no pipeline. This is an operating playbook for adopting AI deliberately: which use cases to pursue, in what order, sourced how, and how to run AI agents in production once the demo is over. Built by a 15-year enterprise IT operator — practical, vendor-neutral, no hype. ─── WHAT'S INSIDE ─── THE HANDBOOK (15-page PDF): ✦ Why AI adoption, why now — the real pressures, and the real failure mode ✦ The AI use-case pipeline — Idea → Qualified → Pilot → Scaling → Live ✦ Prioritising use cases — scoring on value, feasibility and risk ✦ Build, buy, or embedded — sourcing the capability without over-building ✦ The pilot-to-scale path — designing pilots that actually decide ✦ AI governance — proportionate guardrails before the gas pedal ✦ The operating model for AI agents in production — ownership, boundaries, monitoring, escalation, cost ✦ The seven failure modes — how AI programmes actually fail THE AI ADOPTION WORKBOOK (Excel, 7 working tabs): ✦ Use-Case Register — score every AI use case on value × feasibility × risk → auto-priority, with a pipeline stage + owner ✦ Dashboard — pipeline by stage + by sourcing + KPIs, with a chart; updates live from the register ✦ Pilot Scorecard — prove each use case in a bounded pilot (metric → baseline → target → Scale / Iterate / Park) before you scale ✦ AI Governance Register — risk tier, controls, human oversight, owner and review cadence per use case ✦ Agents in Production — boundaries, human checkpoint, monitoring, escalation and cost for every live agent ✦ Lookups — the controlled dropdown lists (stage / type / sourcing) ─── WHO IT'S FOR ─── → CIOs, IT directors, transformation leads, heads of operations → Anyone asked "what's our AI plan?" who needs a real answer, not a slide → Operators who have to move AI from demo to production and keep it running ─── HOW IT WORKS ─── 1. Purchase → instant download 2. Read the 15-page handbook (PDF — any device) 3. Open the AI Use-Case Register in Excel, Google Sheets, Numbers or LibreOffice and run your own pipeline ─── A WORKED EXAMPLE ─── A CIO is asked by the board for "our AI plan." Instead of a slide, they open this playbook and register: 1. They run a workshop and capture 18 candidate use cases in the AI Use-Case Register. 2. Each is scored on value, feasibility and risk — the register ranks them, and a support-ticket-triage case and an invoice-data-extraction case rise to the top while three flashy demos fall. 3. The playbook's pilot-to-scale path turns the top two into time-boxed pilots with a defined go/no-go metric — and the production operating model (ownership, monitoring, escalation) is set before anything goes live. By the next board meeting the answer to "what's our AI plan?" is a ranked pipeline and two funded pilots — not enthusiasm. ─── FAQ ─── Q: What do I need to open it? A: A standard PDF reader for the playbook; Excel, Google Sheets, Numbers or LibreOffice for the register. No macros. Q: Is it an instant download? A: Yes — both files immediately after purchase. One-time payment, no subscription, no DRM. Q: Can my team use it? A: The single license covers one reader; the team license covers up to 5 within one organisation. Q: Will I get updates? A: Yes — buyers get future revisions free, re-downloadable from Gumroad. Q: Is this consulting or legal advice? A: No. It's an operating playbook and a planning tool. AI regulation is evolving fast — validate data-handling, transparency and risk obligations with qualified legal and compliance advisors for your jurisdiction. Q: Is this tied to a specific AI vendor or model? A: No — it is deliberately vendor-neutral. It is about how to choose, pilot, govern and operate AI use cases and agents, whichever models or tools you end up using. ─── GUARANTEE ─── If this isn't what the listing describes, email hello@vihrenlabs.com within 14 days and I'll make it right or refund you. I'd rather fix the problem than keep an unhappy buyer.
Get it → vihrenlabs.gumroad.com