AI Agent Use-Case Selection & Feasibility Scorecard
Decide which use cases are good, feasible candidates for an AI agent before you build — score 6 weighted criteria, gate on data and risk, get a GO / PILOT / PARK verdict. 4-tab Excel + guide.
One-time purchase · instant download · no subscription
Last updated 2026-06-06 — New SKU — 6-criteria weighted scorecard with the data/risk blocker rule and a GO / PILOT / PARK verdict.
AI Adoption & Governance
The operator layer for putting AI agents into production — data and process readiness, an AI governance register, an agents-in-production tracker, and AI vendor TCO. Govern the agent, don't just buy it.
Why this is operator-grade
Built by Petko Petkov — a 15-year enterprise IT operator who has sat on both the vendor-distribution and buyer-operator sides of the table. Every Vihren Labs product is built from real scenarios: real SAP T-codes, real regulation article numbers, real cutover-night failure modes. Not consultant theory — the templates the operator wished existed when the system had to work on Monday morning.
About the maker →The thinking behind it
Your AI agent will amplify your data problems, not fix them
An AI agent is an amplifier — point it at fragmented, duplicated, or stale data and it scales the confusion, fluently. Why bad data no longer looks broken but looks persuasive, why enterprise systems were never built for autonomous decisions, and the three readiness questions — identity, completeness, source of truth — to answer before you deploy an AI agent on anything that matters.
Governance, not agents: the operating model most AI programs skip
Most AI agent projects don't fail on the model — they fail on the operating model: no decision rights, no use-case gate, broken data, runaway cost, no owner after launch. Why the first question isn't 'which agent should we buy' but 'who owns this, and how do we decide', and what an AI Center of Excellence actually is — a thin function with a charter, a GO / PILOT / PARK gate, eval standards, a risk register, and run-and-maintain ownership across the agent lifecycle.
Frequently asked
What is the AI Agent Use-Case Selection & Feasibility Scorecard?
Decide which use cases are good, feasible candidates for an AI agent before you build — score 6 weighted criteria, gate on data and risk, get a GO / PILOT / PARK verdict. 4-tab Excel + guide.
How do I choose which processes are good candidates for an AI agent?
Score each candidate 1-5 on six agent-suitability criteria — task structure, data readiness, value/ROI, risk containability, build feasibility, adoption readiness — with editable weights. The workbook returns a weighted score and a GO / PILOT / PARK verdict, plus a blocker rule that forces FIX-FIRST if data readiness or risk containability is too low, so a fatal weakness cannot hide behind a good average.
How much does the AI Agent Use-Case Selection & Feasibility Scorecard cost, and is it a subscription?
$49 for a single-operator licence, or $99 for a team licence. It is a one-time purchase on Gumroad — you download it and own it, with no subscription or recurring fee.
Who is the AI Agent Use-Case Selection & Feasibility Scorecard for?
It is part of the Vihren Labs AI Adoption & Governance line. The operator layer for putting AI agents into production — data and process readiness, an AI governance register, an agents-in-production tracker, and AI vendor TCO. Govern the agent, don't just buy it.
Who builds Vihren Labs products?
Petko Petkov — a 15-year enterprise IT operator who has worked both the vendor-distribution and buyer-operator sides of the table: SAP S/4HANA migrations, master data management and governance, IT vendor procurement from the distribution side, EU regulatory rollouts, and large shared-services / GBS transitions across Europe. Every product is built from real scenarios — real SAP T-codes, real regulation article numbers, real cutover-night failure modes — not consultant theory.
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