How to Evaluate AI Agent Opportunities (2026)
Quick summary: Score volume × pain × data × write-risk. Treat ~$791/mo at 50K sessions as a platform floor — not store savings. Readiness below 16/30 means do not fund writes.
Key Takeaways
- Treat ~$791/mo at 50K sessions as a platform floor — not store savings
- Readiness below 16/30 means do not fund writes
- McKinsey's State of AI 2025 found 62% of organizations experimenting with agents and 23% scaling in at least one function
- Most of the 62% are still deciding what to fund
- On June 17, 2026, AgentCore Harness reached GA (What's New)
Table of Contents
Evaluating an AI agent opportunity is not a model bake-off and not a vendor ROI slide. It is whether volume, pain, data you can join, and write-risk line up — and whether you can pay the platform floor without pretending it is savings.
McKinsey’s State of AI 2025 found 62% of organizations experimenting with agents and 23% scaling in at least one function. Most of the 62% are still deciding what to fund. This note is that filter.
On June 17, 2026, AgentCore Harness reached GA (What’s New). Cheap hosting is an input to TCO. It is not a benefit line. Agents Classic is in maintenance for new customers after July 30, 2026.
This is part 5 of AI Agents for Business. The longer scoring write-up in the field guide is AI Agent ROI: What to Automate First. The live tool is the eCommerce AI agent ROI calculator.
First-party signals we reuse (not store KPIs) — Support-style AgentCore at 50K sessions/mo ~$791/mo platform + model (decision guide). Gateway ~180 ms → ~95 ms median tool round-trip on a B2B CRM assistant (12 tools, ~8k turns/day) — Gateway post. Model your mix on the AgentCore pricing calculator. Treat ~$791/mo as a floor, not as savings.
Reproduce this — Run the ROI calculator with your ticket or order counts — not a round teaching number. Score readiness on
ai-agent-readiness-checklist.md(/30; below 16, do not fund writes). Platform TCO: AgentCore pricing calculator.
Opinionated take: kill any opportunity whose only number is a percentage with no units and no denominator. Trade-off: your first funded agent may look smaller than the vendor slide. It will have a stop rule and a cost floor you can defend.
The four questions (in this order)
- Volume — How many times does this process run per week? If you cannot count it, you cannot evaluate it.
- Pain — Does a human already do a messy first pass (tickets, a queue), or is this a formula that should stay a workflow?
- Data — Are join keys and named APIs real? Readiness /30 — assessment.
- Write-risk — Does the “win” require refund, price, or PO in week one? If yes, and the score is under 16, do not fund.
Then add platform TCO. If session volume looks like the published silhouette, plan for on the order of ~$791/mo at 50K sessions plus your model mix — not a round “AI will save 30%.”
FactualMinds is an AWS Select Tier Services Partner. We publish no agent case-study ROI. The calculators and the field-guide priority post are the artifacts.
How the live tools fit (and how they lie if you let them)
| Tool | Use it for | Do not use it for |
|---|---|---|
| ROI calculator | Relative rank of workflows you already measure | A board payback week you cannot source |
| Readiness checker | Whether ACP/UCP/catalog work is even in scope | A substitute for org /30 |
| AgentCore pricing | Runtime / Gateway / model mix | Booking the output as savings |
| Decide tree | Which one family after the score | A five-agent roadmap |
What broke — A deck that treated the ~$791/mo silhouette as money already saved, then attached write tools to “make ROI true.” Detection: finance asked for the store KPI; there was only a platform estimate. Recovery: label platform TCO as cost; keep week-one reads; re-rank with the ROI calculator on counted tickets. The silhouette source is the AgentCore vs Q decision guide.
Named substitutes
- Process already a correct template → do not evaluate as an agent — what to automate.
- High calculator score, no APIs → fund integration, not an agent.
- Two “winners” → where to start + decide tree.
- Need the field-guide scoring rubric → ROI priority post.
- Ready to buy the engagement, not another spreadsheet → eCommerce AI Agents on AWS.
If You Only Do One Thing
Put three numbers on one page: weekly volume you already measure, readiness /30, and a platform-floor estimate from the AgentCore calculator. If any cell is blank, you are not evaluating — you are hoping.
What to Do This Week
- Pick at most three candidate processes from last week’s calendar.
- Run each through the ROI calculator with real counts.
- Score the org once on the checklist.
- Fund one read-shaped opportunity, or fund readiness. Then open the service page only if you want a scoped first agent — not a fleet quote.
What This Post Doesn’t Cover
It does not invent a payback period or a ticket-deflection percentage. It does not replace the field-guide ROI rubric. It does not evaluate Amazon Q vs AgentCore — that compare already exists. Who should own the loop is build vs buy AI agents. We have not added a new first-party cost run for this note; ~$791/mo, 50K sessions, ~180→95 ms, 16/30, and McKinsey 62%/23% are the published figures we reuse.
Primary next steps: ROI calculator and eCommerce AI Agents.
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