ACORN FIELD GUIDE · AI ECONOMICS
AI Value Recovery: Find the Cost, Latency and Workflow Waste You Can Actually Fix
AI spend can grow while business value stays unclear. The answer is not to promise arbitrary savings. It is to find one consequential workflow, establish a measurable baseline, identify the bottleneck, and test a bounded intervention.
A practical Acorn method · No invented benchmarks · Human authorization retained
1. Start with a real workflow
Pick one workflow that is expensive, slow, unreliable or blocked. Define the business outcome, who depends on it, and where a human must approve consequential actions.
2. Measure before optimizing
Establish a dated baseline for cost per task, latency, quality, failure rate, manual rework and operational impact. Separate measured facts from estimates and assumptions.
3. Compare the whole system
Evaluate models, providers, prompts, retrieval, routing, compute, data access and human handoffs together. The lowest model price alone does not prove the lowest total cost or the best result.
4. Rank recoverable value
Estimate potential savings or throughput improvements, confidence, implementation effort, dependencies and downside risk. Prefer a small, reversible test when the evidence is uncertain.
5. Keep execution governed
Prepare an intervention plan with acceptance criteria, rollback conditions, evidence capture and a named human decision point. Detecting an opportunity does not authorize a change.
6. Prove the result
Compare the same measures before and after, document changes in workload and conditions, and reconcile the measured outcome with the original hypothesis. Do not claim savings that were not observed.
Start with one five-day value recovery sprint
The AI Value Recovery Sprint is designed to identify the top opportunities, define the baseline and prepare a human-reviewed go/no-go decision. Starting price: US$2,500; scope and payment availability must be confirmed before a binding engagement.
Explore the Value Recovery Sprint ↗