Make the reduction permanent at the next contract renewal, six weeks from now.
Fictional worked example
AI works, but the supplier reduction is not yet supported
A regulated financial-services organisation has materially reduced standard document-review work with AI. Management proposes cutting external supplier capacity by 50% at the next renewal. The Stress Test finds that the technology case is promising, but the permanent supplier decision is ahead of the evidence.
"AI is working" does not require leadership to accept an unevidenced supplier reduction.
Decision at a glance
The case supports more evidence before it supports a permanent supplier band.
Supplier work, internal review, exceptions, controls and rework have not yet been measured together well enough to establish the complete net workload change.
Keep the current commitment temporarily, close the specified evidence gaps and return to the blocking Q1 analysis before the bridge expires.
The proposed 50% band is ahead of the evidence.
Evidence behind the case
AI productivity is real. The permanent supplier-capacity number is not.
Observed evidence
- Standard document-review hours are 46% lower.
- Automated document classes represent approximately 58% of normal supplier workload, but a smaller share during remediation periods.
- Reported supplier hours are approximately 35% lower on average since deployment.
- Multilingual, high-risk and exception work remains largely human-reviewed.
- No major regulatory-remediation event has occurred during the three months of AI operation at scale.
- Complete exception, secondary-review, rework and internal-team workload has not yet been measured together.
- Deeply reduced supplier capacity could take approximately 4-6 months to restore.
Economics and remaining assumptions
50% band annual saving
≈ £2.4m
Three-month bridge cost
≈ £0.6m foregone saving
AI operating at scale
3 months
Supplier restoration lead time
≈ 4-6 months
Assumptions still carrying the proposal
- Current AI performance persists.
- Multilingual automation expands successfully.
- Average-period utilisation represents future demand.
- Half the current commitment can absorb remediation peaks.
- Internal teams will not absorb material additional work.
- Lost supplier capacity can be restored quickly enough if required.
The capacity bridge at the stopping point
The bridge stops at net human work change.
AI productivity is established. Complete net human work change is not, so released capacity and the later bridge stages are not derived.
AI productivity
AI has materially reduced human review of standard documents.
Net human work change
Not yet established across the complete workflow. Supplier work, internal review, exceptions, controls and rework have not yet been measured together well enough.
Stop after Q1
Released capacity is not yet established
The stopping point
The analysis stops at Q1.
The remaining evidence defines what must be collected before the analysis can resume. It is not completed Q2, Q3 or Q4 analysis.
How much human work is actually no longer required?
Not yet established across the complete workflowStandard document-review hours are 46% lower, but that is not yet equivalent to a 46% reduction in total human work. Remaining work includes multilingual and high-risk cases, exceptions, secondary review, rework, controls and work potentially transferred to the internal team.
AI has clearly removed meaningful human effort. The complete net
human work change across supplier and internal capacity is not yet
known.
Stop after Q1
Released capacity is not yet established. Q2, Q3 and Q4 are not
responsibly reached.
Stress Test conclusion
Require specific evidence before structural approval.
The Stress Test does not reject the AI workflow or conclude that supplier capacity cannot be reduced. It finds that the current evidence does not establish how much supplier capacity is genuinely available for permanent reduction.
Evidence bridge ≠ indefinite delay.
Use the three-month extension only for the specified evidence work, assign
clear owners and set the return decision before the bridge expires.
What could change the answer
Close five evidence gaps, then return to the structural decision.
Evidence required
- Net human workload across the complete AI-enabled process, including internal review, exceptions, controls and rework.
- Supplier utilisation under normal and peak/remediation conditions.
- Minimum external capacity required for multilingual, high-risk and exception work.
- Contractual and economic consequences of realistic reduction bands.
- Restoration lead time, cost and procurement requirements.
Bridge controls and return point
- Assign an owner to each evidence item.
- Agree a peak-capacity simulation if a real remediation event does not occur during the bridge.
- Obtain supplier pricing and restoration terms for realistic bands.
- Do not turn the three-month bridge into an open-ended extension.
- Return before the bridge expires with evidence sufficient to establish the complete net human work change.
- Resume from Q1, then proceed through Q2 and Q3 as the evidence allows.
What this example shows
A real productivity result can still be insufficient for a permanent supplier decision.
AI productivity is real
supplier workload appears lower
complete net-work change is not yet known
STOP before released capacity is derived
50% is unsupported
do not invent a compromise percentage
name the evidence required and return to the decision
The failure is not that AI has not worked. The missing link is the evidence from AI performance to permanent supplier capacity.
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