Pilot Efficacy & Scale Readiness

Did the AI initiative create enough value to scale?

The result is not another validation report. It is a scale decision leadership can defend: scale, narrow, redesign, keep measuring, or stop.

MEASURE
PROVE
SCALE
The problem

A good demo is not proof to scale.

Leadership needs evidence the pilot improved the outcome that matters, under real conditions, at economics the organization can support.

The cost

Scaling a weak pilot multiplies review load, exceptions, and disappointment.

The better state

A clear scale decision based on live performance, not slides.

What GNS-AI does

We evaluate the pilot on technical results, workflow fit, human workload, adoption, outcomes, economics, and scale readiness.

Evidence traps

What usually goes wrong with AI pilot evidence

Weak evidence looks strong until you try to scale it.

Wrong endpoint
Weak comparator
Poor workflow measurement
Adoption treated as efficacy
Human work left out
Exceptions and rework left out
Scale assumptions left untested
What we evaluate

Real-world efficacy, not only model scores.

We look at how the pilot behaves in the operating environment.

Technical performance
Workflow impact
Human workload
Adoption
Outcomes that matter
Economics
Scale readiness
Scale decision

Why averages are insufficient for a scale decision

FDA/CDRH highlights how changes in populations, sites, protocols, and inputs can alter AI performance after development. An average pilot result can look acceptable while hiding conditions where benefit, burden, or failure meaningfully changes.

Should the organization scale on the average result, or based on where the evidence shows the AI works under the operating conditions it will face? The scale question is therefore larger than "Did the pilot work?" It also includes where it worked, under what conditions, and what evidence supports broader responsibility.

FDA/CDRH postmarket monitoring

Public terms

Scoped to the pilot and the evidence available.

Commercial terms are confirmed on the fit call.

ScopeOne AI pilot or early deployment
TermsScoped
FocusEfficacy and scale decision
OutcomeScale, narrow, redesign, extend measurement, or stop
Different from Decision Control Assessment.

Pilot Efficacy decides whether the initiative itself should scale. Decision Control Assessment decides how much work AI should do under real conditions, and where a person still needs to step in.

A successful pilot establishes evidence of value. Decision Control becomes relevant when leadership must determine how much operating authority different cases should receive after scale.

Evaluate an AI Pilot

Bring the evaluation plan, available results, and the decision leadership needs to make.