The cost
Delay, uneven review, and weak records grow while the workflow scales.
Decision Control Assessment
Find where AI can do more work without making review, risk, or accountability worse.
A bounded 3-4 week assessment of one consequential workflow. Determine where AI responsibility can expand, where verification or qualified judgment still belongs, what the operating economics look like, and whether persistent Decision Control is warranted.
ASSESS
DECIDE
CONTROL
DECIDE
CONTROL
The problem
Review is rising. Authority is still unclear.
AI already influences important actions. Leaders still cannot say where AI should do more work and where a person must remain in the loop.
The better state
A clear control answer for one workflow, with a path to pilot or implementation if needed.
Why GNS-AI
We combine operating workflow work with Decision Control design. Policy and qualified people keep final authority.
What we examine
One consequential workflow, end to end
Map how AI-shaped outputs are relied on, where review and rework accumulate, where oversight enters, what the operating economics look like, and whether the review process gives qualified people enough context and authority to exercise meaningful judgment.
Where AI can do more
Cases and steps where operating evidence supports expanded AI responsibility without making review, risk, or accountability worse.
Where people step in
Points where verification, qualified judgment, hold, or escalation still belongs with a person.
Operating economics
How review burden, exceptions, delay, and failure exposure change realized value as AI responsibility expands.
Control warrant
Whether persistent Decision Control is warranted for this workflow, or whether a narrower next step is enough.
What leadership receives
A decision package for one workflow
Expand AI work, tighten human steps, keep measuring, or move toward Decision Control Plane™.
Workflow and decision map
How work moves, where AI shapes consequential actions, and where authority currently sits.
Control findings
Where Proceed, Verify, Qualified Review, or Hold or Escalate belongs under the conditions that actually exist.
Operating economics
A clear view of review, verification, exception, delay, and failure exposure tied to the AI-shaped unit of work.
Recommended path
A bounded next step: expand, tighten, keep measuring, run Shadow Mode, or move toward persistent Decision Control.
Illustrative output
What an executive decision package can look like
Illustrative synthetic assessment output. Not a customer result.
Workflow / decision point
Prior-authorization medical-necessity recommendation for outpatient imaging. AI proposes approve, deny, or request more documentation before the case becomes an operational action.
Executive finding
AI can safely handle more routine approvals when documentation is complete and criteria are stable. Incomplete charts and edge criteria still create review burden and appeal exposure if treated the same way.
Proposed handling
Proceed on clear, complete routine cases. Verify when key evidence is missing. Route qualified review for edge criteria. Hold or escalate when the recommendation would create member, provider, or regulatory exposure.
Review / economic implication
Expanding AI only on clear cases can reduce full-review volume without shifting every exception into the same queue. The economic gain depends on keeping verification and qualified review matched to the remaining hard cases.
Leadership recommendation
Pilot expanded AI handling on the clear-case subset, measure appeal and rework rates, and decide whether persistent Decision Control is warranted before broader rollout.
How the engagement runs
Week 1 through Week 4
Public terms: 3-4 weeks | Starts at $30,000 | Typical $30,000-$45,000.
Week 1
Scope one consequential workflow. Confirm systems, roles, decision points, and the operating question leadership needs answered.
Week 2
Map the workflow and decision path. Identify where AI shapes actions, where review enters, and where evidence or authority is thin.
Week 3
Pressure-test control options and operating economics. Distinguish where AI can expand from where verification or qualified judgment must remain.
Week 4
Deliver findings and the recommended path. Decide whether persistent Decision Control is warranted, or what narrower next step fits.
What becomes concrete
The kinds of questions this assessment makes concrete
Bounded work on one consequential workflow. Clear enough to decide where AI can do more and where a person must remain.
Verification
When should stronger verification enter before an AI-shaped conclusion becomes action?
Operating conditions
When should the same AI receive different handling because its operating conditions have changed?
Human judgment
When is a human truly exercising independent judgment?
Reference points
NIST AI RMF frames AI risk management as a continuous lifecycle, not a one-time approval. FDA/CDRH work on AI-enabled devices highlights how operating conditions can change after deployment.
NIST AI Risk Management Framework · FDA/CDRH postmarket monitoring
Public terms
One workflow. Bounded enough to budget.
Public terms for the Decision Control Assessment.
Buyer view
Clear enough to decide.
One workflow. One problem. A clear next move.
What workflow
One consequential AI-influenced workflow you name.
What problem
Review is rising, authority is unclear, or leaders cannot explain why AI was allowed to act.
What you receive
Where AI can do more work, where a person still needs to step in, and a path forward.
What decision after
Expand AI work, tighten human steps, keep measuring, or move toward Decision Control Plane™ when justified.
When this is not the right start.
If the question is whether a pilot worked well enough to scale, start with Pilot Efficacy & Scale Readiness. Pilot Efficacy decides whether the initiative should scale. The Assessment decides where AI can do more work and where a person still needs to step in.
Discuss a Decision Control Assessment
Bring one consequential AI workflow. We will confirm whether the Assessment is the right next step.