Health Plans

AI is in the plan. The operating work is still stuck.

COO, VP Ops, CIO, CAIO, CDO, CMO, and UM / PA / claims leaders feel the same pressure in different places: too many AI bets, automation that still leaves labor, data that blocks the workflow, and AI that shapes consequential payer actions.

GNS-AI helps health plans Prioritize, Design, Build, Prove, and Scale what works, with Decision Control when AI shapes important actions.

Health plan operations and clinical review context
Four stuck situations.Investment. Labor. Data. Control.
Economics

Payer AI value is decided by review burden and operating conditions, not model demos.

Potential value from automation is reduced by retained full review, exceptions, rework, delay, appeals, and failure exposure. Decision Control matters when AI shapes consequential coverage or payment actions, but the economic question applies across Design, Build, Prove, and Scale.

Where plans get stuck

Four primary entry points.

Start with the stuck situation. Then pick the engagement that matches.

A · Prioritize

Which AI opportunities deserve investment?

Ideas pile up across PA, UM, claims, payment integrity, provider ops, and member ops. Capacity does not. Leadership needs a clear order of attack before more build spend.

$7,500 fixed fee | 7 business days.

Prioritize our AI opportunities
B · Build / Prove

Automation entered the workflow. Too much work remains.

Headcount, backlog, exceptions, and turnaround still move with volume. Savings stall when full review and rework grow with automation.

Stage-appropriate next step: Scoped Build, workflow automation, or Pilot Efficacy & Scale Readiness.

C · Data & systems

Data and systems are blocking the workflow.

AI cannot finish work when the data is fragmented, late, or hard to use across core systems. Integration and interoperability become the constraint.

Route through data / interop design and Scoped Build. Denodo is a verified technology partnership for data virtualization and semantic access when that fit is right.

D · Decision Control

AI is shaping consequential payer actions.

Coverage, UM, PA, and claims actions still need the right review at the right time, with a clear basis for why AI was allowed to act.

Start with a Decision Control Assessment. Persistent runtime control sits on the Decision Control Plane. Prior authorization is a proposed application.

In practice

Why payer AI requires more than a human somewhere in the workflow

Case-appropriate AI authority. Selective, substantive human review.

Substantive review

Cigna / PxDx

What happened. ProPublica reported that Cigna's PxDx system supported rapid claim denials with limited clinician time per case. Cigna has stated that physicians review claims and that the reporting mischaracterized its process.

Why it matters. Named human review is not the same as substantive review with enough context and real decision authority.

Where Decision Control could intervene. This is a point where Decision Control is designed to intervene when review is named but may not be substantive for the case at hand.

What different handling could have occurred. Cases that look routine on paper could have been routed to qualified review with enough context and authority before a denial posted.

ProPublica · Cigna response (Becker's)

Practical AI authority

UnitedHealth / nH Predict

What happened. Plaintiffs allege that UnitedHealth and naviHealth used nH Predict to cut off post-acute care in ways that overrode treating clinicians. The company states the tool guides care and clinicians make medical necessity determinations.

Why it matters. Leaders need an operational answer for how much authority an AI-shaped conclusion should receive in the particular case.

Where Decision Control could intervene. This is a point where Decision Control is designed to intervene when an AI-shaped recommendation begins to carry practical authority over care.

What different handling could have occurred. High-consequence recommendations could have been held or escalated for qualified clinical judgment before care was cut off.

STAT on UnitedHealth / nH Predict litigation

Selective automation only works when supported work can move, and when required review is substantive enough that a qualified person can change the outcome before the consequential action moves forward. Decision Control is the layer designed to decide case by case whether the next step is Proceed, Verify, Qualified Review, or Hold or Escalate.

Why now

CMS-0057-F is operating context for impacted payers.

CMS-0057-F is a federal rule on prior authorization and data sharing. Process rules generally began January 1, 2026. API rules generally begin January 1, 2027. Exact dates vary by payer type. This is timing context, not legal advice.

2026 process work

Timeframes, denial reasons, and metrics

Impacted payers generally must meet prior authorization process rules starting January 1, 2026. That includes decision timeframes for most payer types, specific denial reasons, and public prior authorization metrics (initial metrics by March 31, 2026 per CMS).

2027 API work

Patient Access, Provider Access, Payer-to-Payer, Prior Authorization APIs

Major API build and upgrade work is generally due beginning January 1, 2027. Timing varies for Medicare Advantage, Medicaid and CHIP, managed care, and QHP issuers on FFEs.

The business bridge

Electronic PA is not the same as operating value

Electronic prior authorization helps exchange data. Plans still must decide where automation removes work, where clinical review stays needed, and which AI investments pay off.

CMS fact sheet: CMS-0057-F · Prior authorization path · PA economics calculator

Other paths

Pilot and modernization sit below the four entry points.

Use these when the stuck situation above already points here.

Prioritize

AI Use-Case Prioritization Workshop

$7,500 fixed fee | 7 business days. Rank which AI opportunities deserve serious investment.

Prioritize our AI opportunities
Design

AI Initiative Review

$3,500 fixed · 5 business days. Pressure-test one AI, automation, workflow, or data initiative before more capital is spent.

See Initiative Review
Build

Scoped Build

Clear scope, integration, and handoff when the operating problem is clear enough to deliver.

See Scoped Build
Prove

Pilot Efficacy & Scale Readiness

Prove whether a pilot created enough real-world value to justify scale.

See Pilot Evaluation
Control

Decision Control Assessment

3-4 weeks · Starts at $30,000 · Typical $30,000-$45,000. Evaluate one consequential workflow before persistent Decision Control.

See DCA
Runtime

Decision Control Plane

Persistent runtime Decision Control for consequential AI workflows. Scoped.

See DCP

Which stuck situation matches your plan?

A 30-minute fit call confirms Prioritization, Initiative Review, Build, Pilot, Decision Control Assessment, Decision Control Plane, or no engagement.