Moative healthcare
$4.5 trillion. 17 activities. One thesis for each.
Healthcare moves every dollar through 17 distinct activities, from the moment a patient registers to the final collection call. Each activity has its own margin structure, its own AI exposure, and its own trajectory. We mapped the full profit pool, projected the 24-month shift, and wrote a thesis for each one.
The value does not disappear from healthcare. It migrates. The question is whether you see where before your competitors do.
The Moative healthcare thesis
Healthcare profit has concentrated in pattern-matching activities for two decades. Claims adjudication runs at 18% margin. Denial management runs at 20%. Charge capture at 15%. All three involve reading structured input, applying rules, and producing structured output. AI does each of those things faster, cheaper, and without fatigue.
The activities that justified their margins through complexity are the activities most exposed to displacement. Complexity created the margin. AI dissolves the complexity. Complexity created the margin. AI dissolves the complexity. The margin migrates.
Margin escapes administrative overhead for clinical decision-making. When machines solve routine complexity, humans solve diagnostic complexity.
The healthcare profit pool
Revenue share and margin concentration across 17 healthcare activities. Bar width = revenue share. Bar height = operating margin. Color = player concentration.
Three views of the same shift
Start here
The profit pool→
Interactive visualization of 17 activities by revenue, margin, AI impact, and key players. See where the money sits today and where it migrates over 24 months.
The 24-month timeline→
Which activities to rebuild first, why the order is causal, and where the margin compounds. Sequenced by readiness, dependency, and impact.
The thesis→
Moative's opinionated position on which activities gain, which lose, and who captures the difference. Not a survey of use cases. A position on where value lands.
Displaced activities
Where AI automates the core function
Claims processing→
Submission, adjudication, denial management. 5.5B claims/year, $262B initially denied. AI auto-adjudicates routine claims.
Revenue cycle management→
The end-to-end cycle: 17 handoffs from registration to collection. AI compresses the routine workflow to exception-only review.
Benefits verification and prior auth→
The $35B bottleneck. AI reads plan documents faster than humans. 80%+ of verifications become zero-touch within 3 years.
Medical coding→
The bridge between clinical care and revenue. AI reads documentation and suggests codes at 95%+ accuracy. Coders shift to auditing.
Patient billing and collections→
The last mile of revenue. Patient out-of-pocket is 30-35% of provider revenue. AI prioritizes by propensity to collect.
Accelerated activities
Where AI expands what the human can do
Clinical documentation→
Ambient AI captures the encounter. Physicians reclaim 1-2 hours/day. The scribe becomes the auditor. Highest satisfaction AI use case.
Care coordination→
AI identifies high-risk patients early, predicts readmissions, automates care plans. Panel sizes increase 2-3x under value-based care.
Scheduling and patient access→
15-25% no-show rates, 75-85% utilization. AI predicts, backfills, and enables self-service booking. Empty slots become revenue.
Clinical decision support→
From alert fatigue (90% override rate) to contextual, patient-specific guidance. A 5-7 year trust curve, not a 2-year deployment.
Quality and compliance→
Quality scores now swing 2-9% of Medicare revenue. AI turns retrospective chart abstraction into real-time gap detection.
Augmented and compressed
Where AI changes the equation differently
Care delivery→
The one activity AI assists but does not replace. Diagnostic support, staffing optimization, virtual care. The margin impact is indirect: better documentation downstream means better coding means higher reimbursement.
Patient engagement→
AI drops cost per patient touch from $8 to $1.20. But as every provider adopts the same tools, competitive advantage vanishes. The moat is data ownership captured early.
Work with Moative
A principal reads every brief. A thesis is already written for your segment.
We arrive with a point of view on where AI rewrites healthcare economics. The profit pool is mapped. The timeline is sequenced. The question is which activities to rebuild first in your organization and who captures the margin that migrates.
Talk to a principalCommon questions about AI in healthcare
How is AI used in healthcare?
AI impacts healthcare across 17 distinct value chain activities. Eight face displacement (claims, coding, verification, collections). Five get accelerated (documentation, coordination, scheduling, quality, decision support). One is augmented (care delivery). One faces margin compression (patient engagement). The impact varies by activity, not by technology.
What is a healthcare profit pool?
A profit pool maps total industry profit by activity rather than by company. It shows where margin concentrates across the value chain. Claims adjudication captures 18% margin on 15% of revenue. Care delivery runs at 6% on 35% of revenue. The framework comes from Bain; Moative applies it specifically to healthcare AI displacement.
Which healthcare activities will AI displace first?
Benefits verification and prior authorization are first. Both are pattern-matching functions where AI is production-grade today, with low clinical risk. Claims processing, medical coding, and payment posting follow within 12 months. Clinical decision support takes 5-7 years because it requires physician trust.
What does healthcare AI cost to implement?
Ranges from $200-500/provider/month for ambient documentation to $50K-500K for enterprise RCM automation. ROI timelines vary: prior auth automation pays back in 2-4 months. Clinical decision support takes 12-18 months. The total addressable value across all 17 activities is $388B in operating profit.
How does Moative approach healthcare AI?
Map the value chain first. Write a thesis for each activity: who gains margin, who loses it, on what timeline. Start with the profit pool (where the money sits), sequence the AI shift (what order to rebuild), and deploy activity by activity. Principals write the thesis. The pod builds the system.
Is AI going to replace healthcare workers?
Care delivery stays human. The physician-patient encounter does not get automated. What changes are the administrative activities: coders become auditors, claims examiners become fraud analysts, auth specialists become exception handlers. Net headcount may shrink, but the remaining roles require more judgment.