Mercer: AI and Healthcare Stand Out as Bright Spots Across Public and Private Markets

AI + Healthcare: Where Operators and Investors Can Create Real Value Next

Even with choppy markets, healthcare doesn't pause. Demand is steady, costs are rising, and artificial intelligence is moving faster than most roadmaps. That mix creates specific opportunities in both public and private markets-especially in unlisted infrastructure and early-stage ventures-if you know where to look.

This is a practical playbook for healthcare leaders, clinicians, and investors who want signal over noise.

Why this moment matters

• Uncertainty is the baseline, not the exception. Reimbursement pressure, labor shortages, and margin compression are a given. Capital will move to any solution that frees capacity and reduces unit costs.
• AI has crossed the "pilot purgatory" line in several workflows (ambient documentation, prior authorization prep, revenue cycle, imaging triage). Proven ROI is replacing hype in these areas.
• Infrastructure is the backbone. More models, more data, tighter latency, stricter privacy. That points to investment in compute, connectivity, data plumbing, and security close to the point of care.

Where the value pools are forming

• Unlisted infrastructure: Regional data centers near hospital clusters; private fiber and secure edge compute; medical cold-chain and lab logistics; privacy-preserving data platforms across health systems.
• Caret at home, care out of hospital: Hospital-at-home logistics, remote monitoring hubs, dispatch networks, and partnerships that blend clinical teams with virtual-first services.
• Workflow AI for providers: Ambient clinical documentation, coding assistance, claims and denials automation, capacity forecasting, and staffing optimization.
• Life sciences enablement: Patient matching and trial acceleration, site enablement, synthetic data generation, protocol optimization, and safety signal detection.
• Security and compliance: Identity, zero trust, data de-identification, audit trails, and model observability purpose-built for HIPAA environments.

Public markets: angles that still have room

• Managed care and payer-tech with clear levers for medical cost management and back-office automation.
• Medtech and imaging where narrow AI narrows turnaround times and increases throughput.
• Data center and connectivity plays supporting healthcare latency and privacy needs.
• Cloud and software vendors with referenceable outcomes in provider/payer accounts (not just demos).

Sanity checks: durable margins, vendor concentration risk, and the ability to ship behind the firewall. Multiple expansion without operating leverage won't hold.

Private markets: where to deploy and why

• Early-stage venture: Ambient documentation, coding automation, bedside tools for nurses, RAG-based clinical reference, care-at-home orchestration, and trial tech. Seek real-world integrations, not sandbox wins.
• Growth equity: Platforms with multi-product expansion into provider and payer adjacencies, proven integrations with EHRs, and clear payback (< 12 months).
• Unlisted infrastructure: Regional compute and storage, secure data exchanges, and last-mile connectivity that meet PHI requirements.
• Private credit: Lending to PE-backed provider platforms and medtech firms with recurring revenue tied to automation outcomes.

Operator playbook: 90-180 days

• Pick 3-5 workflows with line-of-sight ROI: ambient clinical documentation; denial prevention; prior auth packet assembly; referral triage; predictive staffing.
• Stand up a lean AI governance board: clinical safety lead, privacy and security, operations, and finance. Keep approvals fast and auditable.
• Data plumbing first: identity resolution, consent tracking, PHI boundary management, and a standard for de-identification/pseudonymization.
• Vendor diligence checklist: on-prem/VPC options; HIPAA BAAs; model provenance; bias and drift monitoring; rollback plan; cost per task, not per seat.
• Payment clarity: map each use case to reimbursement, care quality metrics, or hard-cost savings-before you buy.

Compliance and safety: non-negotiables

Clinical risk and privacy can't be an afterthought. Lock these down upfront and you'll move faster later.

• HIPAA guardrails, role-based access, immutable logs, and breach response rehearsals. See Office for Civil Rights guidance here.
• For AI in clinical decision support or SaMD, track labeling, real-world performance, and change control. FDA resources are here.

What to fund now vs. later

• Fund now: ambient scribing; denials/claims automation; imaging triage and quality checks; staffing and capacity forecasting; patient access optimization.
• Position for later: digital twins for operations; longitudinal care orchestration across sites; advanced CDS in narrow specialties with rigorous governance; hospital-at-home logistics with payer alignment.

Metrics that prove it's working

• Clinical time back: minutes saved per visit, after-hours charting reduction.
• Financial lift: denial rate, days in A/R, cost per claim, documentation accuracy.
• Access and quality: time-to-appointment, readmissions, throughput, guideline adherence.
• Model health: drift, hallucination rate for defined tasks, escalation frequency, error severity.

Common failure modes (and easy fixes)

• Pilots without owners: assign a P&L leader and a clinical sponsor from day one.
• Shiny tools without plumbing: standardize identity and consent before scaling vendors.
• Seat licenses over task outcomes: pay per task completed or per claim touched. Track cost per task monthly.
• No rollback plan: always keep a human-first fallback and a clear stop-loss condition.

For teams upskilling fast

If your clinicians, revenue cycle teams, or data staff need structured training on practical AI workflows, here are curated paths you can start this week:

• AI courses by job function for targeted, role-based learning.
• AI certification for data analysis to sharpen operational analytics and decision support.

Bottom line

Healthcare's next gains come from doing simple things consistently: fix the data pipes, target a few high-ROI workflows, and fund the infrastructure that keeps PHI safe and models stable. Public markets will reward operating leverage. Private markets will prize integrations and outcomes over hype.

Opportunities are real-especially in unlisted infrastructure and early-stage venture-but they belong to teams who can show measurable impact, not just big promises.