Industries
Olakai for Healthcare & Life Sciences
Measure AI ROI, govern risk, and prove value across your health system and life sciences organization.
AI Is Advancing Patient Care. Measurement Makes It Scalable.
Healthcare organizations are investing heavily in AI. Over 80% of health system executives believe generative and agentic AI will deliver significant value across clinical operations, business functions, and back-office processes. AI is already automating medical coding, streamlining prior authorizations, and enabling predictive analytics for population health management.
But the governance and measurement gaps are acute. Nearly half of healthcare organizations that permit generative AI use lack governance frameworks. Only 31% actively monitor the AI systems they’ve deployed. HIPAA requires strict controls over Protected Health Information, the FDA is scrutinizing AI in clinical decision support, and over 215 state-level AI bills were introduced in 2025 alone. Without centralized measurement, healthcare organizations face a lose-lose: either restrict AI adoption and fall behind operationally, or allow it to spread ungoverned and hope no PHI breach makes the news.
By the Numbers
Nearly half of healthcare organizations using AI have no governance framework in place.
In the most regulated industry in the world, ungoverned AI isn’t just risky — it’s a ticking compliance clock.
Example KPIs for Common Agentic AI Workflows
Health systems and life sciences companies deploy AI across compliance, finance, patient retention, recruiting, and operations. Olakai gives you the KPIs to prove each workflow is delivering value while meeting HIPAA, FDA, and state regulatory requirements.
Example 1: Compliance Monitoring · Legal
Regulatory landscapes shift constantly across HIPAA updates, FDA guidance, state mandates, and new legislation, yet most legal teams learn about changes reactively. This workflow continuously monitors regulatory sources, assesses impact on operations, identifies necessary policy updates, and notifies affected stakeholders with clear action items. For health systems navigating HIPAA, FDA, and 44 states’ worth of emerging AI regulation, proactive compliance is no longer optional.
Key KPIs to measure with Olakai
Regulatory Response Time Days from regulatory change published to internal policy updated.
Compliance Gaps Identified Regulatory gaps caught proactively versus reactively.
Penalties Avoided Estimated dollar value of fines prevented through proactive compliance.
Example 2: Invoice Processing · Finance
Healthcare finance teams manage enormous volumes of invoices from medical suppliers, pharmaceutical vendors, equipment providers, and service contractors. This workflow automatically extracts invoice data using OCR and email parsing, matches invoices to purchase orders, validates amounts and vendor information, routes for approval, and updates the accounting system. Medical billing complexity makes automation especially valuable — errors can trigger costly audits.
Key KPIs to measure with Olakai
Processing Cycle Time Hours from invoice received to payment approved.
Error Rate Percentage of invoices requiring manual correction.
Cost per Invoice Total processing cost per invoice, including labor and systems.
Example 3: Churn Risk Detection · Customer Success
In healthcare, “churn” means losing provider network participants, health plan members, or key payer relationships. Each departure has cascading effects on patient access, revenue, and network adequacy requirements. This workflow monitors engagement patterns, service utilization, and satisfaction signals to flag at-risk relationships before they deteriorate, giving account teams time to intervene with tailored retention strategies.
Key KPIs to measure with Olakai
Provider/Payer Retention Rate Percentage of flagged at-risk relationships retained after intervention.
Revenue Retained per Intervention Dollar value of relationships saved by early outreach.
Network Adequacy Score Provider coverage ratio maintained through retention efforts.
Example 4: Candidate Screening · HR
Healthcare faces a persistent talent crisis, and recruiting teams are overwhelmed screening applications for clinical, administrative, and technical roles. This workflow parses resumes, matches candidate credentials to job requirements, verifies clinical certifications and licensing, ranks candidates by fit score, and schedules screening interviews. For roles requiring specific certifications, board eligibility, or state licensure, automated credential verification alone saves weeks per hire.
Key KPIs to measure with Olakai
Time to Fill Days from role opened to offer accepted.
Credential Verification Accuracy Percentage of certifications and licenses verified correctly on first pass.
Recruiter Throughput Candidates screened per recruiter per week.
Example 5: Maintenance Scheduling · Operations
Medical equipment downtime doesn’t just cost money — it disrupts patient care. MRI machines, surgical robots, infusion pumps, and diagnostic equipment must maintain near-perfect uptime. This workflow monitors equipment health metrics in real-time, predicts failures before they occur, optimizes maintenance windows to minimize patient care disruption, and coordinates with biomedical engineering teams. Predictive maintenance in healthcare means fewer cancelled procedures and better patient outcomes.
Key KPIs to measure with Olakai
Equipment Uptime Percentage of time critical equipment is operational.
Maintenance Cost per Device Total cost including parts, labor, and downtime per asset.
Procedures Preserved Patient procedures not rescheduled due to equipment failure.
Why Measurement Changes Everything
From Regulatory Lag to Proactive Compliance
Track how quickly your organization adapts to HIPAA updates, FDA guidance, and state AI regulations. Measure gap identification speed and remediation cycles rather than waiting for the next audit to find out.
From Revenue Cycle Friction to Financial Clarity
Measure invoice processing time, error rates, and cost per transaction. When you can prove AI automation is cutting days from your revenue cycle and reducing billing mistakes, the investment case makes itself.
From Retention Guessing to Network Protection
Instead of hoping churn models work, measure exactly how many providers or payers were retained, how much revenue was saved, and whether network adequacy standards were maintained through every intervention.
From Shadow AI Risk to HIPAA-Governed Adoption
Replace “block everything” with “measure and govern.” See which unsanctioned AI tools access patient data, quantify the PHI risk, and bring high-value usage into the fold with proper Business Associate Agreements and oversight.
From Talent Scramble to Strategic Hiring
Track time-to-fill and credential verification accuracy for clinical and administrative roles. When you can prove faster, more accurate hiring during a staffing crisis, recruiting becomes a measurable strategic asset.
From Equipment Downtime to Patient Care Continuity
Measure equipment uptime, maintenance costs, and procedures preserved. When you can connect predictive maintenance to patient outcomes, operations stops being a cost center and starts being a care enabler.