Healthcare’s Next Phase of AI: Precision, Integration, and Explainability

Published in Healthcare Business Today authored by Siva Namasivayam, chief executive officer at Cohere Health

Overview:

In a new article for Healthcare Business Today, Cohere Health CEO Siva Namasivayam explains how healthcare is entering a new era of precision driven by real-time decision-making, transparent and domain-specific AI, and proactive processes that connect care planning to payment accuracy. As the gap widens between the speed of care delivery and administrative decision-making, health plans are facing increasing industry pressure to modernize.

Siva discusses how true transformation requires more than automating slow, manual legacy processes. The plans that will lead the next phase of healthcare are boldly embracing enterprise transformation by adopting domain-specific, clinically trained AI and moving decision-making earlier to reduce downstream costs and friction. The article highlights a broader industry shift from isolated point solutions to end-to-end intelligence that unifies utilization management, inpatient review, and payment integrity.

Key themes covered:

1. Healthcare is catching up to real-time expectations

• Patients and providers increasingly expect real-time experiences similar to other industries.
• Health plans are turning to AI-powered automation to reduce delays, administrative burden, and rework.
• Real-time operations require connected insights so care approvals directly inform payment determinations.

2. Domain-specific AI is taking the lead over general-purpose models

• Generic LLMs lack the clinical nuance, policy context, and transparency required for safe healthcare decision-making.
• Purpose-built, clinically trained AI is becoming essential for UM, inpatient review, and payment integrity.
• Precision and explainability are critical to avoid delayed care, provider abrasion, and inaccurate payments

3. Glass-box AI is becoming the new standard

• Health plans are prioritizing transparent, auditable AI over opaque systems.
• Providers expect visibility into decision logic to reduce friction and unnecessary appeals.
• Transparent AI supports compliance, oversight, and defensible decision-making across the care and cost continuum.

4. Shifting left: prevention instead of recovery

• Plans are moving from retroactive post-pay recovery to smarter, proactive decision-making.
• Earlier access to clinical evidence improves accuracy, reduces unnecessary spend, and minimizes disputes.
• Configurable AI agents help scale complex reviews so auditors focus only on true exceptions.

5. Breaking down silos for enterprise-wide impact

• Fragmented UM, inpatient review, and payment processes create duplicative work and provider frustration.
• Health plans are increasingly aligning workflows and insights across the care and cost continuum.
• Clinically trained AI, paired with expert human oversight, enables consistent, evidence-backed decisions at scale.

Read the original article