Streamlining care journeys, reducing costs, accelerating payments, and improving outcomes across the healthcare ecosystem through the next generation of AI innovation and integration.

We are living through one of the most significant technology shifts of our time. Artificial intelligence (AI) has rapidly evolved from breakthrough innovation to everyday enterprise capability. What once felt experimental now drives real decisions across industries.

The potential for positive disruption in healthcare is extraordinary. Administrative burden can shrink. Payments can accelerate. Insights can surface earlier. Costs can be addressed before they escalate, with patients ultimately benefiting.

To understand where healthcare goes next, it helps to look at how AI has evolved.

The first wave, spanning the 2000s through the 2010s, focused on predictive models. Machine learning strengthened claims analysis, anomaly detection, risk scoring, and payment integrity. It introduced a data-driven focus into operations.

The second wave accelerated in the 2020s. Generative models demonstrated reasoning at scale and the ability to interpret unstructured information. Expectations shifted quickly. The question moved from “Can AI help?” to “How fast can we deploy it?”

Now a new wave is emerging. This wave will determine whether AI delivers incremental efficiency or system-level impact. It is not about generating content or automating isolated tasks. It is about embedded intelligence operating inside the financial and operational infrastructure of healthcare: within claims systems, within payment workflows, within compliance frameworks, and within employer cost management strategies.

Intelligence must live inside the workflow, strengthening how payers, providers, and employers operate across a complex healthcare economy. It must be secure, auditable, and accountable.

Healthcare is ready to move beyond experimentation toward intelligent execution. The organizations that lead this next wave will embed AI responsibly, at scale, to reduce friction, strengthen financial performance, and improve care and affordability for patients.

That is where real transformation begins.

THE CHALLENGE​

AI in Healthcare: High Expectations, Real-World Complexity

Healthcare presents extraordinary opportunity for AI, shaped by unique operational and regulatory complexity.

In a system defined by workforce strain and margin pressure, efficiency matters. Decisions influenced by AI affect payments, compliance, provider stability, and patient access. Applied with discipline, AI can strengthen financial performance and improve system cohesion.

AI adoption must navigate four realities:

  • Data volume and quality
  • Data protection and governance
  • Evolving policies and regulations
  • Operational complexity

 

Data Volume and Quality

Healthcare does not lack data. But it remains fragmented and difficult to reconcile across the systems used among payers, providers, employers, and others. Transparency has increased access to new data, but clarity—and ultimately improved outcomes for patients, the healthcare consumer—comes from integration.

AI creates value when it surfaces anomalies and trends early enough to influence decisions before costs escalate. In healthcare, greater transparency supports greater accuracy, and accuracy directly impacts reimbursement, compliance, and patient experience.

Data Protection and Governance

Healthcare data is among the most sensitive assets in the economy. AI operating in this environment must meet rigorous standards for security, auditability, and oversight.

Infrastructure selection is a governance decision. Models must be transparent, defensible, and aligned with federal and state requirements and laws. Responsible development and strong cybersecurity enable scale and trust.

Evolving Policies and Regulations

Healthcare regulation continues to evolve. Transparency mandates, payment reforms, and surprise billing protections introduce ongoing complexity.

Sustainable innovation requires the ability to operationalize policy at scale while maintaining compliance and consistency.

Operational Complexity

Healthcare has clear opportunities to reduce systemic friction. Administrative processes can affect quality patient care, increase costs, and delay payments. Disconnected systems create inefficiencies. Manual review slows reimbursement and the coordination of quality patient care.

AI can reduce this friction at its source, accelerating cooperation across stakeholders and strengthening affordability and access across the system.

THE NEXT HORIZON

Intelligent Execution: An Infrastructure Built for Healthcare

Healthcare leaders must prioritize AI where it drives measurable outcomes: revenue stability, cost containment, operational efficiency, and improved access to quality care. Adoption accelerates when intelligence is embedded directly into financial and care delivery workflows.

The next wave is about strengthening infrastructure. Value emerges when intelligence operates inside systems across payers, providers, and employers. This is the shift from isolated automation to ecosystem intelligence.

True impact requires workflow accessibility, cross-ecosystem reach, financial accountability, and governance discipline.

AI must function within claims adjudication, payment workflows, contracting, and reconciliation processes. Intelligence beside the system creates insight. Intelligence inside the system creates action.

Healthcare is financially interdependent. Payer and employer decisions affect providers. Provider billing affects patients’ access to care and financial well-being. Employers largely bear the cost of a broken system. Intelligence that extends across stakeholders reduces friction at scale.

Insight alone does not create value. Intelligence must translate into faster payments, fewer disputes, reduced wasteful spend, and improved quality and patient access. In healthcare, trust determines scale. AI systems that enable reimbursement decisions to be more efficient and operate on protected health information must be secure, auditable, and accountable.

Organizations positioned at the intersection of workflow access, ecosystem connectivity, financial accountability, and governance discipline will shape the next era of healthcare intelligence.

 REAL-WORLD APPLICATIONS OF EMBEDDED AI

Embedded intelligence creates value when it operates inside real workflows. Across healthcare, that means claims systems, payment operations, compliance frameworks, and employer cost management environments.

Reducing Disputes and Improving Payment Accuracy

 Billing modifier misuse frequently leads to denied and disputed claims, requiring manual review and increasing administrative cost.

Within Claritev’s payment and revenue integrity workflows, AI is a key component in analyzing structured claims data alongside clinical documentation to streamline review and reduce manual intervention, while preserving appropriate human oversight where needed.

Moving from post-pay recovery to pre-pay prevention reduces disputes and accelerates reimbursement. Embedded intelligence strengthens coordination across payers, providers, and employers.

Navigating Regulatory Complexity in Surprise Billing

The No Surprises Act introduced complex compliance requirements and increased arbitration activity. Payment disputes affect payer operations, provider revenue, and employer cost simultaneously.

Within Claritev’s negotiation and payment solutions, AI-assisted analysis generates defensible and customizable payment offers grounded in public market data.

The result is reduced manual effort, faster resolution, stronger compliance alignment, and improved financial performance across stakeholders.

Scaling Expertise Through Embedded Analytics

Employers and brokers often seek clearer visibility into cost drivers and performance trends.

Within BenInsights®, Claritev applies AI-driven models and emerging agentic workflows to translate data into actionable insight. Instead of manually calculating metrics and tracing root causes, embedded intelligence focuses on clinical and financial cost trends and emerging risk from benefit plan utilization.

Insight becomes accessible. Action becomes faster. Oversight becomes stronger across the ecosystem, and patients benefit from more timely, informed care decisions.

CONCLUSION

Moving Forward with Confidence and Clarity

 Healthcare is an interconnected financial ecosystem. Optimizing one workflow in isolation will not resolve systemic inefficiencies.

The infrastructure across payers, providers, and employers is where intelligence creates lasting impact. When embedded within this infrastructure, manual reviews decline, payment cycles accelerate, disputes decrease, and administrative costs fall. Financial predictability improves. Affordability increases. Ultimately, patients benefit.

This is how AI fulfills its promise in healthcare.

The organizations that define the next era will integrate intelligence into core workflows and align it to measurable outcomes across the system.

Embedded intelligence, applied with discipline and governance, can reduce friction, strengthen performance, and make healthcare more transparent and affordable.

That is the opportunity ahead.