What do healthcare providers and payers have in common? Both encounter rising costs, staffing shortages, compliance challenges and changing consumer expectations.
Take increasing expenses, for example. The average overhead for today’s medical practice ranges from 60 to 70 percent, with annual expenses estimated at between $600,000 and $800,000. That number indicates an average year-to-date increase of 11.1 percent in 2025 compared to 2024. PwC projects the medical cost trend for 2026 will be 8.5 percent for group plans and 7.5 percent for individual plans.
Administrative burdens impact both payers and providers, too. Compliance is one of the biggest administrative burdens for payers, while prior authorization (PA) inundates providers.
The proliferation of artificial intelligence (AI) adoption is another facet healthcare payers and providers have in common. Roughly two-thirds of physicians report using AI, and a McKinsey & Company survey found that 85 percent of respondents, including healthcare payers, are exploring or already using the technology.
Approximately 70 percent of health plans are prioritizing agentic AI for utilization management, PA processes and claims management. According to McKinsey analysis, for every $10 billion of payer revenue, AI solutions could save $150 million to $300 million in administrative costs, save $380 million to $970 million in medical costs and increase revenues by $260 million to $1.24 billion.
AI: Reshaping Payer Operations
Skyrocketing administrative costs, PA backlogs and shifting member expectations continue to alter the healthcare payer industry. However, the impact of AI is showing up through lower administrative overhead, faster claims and PA decisions, better fraud detection and higher member engagement. Perhaps the best part is that conversational AI is delivering fast and accurate support without burning out payer staff.
Member and Provider Support
Many healthcare payers rely on call centers with limited hours and long wait times. Conversational AI provides 24/7, multilingual support across Medicare, Medicaid and commercial lines, offering consistent responses to complex coverage questions. AI agents handle a wide range of common tasks, including:
- Explaining benefits and cost sharing
- Finding in-network providers and checking claims status
- Guiding members through enrollment and appeals
The multilingual capabilities of agentic AI are especially important for diverse populations with limited English proficiency (LEP). Plus, the technology frees human agents to focus on more complex tasks.
Claims Adjudication and Denial Reduction
It’s not unusual for traditional claims processes to result in manual errors, which increase denials and delays for both payers and providers. AI streamlines this process using natural language processing (NLP) and optical character recognition (OCR) to automatically extract data from various forms of medical documentation. Agentic AI performs real-time validation of diagnosis and procedure codes against payer rules, auto-suggesting corrections and flagging potential denials before they occur.
Almost 70 percent of healthcare providers using AI in claims report reduced denials or improved resubmission success. AI also enables risk-prioritized audits, enabling human experts to focus on more complex claims.
Prior Authorization and Utilization Management
On average, it takes ten days to verify prior authorization. AI centralizes plan-specific medical necessity criteria, documentation requirements and escalation pathways in a single interface to auto-classify requests, extract clinical details from attachments and match them to evidence-based guidelines for rapid recommendations. Auto-matching to necessity criteria facilitates instant approvals for routine imaging, and transparent tracking reduces follow-up calls from healthcare providers.
Turnaround times for PA decrease from days to hours or minutes for low-risk services, improving patient access while reducing avoidable inpatient admissions. AI can also identify patterns where certain services or providers consistently meet criteria, prompting “gold carding” that further reduces administrative burden.
Fraud, Waste and Abuse Detection
It’s estimated that fraud, waste and abuse cost the United States healthcare systems anywhere from $250 billion to $800 billion annually. Powered by AI, machine learning models analyze vast claim datasets, pharmacy records, and prior-authorization histories to detect anomalies that traditional approaches miss.
Predictive analytics flag suspicious activity in near real time, enabling proactive intervention before large sums are paid and providing advantages such as:
- Explainable audit trails that support investigator oversight
- Network-level detection identifying collusion among providers, patients and pharmacies
- Proactive flagging that shifts the model from reactive to preventive
Member Engagement
AI identifies practical barriers, such as transportation, childcare and language, that prevent members from accessing care and triggers automated interventions based on individual member profiles. Agentic AI powers omnichannel outreach campaigns across email, SMS, app notifications and automated voice calls, nudging members to close care gaps, refill medications, or attend follow-up visits. Examples include:
- Diabetes management: Reminders with glucometer integrations
- Maternal health: Prenatal and postpartum outreach with transport vouchers
- Post-discharge: AI-scheduled follow-ups reducing readmission risk
Advantages of AI for Healthcare Payers
AI is a competitive necessity for payers facing small operating margins and high member expectations. That’s why payers investing in it procure measurable value that distinguishes them from competitors.
Operational Efficiency and Cost Reduction
AI automates scheduling, documentation and generation of billing reports. McKinsey & Company estimates that, by using AI, payers could see net savings of 13-25 percent in administrative costs and five to 11 percent in medical costs as well as three to 12 percent higher revenue.
Digital Front Doors
AI-driven platforms provide cost transparency, preservice coordination and personalized health guidance, all of which are crucial for member retention and acquisition. These digital front door experiences meet consumer expectations like those experienced in banking and retail.
Member Services Enhancement
AI agents provide 24/7 multilingual support. This improves member satisfaction while reducing reliance on human agents and leads to fewer follow-up calls about benefits or coverage. AI also provides members with detailed information about their coverage, benefits, and costs in real time. AI agents explain plan options, compare providers and clarify a patient’s treatment coverage before services occur. This transparency helps members make informed choices about their healthcare while reducing confusion and surprise bills.
Process Automation
The streamlined claims processing, PA and eligibility checks produced by AI reduce manual effort, errors and processing times. The resulting real-time issue resolution accelerates provider reimbursement and improves stakeholder relationships.
Personalized Care Management
As outlined in the journal Cost Effectiveness and Resource Allocation, the integration of AI into health insurance has driven advancements across crucial areas, including cost management, fraud detection, and operational efficiency. AI also strengthens transparency, data security, and customer privacy, supporting fairer practices and reduced operational costs.
Even smaller payers can gain value from AI. Partnering with experienced technology providers such as Providertech helps you compete with larger national carriers. That’s because our team of experts and professionals has extensive healthcare experience, including technology, clinical and operational perspectives. Schedule a demo with us, or listen to a sample recording to learn more!
