In the healthcare technology landscape, generative AI (GenAI) is emerging as a valuable companion to longstanding predictive AI solutions. GenAI refers to AI that can assist in creating content — such as summarizing complex clinical information — while predictive AI leverages data patterns to forecast outcomes and support decision-making.
Organizations that have provided proven predictive AI tools for over a decade are now complementing these capabilities with GenAI to further improve efficiency, reduce administrative burden, and foster greater alignment between health systems and health plans. In today’s fast-moving environment, how can GenAI deliver rapid impact without overpromising automation?
Supporting Administrative Efficiency
Administrative costs make up over 40% of hospital expenses, according to the American Hospital Association. GenAI can help reduce this burden by supporting documentation-heavy processes that traditionally consume valuable clinical time.
For example, GenAI can assist with drafting clinical summaries for medical necessity reviews, preparing supporting narratives for appeal letters, and helping streamline prior authorization documentation. Rather than replacing clinicians, GenAI enhances their workflows — allowing them to focus more on patient care coordination and transitions of care.
Driving Financial Resilience Through Collaboration
GenAI also plays a role in supporting the financial health of provider and payer organizations. As claim denials rise — with commercial denials increasing 20.2% and Medicare Advantage denials 55.7% year-over-year — tools that accelerate alignment between stakeholders are increasingly critical.
When used alongside predictive analytics, GenAI can assist in drafting structured, clinically grounded content that helps ensure clarity and consistency in utilization management. These efficiencies reduce administrative friction and help providers and payers arrive at the right decision faster. In today’s environment of staffing shortages and margin pressures, this kind of shared intelligence can deliver meaningful ROI.
Enhancing Communication and Alignment
GenAI also holds promise for improving communication between teams — from utilization management to case management to payer partners. By helping generate summaries of clinical cases, GenAI ensures that all stakeholders have a clearer, shared understanding of the patient’s medical history and current needs.
Initial feedback from Xsolis clients indicates these summaries may also be extended to downstream settings, such as skilled nursing facilities or physical therapy, to help expedite documentation and treatment planning.
Breaking Down Silos to Reclaim Time for Patient Care
Predictive AI has long helped healthcare organizations analyze large volumes of structured and unstructured data to inform decisions. With GenAI as a complementary capability, teams can move faster while staying aligned.
For example, Xsolis’ Dragonfly platform — which already helps users save approximately two hours per day — now incorporates GenAI to support faster preparation of clinical summaries used in medical necessity review. Rather than replacing human oversight, this collaboration enables concurrent reviews to be completed more efficiently, helps reduce avoidable denials, and frees up time for more patient-focused tasks.
The Path Forward: Responsible Innovation with GenAI
Integrating advanced technologies in healthcare is a journey, not a sprint. While the industry remains cautiously optimistic about GenAI’s potential, the focus must remain on responsible, human-centered implementation. According to a recent Harris Poll, over 90% of providers and payers express confidence that GenAI can help reduce administrative tasks — if deployed thoughtfully.
By pairing GenAI with proven, predictive AI capabilities, healthcare organizations can reallocate time and energy toward improving both patient and member experiences — while simultaneously strengthening the operational partnership between providers and payers.
Learn more about how Xsolis is bringing predictive and generative AI together — responsibly.