Walking into ITC Vegas 2025 this year, the tone was unmistakable: grounded, candid, and markedly more practical than years past. Conversations moved quickly past the hype and straight into the real issues leaders are grappling with such as rising fraud pressure, the strain on claims operations, and the need for AI that does more than make promises. With insurance fraud now costing the U.S. an estimated $308.6 billion annually, the urgency was felt in every session and hallway discussion. Trust, transparency, and performance weren’t just themes; they were expectations. It created the right backdrop for honest dialogue about what claims organizations actually need next, and what they’re no longer willing to tolerate.
That energy aligned strongly with the announcements Wisedocs brought to the conference. Case Reports & Cross-Case Insights and our reengineered Wisedocs Intelligence Engine weren’t just product updates, they opened the door to deeper industry conversations around the future of claims intelligence, defensibility at scale, and the infrastructure carriers need to keep pace with what’s coming.
I kept hearing the same themes echoed back from leaders across the ecosystem. Stakeholders described the same pressures of more medically and legally complex files, higher fraud sophistication, and the need for stronger claims efficiency. Many shared that reviewers are spending too much time sorting paperwork instead of making informed decisions, creating delays that have a ripple effect across multiple teams. Approximately 84% of health insurers are already using AI or machine learning in some form, and nearly 92% are aligning their governance principles with clarity, accountability, and consistency. The standards around how these AI solutions should perform have never been higher, and frankly, it’s about time we held technology to the same standard as the people doing the work.
Compliance expectations shaped the conversation across the week. The same sentiment rang true: organizations want domain-trained AI that is built to help them move faster while keeping their operations consistent and audit ready. Afterall, in a legacy industry like insurance, anything less than dependable isn’t worth deploying.
Looking back on the conversations I had at ITC, one thing became clear: meaningful progress requires letting go of what’s no longer serving us. If we want to build a stronger, more scalable future for claims, we have to start by naming what no longer works. Here are the beliefs claims leaders agreed it’s time to move past
One thing that became very clear at ITC this year: the industry is exhausted by vendors claiming they’ve built “AI for insurance” when the models were never trained on actual claims or medical data. If your foundation is a generic LLM, you’re not solving real operational problems, you’re just repackaging ChatGPT with a glossy UI. Claims teams deal with nuanced, high-stakes document types, and generic engines simply can’t meet that bar. At Wisedocs, we’ve trained over 1,500+ document-type models so our customers get insights built on true domain depth.
I’ve scaled enough SaaS products to know that a single accuracy number without context is meaningless. A 99% metric on clean PDFs doesn’t tell you anything about how a model performs on the messy, scanned, multi-format files claims teams handle every day. Leaders at ITC were vocal: accuracy must be transparent, benchmarked, and tied to real-world document types. True partners don’t hide the edge cases, they build systems with workflows that are auditable and defensible.
This point kept coming up, and it’s one the industry is finally pushing back on. Claims decisions require nuance, experience, and AI governance that automation alone simply cannot provide. The strongest solutions pair speed with expert-in-the-loop oversight to ensure accuracy, compliance, and trust. ITC 2025 made the industry’s stance clear: AI should empower adjusters and examiners, not sideline them.
Many people still assume any AI can easily interpret a complex medical record or a claims packet, but that couldn’t be further from reality. General LLMs break down quickly when faced with multi-format, multi-source, 50,000-page claims files. Without domain-training and contextual knowledge from real claims data, off-the-shelf LLMs simply can’t interpret the nuances. That’s why we rebuilt the Wisedocs Intelligence Engine on 25M+ claims-document data points, designed specifically for high-stakes medical and legal content. Even OpenAI has now restricted medical and legal advice, a glaring reminder that claims and medical document reviews require specialized intelligence, not general chatbots.
If there was one area where the industry aligned this year, it was governance. Auditability, explainability, and traceability aren’t “nice to have”, they’re mandatory in the high-stakes industry of claims. As compliance expectations grow, every AI output must be expertly reviewed, audit-ready, and defensible. The future of claims intelligence belongs to teams who architect transparent pipelines that prove accuracy, not just promise it.
Across every theme, the takeaway was clear: teams are asking for AI that’s defensible, transparent, and truly domain-aware, working alongside their expertise, not against it.
Walking the floor at ITC, the industry’s push for real, grounded solutions was impossible to miss — and that’s exactly why our first announcement resonated so strongly. Our unveiling of enterprise ready claims intelligence landed at exactly the right moment. Professionals were asking for clearer fraud detection, reliable reporting, and easier ways to surface patterns within portfolios. These features give adjusters human-verified summaries, trend visibility, and a way to manage rising documentation volume while avoiding manual effort.
In almost every conversation I had with leaders this year, the message was the same: they don’t just want AI, they want AI they can trust, scale, and defend. That’s why our second announcement mattered. The launch of the Wisedocs Intelligence Engine outlined a clear path forward for carriers, delivering faster processing, deeper clarity, and reliable guidance through a reengineered system purpose-built for enterprise scale. The new engine meets those priorities with 8x faster performance, modular models trained on real claims data, and expert-in-the-loop supervision. Together, these launches aligned with the strongest themes at ITC around dependable AI, safer automation, and capability at the enterprise level.
Coming out of a key event like ITC, it was clear that carriers are asking for more from their AI partners. But it’s exactly these moments that remind me why we build: to listen, to learn, and to deliver a product that not only meets the market’s needs, but creates meaningful, lasting value.
By pairing AI with human oversight, we’re giving carriers the level of clarity required to move confidently through dense files and arrive at stronger, more informed decisions. Many teams at ITC described working through tens of thousands of pages in mixed formats while facing rising legislative pressure. Case Reports, Cross Case Insights, and the Intelligence Engine were built for this reality and help carriers keep their decisions defensible and auditable.
When I think about what the future holds for carriers, the path forward is becoming more defined: stronger fraud detection, streamlined workflows, and more consistent outcomes powered by trusted intelligence. That momentum carries straight into early 2026, where our Q1 roadmap brings advanced document sharing and expanded cross-case capabilities to life. This is the work that motivates us every day, and it’s an exciting chapter to build in where we’re right on track to deliver trusted claims intelligence that will move carriers and the entire industry forward.