Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Shantanu Baruah, President & Global Head – Healthcare, Life Sciences, & Insurance at Hexaware
After several years of pilots, proofs of concept, and isolated chatbots, 2026 will be the year AI in insurance and healthcare moves from experimentation to true industrialization. The focus will shift from “Can we do this?” to “How do we safely scale this in production?” Autonomous agents, ambient intelligence, multimodal interfaces, and predictive systems will begin to transform how work actually gets done day to day. At the same time, the questions of trust, accountability, and data quality will become impossible to ignore. Here are five key trends that will define how AI reshapes these industries in 2026.
1. AI shifts from pilots to scale execution in insurance and healthcare
In both insurance and healthcare, AI will move beyond narrow use cases and become a core engine of “scale execution.” Instead of isolated chatbots or point solutions, we will see autonomous agents monitoring entire workflows. In insurance, these agents will continuously scan incoming claims to flag suspicious activity up front, rather than discovering fraud months later. Dynamic pricing and real-time underwriting will draw on climate and catastrophe models that combine satellite images, drone footage, and risk data to quickly assess high-risk properties.
In healthcare, ambient listening will evolve into a deeper “ambient visit experience.” Today, most ambient tools simply transcribe encounters into electronic records. In 2026, AI agents will start to act on that information: initiating lab orders, triggering prior authorizations, scheduling follow-up appointments based on the patient’s calendar, and coordinating across payers and providers. Combined with better use of shared data ecosystems, this shift will unlock more predictive intervention, where organizations focus not just on treating disease and processing claims, but on preventing them.
2. The liability gap and data challenges become the primary barriers to adoption
The biggest obstacle to broader AI adoption in 2026 will not be technology, but responsibility. As AI agents become more autonomous, a new “liability gap” emerges: when an AI system settles a claim that should have been denied, or misses a drug interaction a human might have caught, who is accountable? That question will be front and center for insurers, providers, and policymakers.
At the same time, fundamental challenges around data will persist. Healthcare still wrestles with entrenched data silos and conflicting models between payers and providers. Legacy IT systems in both industries make it difficult to fully leverage modern AI. Concerns around synthetic fraud, black-box decision-making, and data quality will force organizations to be more thoughtful in how they design, govern, and explain AI systems. As a result, even as the technology becomes capable of full autonomy, multiple humans in the loop will remain the norm for the foreseeable future.
3. Insurance workflows and customer experience will be completely reimagined
Beyond underwriting, AI will fundamentally reshape how insurance works, from first notice of loss through payment and renewal. Traditional workflows rely heavily on manual processes: call center agents capturing details, adjusters driving to sites, staff keying documents into core systems. In 2026, first notice of loss will shift to a multimodal intake process, where AI can understand voice, images, and text together. This will not only reduce friction; it will also bring a layer of empathy back into the process, especially in moments of crisis where customers can get personalized, detailed answers to dozens of pressing questions.
Remote inspection using computer vision and drones will dramatically shorten cycle times and improve accuracy in damage assessment. Middle office operations will also be transformed: policy changes that once required manual review will be processed instantly, renewals will become far more seamless, and reserve setting will be more data-driven. Meanwhile, AI-powered voice bots will enable 24/7, natural conversations with customers in multiple languages, providing information and reassurance at scale while human experts focus on more complex cases.
4. Patient experience and provider operations will become more personalized and relationship-oriented
On the healthcare side, AI will make care more personalized and more efficient at the same time. Ambient visit experiences will ensure that by the time a patient leaves an exam room, prescriptions are ready, tests are ordered, referrals are initiated, and appointments are scheduled – without a long trail of follow-up phone calls and paperwork. This creates a more relationship-oriented model of care where the focus is on the patient experience, not administrative burden.
Hyper-personalized care pathways will also become more common. With access to symptoms and medical history, AI will be able to ask a handful of targeted questions and then route patients appropriately (to urgent care, emergency departments, or primary care) while factoring in allergies, medications, and prior conditions. Digital concierge services will offer 24/7 guidance and care coordination, answering questions and providing support across physical and mental health. For providers, AI will reduce time spent on note-taking, discharge summaries, and shift handovers, freeing clinicians to focus on higher-value patient interactions, with AI serving as a second opinion and decision-support partner.
5. Key AI technologies will reach mainstream adoption across both sectors
Several technologies that have been emerging at the edges will move toward mainstream adoption in 2026. Ambient clinical intelligence will be widely deployed in healthcare settings as a core part of patient encounters. Predictive diagnostics and early warning systems will play a larger role in spotting risk earlier and enabling more proactive interventions. Digital twins, while still maturing, will increasingly be used in areas like clinical trial simulation and personalized medicine design. In insurance, agentic claims systems, computer vision for damage assessment, and compliance-focused AI will become embedded in everyday operations.
In summary, 2026 will be less about experimenting with what AI can do and more about industrializing what it should do in both insurance and healthcare. Organizations that succeed will be those that treat AI not as a novelty, but as a core operational capability – while taking seriously the questions of accountability, data quality, ethics, and human oversight. AI will not replace people in these industries, but it will meaningfully change how they work, enabling more empathy, speed, and precision in moments that matter most.
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ABOUT THE AUTHOR
Shantanu Baruah is President & Global Head – Healthcare, Life Sciences, & Insurance at Hexaware. He is responsible for driving global strategy, client success, and growth across the H&I vertical. His focus areas include expanding digital capabilities, accelerating AI-led transformation, and strengthening domain-driven delivery. He has over 25 years of experience in the healthcare and life sciences industry, with a strong track record in building high-performing global teams and leading complex client transformations.
