How quickly does the insurance space evolve? Nearly three years ago, I wrote about
Yet while technology advances quickly, it also follows a pattern of evolution. Over the past 36 months, our industry has seen remote imagery emerge as a complement to telematics, Big Data morph into advanced analytics, and AI move from curiosity to an industry imperative. Each pivot represents the natural next step in the digital sophistication of carriers, agents and brokers.
Today's top emerging tech trends in the insurance space also continue a trajectory I saw developing three years ago. The move-fast-and-break-things ethos that defined ambitious insurtechs has given way to a more measured approach centered on compliance and sustainability.
One reason for this shift is financial, as global insurtech funding
Simultaneously, startups are moving away from disruption and toward cooperation. VC firms are choosing to invest in insurtechs that design solutions built to help carriers and brokers achieve maximum efficiency and growth.
Given these global changes, what technological advancements can we expect to see across the insurance industry heading into 2026? These are the top five technologies that stand out.
1. AI and Intelligent Document Processing
Generative AI
Generative AI began as a novelty, with lots of experimentation and pilot programs but few use cases in production. Concerns about AI hallucinations and worries about deploying generative AI ethically and responsibly slowed down adoption.
Today the Large Language Models (LLMs) that power generative AI have improved materially, providing the context needed to reduce hallucinations. This has sparked a massive shift from experimentation to mainstream. Generative AI is now proven in:
· Customer service and care, handling the bulk of customer interactions with a personal touch that feels nearly human
· Coding assistance, enabling IT teams to modernize faster
· Document generation, creating policies, summaries and marketing content for human review quickly
ROI includes better customer service, faster product launches and increased staff productivity.
Intelligent Document Processing (IDP)A more advanced application of generative AI, IDP presents a massive opportunity for carriers, brokers and agents to become even more efficient and effective. IDP uses AI tools to read documents and extract key pieces of information, turning unstructured data into structured information available for use by multiple downstream systems. This use case is essential for improving the ROI of generative AI. IDP can be used to:
· Scan incoming claims submissions, select key details and push them into underwriting systems
· Run sophisticated validation and review underwriting data in real time
· Perform claims triage by scanning forms, flagging issues and routing them to adjusters
In these ways, IDP will help underwriting and claims staff spend less time on tedious tasks and more time on strategic decision-making. Of course, human review of this data remains necessary to validate the information and catch potential lingering hallucinations.
Agentic AI
Agentic AI takes generative AI and IDP to the next level. It involves deploying autonomous AI agents that can take multistep actions and provide trusted outputs. Potential use cases include:
· Orchestrating multiple data pulls, running scenarios and preparing recommendations in underwriting
· Moving from document intake to validation, routing and escalation in claims with minimal human input
· Completing quote, bind and issue processes across integrated systems
While AI agents can complete the bulk of this work autonomously, a human-in-the-loop will still be required to manage approvals and exceptions.
2. Big Data and Advanced Analytics
Now that most insurers have compiled huge volumes of data, the next step is extracting meaningful insights from that information faster and more accurately. That is where advanced analytics will come into play. Expect to see wider adoption in 2026, with predictive analytics expanding from niche programs to enterprise-wide implementation.
The competitive edge will go to insurers that move away from static analysis toward real time, dynamic models capable of updating predictions as data flows into systems. Consider the value of combining data from telematics and internet of things (IoT) devices with insureds' demographic and socioeconomic data to create a 360-degree view of risk in the moment.
As predictive models mature, they will sharpen our industry's ability to assess and segment risk accurately, price policies, implement more sustainable pricing and improve profitability. Embedding predictive analytics into underwriting and claims workflows can boost worker productivity, too.
3. API Connectivity
Implementing predictive analytics can be challenging for insurers saddled with difficult-to-integrate legacy systems. Application programming interfaces (APIs) offer a bridge, allowing organizations to easily connect different systems and move data up and down the entire insurance value chain.
With API connectivity, insurers can embed core processes such as quote, bind and issue directly into existing workflows instead of treating them as separate transactions. This improved functionality can help insurers launch sought-after products like embedded insurance to improve the customer experience. APIs can also link carrier, agent and broker systems with third-party providers, bringing in crucial data like property records and credit scores without requiring manual searches or re-keying.
4. Core System Modernization and Cloud Computing
Integration hassles are not the only problem with legacy systems. Older platforms are also more difficult and costlier to maintain, creating what is known as technical debt. Modernization is the path toward lowering technical debt, which is why insurers will continue moving their core systems — such as billing, policy and claims platforms — to the cloud.
Along with reducing upkeep cost and time, cloud modernization eases data integration and prepares carriers for an AI-enabled future. Cloud-based solutions that offer low-code and no-code capabilities democratize technology, allowing business users to create processes and products without requiring a team of dedicated information technology (IT) developers or deep knowledge of programming languages.
5. Computer Vision and Remote Imagery
While telematics gives insurers valuable in-the-field data, computer vision and remote imagery go a step further. They provide photos and videos — including aerial and satellite imagery — so underwriters and adjusters can do their jobs better.
Remote imagery can replace in-person annual inspections by providing underwriters with real-time evidence of roof damage or vegetation encroachment for properties in wildfire-prone areas. After a catastrophic (CAT) event, aerial images from drones can help adjusters triage an onslaught of claims in hours instead of weeks. Computer vision models, meanwhile, can interpret fender damage from photos and shrink the claims cycle from days to minutes. These efficiencies make computer vision and remote imagery a top tech selection for 2026.
Technology trends are historically a moving target, but as insurers take a more pragmatic approach to innovation, the industry and our policyholders will benefit. Creating a solid foundation in AI and predictive analytics will help carriers, agents and brokers build resilient business models and achieve sustainable growth.
