Insurers and MGAs are upping the ante on AI. For the last several years, the industry has focused on the best ways to leverage
However, the application of generative AI is becoming more sophisticated and innovative. In 2025, insurers and MGAs will look to deploy AI capable of executing and completing tasks independently. These tools will enhance productivity and enable cost efficiencies across the insurance value chain.
Here are five gen AI trends that can contribute to modernizing and transforming insurance operations:
1. The future of gen AI is agentic capabilities. The first wave of AI was rule-based. The second wave focused on machine learning. The emerging third wave is agentic. Insurance organizations will implement cognitive, role-based AI assistants as digital co-workers across many insurance processes. AI assistants can assume distinct personas, such as risk appetite or claims experience specialties, and support those functional teams. They can learn quickly, be trained and retrained easily, locate and access fresh data instantly, and adapt to new information and processes efficiently.
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2. The perfect feedback loop will be an AI ecosystem. Insurance organizations won't just put one AI assistant into place. Expect them to onboard and integrate multiple versions to take on a variety of knowledge work and basic tasks. The digital coworkers won't operate in silos but will become adept at communicating across functional areas and processes, creating a virtuous circle and feedback loop: An AI assistant supporting claims can share incoming claims experience/processing outcomes with an AI assistant handling risk appetite. If an insurer processes many claims in a particular product line or risk class, the risk appetite assistant can flag eligibility guideline changes for the underwriting team's consideration.
3. Avoid technical jargon and speak plainly with AI assistants. ChatGPT and similar applications have paved the way for conversational language communication with advanced AI solutions. Non-technical interactions will proliferate and become natural when working with autonomous AI assistants. Users can intuitively interact and manage AI assistants as the technology improves and more directly supports team collaboration with role-based AI assistants in critical operational areas.
Plain language capabilities will make AI assistants more adaptable to supporting change and disruption in business activities. For example, while it may have taken months to update legacy systems to bring new products to market or activate revised underwriting guidelines, adjustments can be made immediately with a risk appetite AI assistant without technical support. The AI assistant can learn and apply the new guidelines immediately. Let's say a commercial insurer wants to eliminate Lessor's Risk Only (LRO) coverage for properties with businesses open later than 10:00 PM. The new guideline can be fulfilled via simple verbal or typed instructions to the AI assistant — no programming is required.
4. Grounding AI sets the table for building trust. Accuracy of risk-quality information and transparency of data sourcing by AI is a priority for every insurance organization, particularly as new state and federal regulations continue to evolve. Expect more focus on grounding AI, which can connect AI outputs to verifiable sources of information. By providing models with access to specific data elements, grounding can tether AI-generated information and actions to source data, thereby reducing hallucinations and helping build trust in emerging AI technology's implications and outputs.
5. AI advances from an efficiency tool to a driver of innovation. As insurance organizations experiment with generative AI, there will be a growing realization that the technology isn't outthinking them. Instead, it's making their knowledge-based work more refined and constructive. The apprehensions of people being replaced by AI will continue to dissipate. But that doesn't mean people don't need to adapt to AI. Refusing to incorporate the technology will put professionals at a disadvantage compared to their peers. Insurance professionals will have to focus on ways to use AI to optimize their workflows.
This year, we'll see exponential growth in generative AI deployment among insurers and MGAs. Cognitive, role-based gen AI in the form of autonomous AI assistants will enable insurance organizations to add capacity, access risk insights on demand, reduce premium leakage, manage claims more proficiently, and improve cost efficiency. Uncertainties around AI will dissipate as grounding AI builds trust, and there is less anxiety that AI will replace people. With more advanced use cases for cognitive and adaptive AI across the insurance lifecycle, insurers and MGAs will gain productivity, grow their books of business, and refine policyholder services.
