Streamlined operations, more tailored insurance product offerings, improved fraud detection, and faster claims resolution are all hallmarks of how generative artificial intelligence (AI) has helped improve insurance industry workflows over the past few years.

In 2025, insurers, MGAs, agents and brokers will take another leap forward as they leverage more advanced generative AI solutions. Insurance organizations will expand generative AI usage to cognitive solutions that can independently learn, reason, communicate and collaborate to execute fundamental operational tasks.

By integrating generative AI and working with insurers and managing general agents (MGAs) that deploy modern technology, agents can provide more tailored coverage options, accurate pricing, faster quoting and binding, and a better informed and personalized experience for their policyholders.

Here are four ways generative AI will elevate commercial insurance application submissions and policy lifecycle management within the agency distribution channel:
 
1) AI assistants will boost productivity. The next evolution of generative AI is the proliferation of assistant capabilities, sometimes called “agentic" AI. AI assistants are role-based digital co-workers built to assist autonomously and productively in many critical areas of the insurance workflow. Assistant AI programs can assume distinct personas, such as a risk appetite or claims experience assistant, in support of a human team. AI assistants can learn quickly, be trained and retrained easily, locate and access fresh data in real-time, and efficiently adapt to new information and processes.

AI assistants will enable agency staff to expedite coverage for their commercial clients by collaborating with carrier underwriting teams. A risk analysis AI assistant with instant access to exposure data can ensure accurate application completion; and a risk appetite AI assistant can immediately review agency submissions to determine eligibility, which also allows an agency to gain agility in seeking coverage and pricing elsewhere, if necessary.

AI assistants will enable agents to provide accurate, up-to-date coverage for specific product lines. For example, with lessors risk only (LRO) coverage related to property insurance, an agent will often supply a list of tenants to the insurer with the initial submission. But occupancy information may be missing or may change during the policy term. If tenants are not accounted for in the submission and issuance process, the nature of the business could expose the client.

By working with an insurer utilizing a cognitive AI assistant to monitor its LRO guidelines and portfolio in real time, an agency can be alerted to occupancy exposures and the need to review and update coverages with the policyholder.
 
2) AI assistant ecosystems create agile, responsive collaboration. Insurers and MGAs will adopt multiple AI assistants across the entire insurance workflow—from underwriting to claims to premium audits. These digital coworkers will become adept at communicating across functional areas and processes.

Information sharing between assistants will reduce the need for agency clients to provide the same information multiple times. For instance, if a workers compensation policy undergoes a premium audit, a risk analysis AI assistant specialized in underwriting processes can be trained to share information with the AI assistant designed to collect information for the audit process, so the agency's client does not need to answer the same set of underwriting questions again.

3) AI assistants will communicate like people. With platforms such as OpenAI ChatGPT and Google's Gemini, the plain language capabilities for generative AI solutions will continue to gain momentum. These qualities will proliferate among the autonomous AI assistants deployed by insurers, MGAs and their distribution partners. Users can interact and manage AI assistants more naturally and intuitively.

Some of the routine interactions agents have with insurers, such as identifying and providing missing information for policy applications, will be handled by AI assistants instead of human personnel. By having AI assistants handle simple inquiries, agency and insurer teams will have more flexibility to work on complex operational tasks and refine their customer service capabilities.

4) Grounding AI will help alleviate trust issues. Trust in AI output remains a top priority for all entities across the insurance sector. Currently, only 17% of agents trust AI technology, according to the 2024 Agent for the Future survey. Organizations seek accuracy in risk information and require complete transparency in the data used to determine AI-generated insights.

In response, insurance organizations and solution providers will increasingly ground AI to improve accuracy and answer concerns about trust while ensuring technology-enabled processes are aligned with current and future regulations. Grounding AI is providing models with access to specific data sources, which tether AI-generated content and actions to source data, thereby reducing “hallucinations." An AI assistant's output will then be connected to transparent and verifiable sources of information, building trust in emerging AI technology's output and analyses.
 
In 2025, generative AI will continue to reshape the independent agent distribution channel. By adopting generative AI technology and working with insurers and MGAs who embrace these AI trends, insurance agents can gain a competitive advantage with fast, precise coverages and pricing, as well as provide a more straightforward and exemplary service experience for policyholders.

Sathish Kumar Manimuthu is chief technology officer at NeuralMetrics, a leading provider of generative AI technology featuring a suite of AI-powered risk-quality data products and agentic AI capabilities for commercial insurers and MGAs.