Artificial intelligence is already making an impact in the global insurance industry, and four subsectors are particularly ripe for further disruption: brokers, managing general agents (MGA), software providers and third-party administrators (TPA), according to a report from consulting firm McKinsey & Company.
The firm estimated that generative AI could unlock between US$50 billion and US$70 billion of insurance industry revenue, “with the highest impact on marketing and sales, customer operations and software engineering dimensions.”
Brokers
Insurance brokers have already used AI to increase conversion with automated submissions, match carrier appetites and find opportunities for additional sales. In the future, agentic AI may handle renewals for simple risks with limited human intervention, the report noted.
AI can also reduce administrative workload by simplifying processes like quoting, filling application forms and processing endorsement on carrier websites. In the longer term, brokers with larger books of business will have access to more data and can use it to attract agents.
MGAs
Premium volumes in the U.S. channelled through MGAs grew about 14% annually over the last decade, with direct premiums nearly doubling between 2020 and 2024, to $97 billion from $47 billion, the report said.
“MGAs have become central to innovation in insurance, creating demand for more sophisticated use of data and technology. As the market further evolves, AI can create value across both underwriting and distribution,” it said.
AI speeds up customer intake and can perform risk scoring at underwriting. Some AI systems can underwrite and quote simpler, lower-risk policies, with minimal human input.
MGAs that consolidate their proprietary data and generate clear customer insights will be valuable partners to carriers and brokers, McKinsey said.
Software providers
Carriers are moving from having monolithic AI systems toward having a more modular approach where models are matched with the right use cases.
Software providers developing custom models can collaborate with other AI systems using open standards. At the same time, legacy system providers will need to make their platforms more open to accommodate other models. Insurers will be able to plug new tools in core systems without major re-platforming and avoid being locked in to specific vendors, the report said.
Third-party administrators
TPAs have access to transaction-level data and can use AI to improve speed and service in high-volume workflows. But it’s not clear yet how they can generate revenue from more efficiency.
Currently, TPA arrangements still rely on head count and activity-based metrics or cost-plus revenue models. So, increased automation can pressure top-line revenue as compensation isn’t always linked to better outcomes.
“As a result, we expect the next phase of the subsector to be defined less by whether TPAs adopt AI (they will) and more by how they evolve their pricing models and competitive positioning,” the report said. “And as automation reduces the complexity advantage that TPAs have historically held, maintaining cost competitiveness and continuous innovation will remain critical.”