Commercial insurance has long been hampered by outdated methods that rely heavily on manual processes, making efficiency a persistent challenge. Industry professionals often deal with large amounts of paperwork and siloed data, resulting in slow underwriting and claims processing. With growing technological advancements, companies are now looking at artificial intelligence (AI) to address inefficiencies in the sector. This shift is evident as businesses explore AI-driven solutions aimed at streamlining operations and improving connectivity among brokers, wholesalers, and carriers.
Compared to previous efforts at digitization, which primarily focused on minor automation improvements, the current wave of AI adoption is more comprehensive. Earlier initiatives often required integrating multiple tools separately, leading to partial efficiency gains. However, new AI-driven solutions aim to unify various aspects of insurance workflows, reducing reliance on multiple point solutions. The increasing availability of advanced AI models has enabled a more seamless transition to automation.
What Role Does AI Play in Commercial Insurance?
AI is being deployed to address inefficiencies by introducing standardization across various systems. One key challenge in the industry has been fragmented data, with different definitions and metrics leading to inconsistencies. AI can create a unified data layer, ensuring standardization across firms and improving decision-making accuracy. This development is particularly relevant for brokers, who often struggle with extensive paperwork and complex workflows.
Outmarket AI, a company working on AI applications for the insurance sector, recently secured $4.7 million in funding to enhance its platform. The company is building an AI model designed specifically for insurance, rather than relying on general-purpose AI tools. This approach aims to integrate seamlessly with legacy systems and improve workflow automation.
“We’re not just digitizing insurance,” said Vishal Sankhla, co-founder and CEO of Outmarket AI. “We’re redefining it.”
How Will AI Improve Broker Efficiency?
Brokers play an essential role in the insurance ecosystem by advising businesses on appropriate coverage. However, their operations involve handling large volumes of unstructured data, often spread across separate systems. AI-powered platforms can help brokers manage data more effectively, automate document processing, and reduce the administrative burden associated with policy management.
One of AI’s advantages is its ability to improve key performance indicators, such as the submission-to-bind ratio. AI can analyze historical data to pre-fill renewal applications and suggest faster policy-binding options when delays occur.
“If one carrier takes too long, brokers can explore faster alternatives. AI can also pre-fill renewal applications using last year’s data, eliminating unnecessary back and forth,” Sankhla stated.
As AI gains traction in commercial insurance, the competitive landscape will likely shift from who adopts AI to how well companies integrate it. The focus will be on optimizing workflows without forcing fundamental changes to existing systems. While companies have previously used separate tools for data management, analytics, and automation, AI platforms now aim to provide an all-in-one solution, reducing complexity for brokers and underwriters.
The broader implications of AI adoption go beyond brokers. More streamlined insurance processes mean underwriters receive complete applications faster, improving turnaround times for policy approvals. Insurers can enhance risk assessment models with better-quality data, leading to more precise coverage options for businesses. While these technologies promise efficiency improvements, their success will depend on adoption rates and seamless integration into existing industry workflows.
