Oct 224 min read

InsurTech Ohio Spotlight with Matt Workman

Matt Workman, a seasoned leader with over 24 years of experience in the insurance industry, specializing in helping companies leverage transformative technologies, currently serves as a Senior Client Partner at Persistent Systems. Matt was interviewed by Andrew Daniels, Co-Founder and President at CrashBay, and Founder and Managing Director at InsurTech Ohio.

Matt, what is the current state of Artificial Intelligence (AI) adoption in the insurance space?

“Artificial Intelligence adoption in the insurance space is accelerating across the entire value chain—whether it's MGAs, carriers, TPAs, brokers or reinsurers. All of them are exploring and implementing AI technologies across various functions. However, carriers are primarily using AI for underwriting, claims processing, fraud detection and customer service, often through tools like chatbots. Artificial Intelligence is crucial for automating repetitive processes such as form submissions, claim reviews and customer inquiries. It's also being applied to risk assessment and policy pricing, enabling analysis of large amounts of structured and unstructured data faster and more accurately than ever before.

That said, the industry is still in the early stages of adoption, and full implementation is a few years away. Many companies, particularly small and medium-sized ones, are waiting to see how AI unfolds before fully committing. Only a handful have integrated AI into their end-to-end processes.

Adoption remains fragmented, largely because of the complex nature of insurance operations. Artificial Intelligence implementation involves multiple stakeholders and navigating regulatory constraints. A significant barrier is the continued reliance on legacy systems, which are challenging to modernize. Overcoming these hurdles will take time.”

How can AI create differentiation?

“It comes down to two key elements: personalization and efficiency. Artificial Intelligence enables highly tailored experiences based on customer data and satisfaction. For example, it can analyze behavioral data to recommend personalized policies or suggest premium adjustments. We're already seeing a more customized experience for policyholders, insurers and brokers.

This shift appeals to a broad demographic, from younger generations to older customers seeking more tailored products. On the efficiency side, AI-driven process automation reduces operational costs and accelerates service delivery, particularly in claims management. By eliminating much of the manual effort at the first notice of loss, AI can drastically improve processing times.

Another area ripe for AI disruption is underwriting. Despite the wealth of data and tools available, many manual elements remain in the underwriting process. Artificial Intelligence can help streamline these tasks and enhance efficiency, offering significant value where time-consuming manual work still prevails.”

For sellers of AI tools in the insurance space, how should they approach potential customers?

“Sellers need to approach insurance clients with deep industry knowledge. Insurance is a complex space with unique challenges, and a lack of understanding will make it difficult to succeed. Many sellers have broad knowledge across multiple industries, but deep expertise in underwriting, claims and the overall customer experience is essential.

Insurance is slower to adopt new technologies and more risk-averse compared to other industries, so building trust is key. This comes from showing genuine care for the industry and offering proof of value. Given the regulatory limitations and compliance concerns, trust is critical. Sellers must understand that coming in with an attitude of 'solving all problems with AI' is a mistake.

Instead, they should focus on smaller, meaningful efforts that are manageable for buyers. Understanding the industry, speaking the language and demonstrating real solutions will help sellers navigate this space effectively. Many insurers are still in experimental phases with AI.”

How should buyers approach the vetting process?

“First, buyers need to be clear about their goals. What are you trying to solve? What are your pain points as a carrier, MGA or TPA? Being honest about these goals is important. Any solution should provide immediate operational benefits and long-term scalability. Buyers should aim to implement solutions gradually—don’t try to boil the ocean.

It can be overwhelming to evaluate multiple vendors. When vetting AI solutions, buyers should prioritize data security, regulatory compliance and the vendor’s track record within the insurance industry. Insurers are often behind other industries in technology adoption, so working with knowledgeable partners is vital.

Data privacy and cybersecurity are also critical. Due diligence is essential to avoid potential breaches or non-compliance issues, which could have severe repercussions. Non-compliance can lead to serious consequences, so this aspect cannot be overlooked.”

Should carriers build their own AI models?

“No. In my view, it's a waste of time, energy and resources—unless you're a large carrier or broker with deep pockets. Some organizations have the internal talent to take on these projects, but most do not. I know of one individual outside the insurance industry who built an AI model application for a health and life sciences company as a side project, but such cases are rare and even more rarely scalable.

Most players in the insurance ecosystem lack the scale to build their own AI models effectively. The smarter approach is to partner with vendors who specialize in insurance AI. These partners already have the expertise, models and integration capabilities needed to address the core elements of the insurance ecosystem efficiently.

In closing, as the industry continues to evolve, a thoughtful approach to both selling and adopting AI will be essential for creating meaningful value.”