The insurance industry has spent the past several years deploying AI to make existing processes faster and cheaper. Automating software testing workflows, surfacing policy data for call center representatives, and summarizing claims documents—these initiatives deliver measurable ROI, and many carriers are operationalizing them at scale.
As AI becomes more widely used, however, a more important question is emerging: will insurers simply improve existing processes, or will they redesign them entirely?
The Limits of Process Automation as a Moat
The current wave of insurance AI is largely focused on workflow enhancement. Carriers are deploying large language models to streamline underwriting submissions, extract information from claims, and reduce administrative burden across business functions. The efficiency gains are real; the problem is that they are widely replicable.
The larger opportunity may lie in rethinking how core insurance functions operate. Rather than applying AI to existing underwriting, claims, or service processes, carriers can use it to redesign those workflows from the ground up. Companies that take this approach may be better positioned to create longer-term differentiation and capture greater value.
What Reimagination Actually Looks Like
Reimagining the underwriting process means asking what that workflow would look like if it had been designed with AI as a foundational capability from the outset and recognizing that the answer might look entirely different from what exists today.
This kind of rethinking carries meaningful implications for where value accrues across the insurance technology stack. Data will play a critical role in determining which carriers may succeed. The value generated by AI depends heavily on access to high-quality, well-organized data. Insurers operating on fragmented legacy systems may face challenges, while those with more integrated technology infrastructures may be better positioned to scale AI effectively.
The Organizational Dimension
Technology strategy alone does not determine outcomes. The carriers that move earliest and most deliberately on this dimension—aligning governance structures, retraining workforces, and redesigning accountability around AI-augmented decision-making—are likely to sustain advantages that pure technology investment cannot replicate.
The efficiency phase of insurance AI is well underway. The reimagination phase is just beginning.
For more information on related investment opportunities and insights, please watch our William Blair Thinking video podcast, "On Risk: AI in Insurance (Infrastructure)," featuring William Blair’s group head of financial services and technology research, Adam Klauber, and Rich Drab, senior consultant in Capgemini’s Insurance Practice, and David Mocklow, head of insurance at Growth Protocol.