Joe Christman (pictured), chief technology & AI officer at Novacore, positions the company’s transformation agenda around a single, defining objective: underwriting profitability.
Rather than pursuing broad digital change, Novacore concentrates its technology and AI investments on improving outcomes across the underwriting value chain. That focus reflects a wider shift among MGUs, where precision and speed increasingly determine competitive advantage.
Christman says the company aligns its transformation efforts across three core constituencies: producers, carrier partners, and internal underwriting teams. Each interaction point becomes a target for AI-driven enhancement, from submission intake to risk evaluation. “We are really laser focused on one thing, and that is writing profitable business,” he said. That clarity of purpose shapes both the pace and direction of Novacore’s technology deployment.
The rapid evolution of large language models marks a turning point in Novacore’s strategy. Christman points to the release of next-generation models as a catalyst that fundamentally alters the competitive landscape. The world changed in November with the release of Anthropic’s Claude Opus 4.5, this has empowered companies like ours to really operate at the level of some of the leading tech companies in key areas,” he said.
For MGUs, this shift expands access to AI and automation capabilities that were once limited to large insurers or technology firms. Novacore responds by embedding these models across its workflows, targeting inefficiencies that historically constrain underwriting performance. The emphasis is not on experimentation alone, but on practical deployment tied directly to business outcomes.
This approach extends beyond internal operations. By enhancing how the firm interacts with brokers and carriers, Novacore aims to streamline communication and decision-making. AI tools are applied to reduce friction in submission handling, improve data
extraction, and accelerate turnaround times. These improvements, in turn, reinforce the firm’s ability to select and price risk effectively.
Christman emphasizes that the opportunity is not incremental. “There are opportunities to transform every part of our value chain with these new models,” he said. The company pursues that opportunity aggressively, prioritizing initiatives that directly contribute to underwriting accuracy and efficiency.
While the technology itself advances rapidly, Novacore relies on a familiar operating model to ensure successful implementation. Christman describes a “two-in-the-box” approach, pairing business and technology leaders on every initiative. This structure ensures that subject matter expertise is integrated from the outset, reducing the risk of misalignment between tools and user needs.
“Any large initiative or even small initiative, you need to have a business sponsor and a tech sponsor involved in day one,” he said. This model reflects lessons from prior transformation efforts, where lack of engagement from end users often limits adoption. At Novacore, underwriters and other stakeholders are involved early, shaping how new capabilities are designed and deployed.
The nature of AI-driven tools also contributes to smoother adoption. Unlike earlier systems that introduce additional complexity, newer solutions often remove manual tasks that underwriters find burdensome. “These new AI architectures are solving problems that are most burdensome to our underwriters,” Christman said. As a result, resistance to change diminishes, and uptake accelerates.
The outcome is a reallocation of time and expertise. By automating routine processes, Novacore enables underwriters to focus on higher-value activities such as risk assessment and portfolio management. “What that has allowed us to do is give our underwriters more time to do what they do best at,” he said. That shift reinforces the company’s central objective of improving underwriting quality.
Novacore applies equally stringent criteria to its external technology partnerships. In a market crowded with emerging vendors, the firm adopts a clear filter: any partner must be built on leading AI platforms. “we prioritize partners that have a leading AI lab powering their software,” Christman said.
This requirement reflects both performance expectations and a desire to avoid short-lived solutions. By anchoring partnerships to established AI ecosystems such as
OpenAI, Anthropic, and Google, Novacore aims to ensure scalability and continuous improvement. At the same time, the firm uses these tools internally, allowing both business and technical teams to build familiarity and expertise.
Leadership alignment plays a decisive role in sustaining this strategy. Christman highlights the importance of executive commitment, citing strong support from Aaron Miller and Chase Clark. “They are fully committed to revolutionizing how we underwrite through the power of tech and AI,” he said. That endorsement establishes a top-down mandate that reinforces adoption across the organization.
Christman argues that such alignment is not optional. “Without that, most… companies fail in these types of AI transformations,” he said. At Novacore, leadership support extends beyond vision-setting to active participation in execution, ensuring consistency between strategic goals and operational decisions.
The firm’s transformation efforts ultimately converge in their proprietary platform, which serves as the central hub for its AI capabilities. By consolidating tools and workflows into a unified environment, Novacore seeks to embed its strategy into daily operations rather than treating it as a standalone initiative.
