At Upland Specialty Insurance, transformation is never about technology for its own sake. Instead, the company takes a pragmatic approach, targeting specific pain points in underwriting workflows and pairing focused innovation with disciplined delivery.
For Doug Alexander, chief technology officer, the mission is straightforward: make underwriters more effective by addressing manual bottlenecks and improve the speed to insights for decision-making across the business.
“The big focus for innovation initiatives is for underwriting teams,” Alexander said. “There are two pieces: operational efficiencies—how you help underwriters do their job better—and the insights you provide to them.”
The result is a deliberate, calibrated push toward automation and better data, centered on real operational needs rather than experimentation for its own sake.
Alexander says Upland’s innovation efforts focus on two main areas within underwriting: reducing manual tasks and enhancing the speed and quality of data available to decision-makers.
Operational efficiency often means automating repetitive manual work, such as using AI for data extraction, third-party data lookups and integrating disparate sources of information so underwriters can spend less time on lookup tasks and more time on judgment calls.
“We automate many of the manual lookup tasks, third-party integrations and stitch all that together,” he said. “Then you focus on the insights to address is this really within our target, and does it cover some other concerns that we may have.”
That dual focus, Alexander says, helps underwriters sift through data faster and with greater context. The objective is not to replace human judgment but to augment it with tools that reduce friction in daily workflows.
Underwriters, for example, can receive faster alerts about where a risk sits relative to appetite, and where further scrutiny is required. In practice, this means linking core systems such as OneShield, Upland’s policy administration platform, with advanced data extraction tools like Further AI to eliminate data silos and streamline analysis.
Selecting the right technology partners is a central part of Upland’s transformation strategy. Alexander says the company takes a measured stance when vetting third-party providers, prioritizing small proofs of concept to validate value quickly.
“We check a lot of references and prefer small proof-of-concept projects,” he said. “We don’t believe the hype. We break the problem down into small pieces, measure success quickly and focus on workflows that genuinely add value.”
Part of that discipline, he adds, is resisting solutions that promise broad, one-size-fits-all fixes. “You have to know where technology fits and where there’s a basic workflow or process problem that should be fixed before you start throwing AI at it,” Alexander said.
His background in venture due diligence underscores that point: understanding vendor risk and aligning technical capability with business value are essential to avoid costly missteps.
“You probably don’t want to be the first on your block with a new vendor unless you’re a design partner and you really understand that risk,” he said. “That’s where talking to people you know and looking at actual use cases matters.”
