Convr AI Deploys Autonomous Agents to Reshape Underwriting

CHICAGO, IL – December 16, 2025 – In a move that signals a significant leap from automated assistance to autonomous action, Convr AI® has announced the deployment of Agentic AI Workflows within its underwriting workbench. The company, which serves the commercial Property & Casualty (P&C) insurance sector, is introducing a new class of digital workers designed to operate with unprecedented independence, aiming to redefine efficiency and speed in one of the insurance industry's most critical functions.

The launch integrates pre-built 'agents' focused on referrals, financial analysis, and underwriting authority directly into the Convr platform. This development moves beyond traditional automation tools, which typically require direct user commands to perform tasks. Instead, these new AI agents are designed to proactively manage and advance underwriting files, functioning less like a tool and more like a digital member of the underwriting team.

"Agentic AI reduces friction across the underwriting process," said John Stammen, Chief Executive Officer at Convr, in the company's announcement. "The agents make moves that work for you autonomously to drive a quicker submission through quote that enable you to write more business, faster."

Beyond Automation: The Rise of the Proactive Agent

The core distinction of this new technology lies in the concept of 'agentic' behavior. Unlike rule-based systems that follow a rigid, pre-programmed script, these AI agents leverage large language models (LLMs) to interpret goals, orchestrate complex tasks, and interact with various data sources and software tools. This allows them to operate with a degree of autonomy, making decisions and initiating actions to move a submission forward.

For instance, Convr's new Referral Agent can automatically analyze a submission's exposures, loss history, and coverage limits to generate a comprehensive referral summary. It then determines whether the submission falls within the carrier's risk appetite or requires escalation to a human underwriter. The system is designed for adaptability, allowing carriers to grant the agent increasing levels of agency.

"You can actually give the agent more agency to make the referral," explained Harish Neelamana, Co-Founder and President at Convr. "You can drive the declination process without stepping into it and you can make corrections on your initial clearance and triage. Those are all templates that are built into the Convr platform."

To lower the barrier to entry, Convr has developed a library of pre-built templates with starter prompts. This enables underwriting professionals, even those without a background in prompt engineering, to configure and deploy these workflows. This approach aims to empower existing teams to customize the AI's behavior to fit their specific operational needs and risk philosophies.

The Human Element in an Autonomous World

The introduction of systems capable of autonomous decisioning inevitably raises questions about the future role of human professionals. Industry analysis suggests that Agentic AI is poised to augment, rather than replace, human underwriters. The technology is expected to handle the high-volume, data-intensive tasks that currently consume a significant portion of an underwriter's day—data extraction, form-filling, preliminary risk flagging, and data enrichment.

By automating these processes, the technology promises to free up underwriters to concentrate on higher-value activities. This includes handling complex, nuanced cases that require deep domain expertise, negotiating with brokers, building client relationships, and providing critical strategic oversight of the automated portfolio. The role is expected to evolve from a data processor to a risk strategist and portfolio manager who governs the AI's performance.

However, this transformation will necessitate a shift in skill sets. Underwriters will need to become adept at collaborating with AI systems, interpreting their outputs, and intervening when human judgment is required. This human-in-the-loop model is seen as essential for ensuring governance, managing exceptions, and maintaining the institutional knowledge that AI models lack.

Navigating a New Frontier of Risk and Regulation

While the potential for efficiency gains is substantial, the move toward autonomous underwriting also introduces a new set of challenges. As AI agents take on more decision-making authority, the issues of data bias, model transparency, and regulatory compliance become paramount. An AI trained on historical data may inadvertently perpetuate past biases, leading to unfair or discriminatory outcomes if not carefully monitored.

The 'black box' problem, where the reasoning behind an AI's decision is not easily understood, presents another hurdle. Insurance is a heavily regulated industry, and carriers must be able to explain and justify their underwriting decisions to regulators and customers. Ensuring that these autonomous systems are transparent and their logic is auditable is a critical challenge that developers and adopters must address.

Furthermore, granting AI agents access to multiple systems and sensitive data introduces new security considerations. Protecting this information and ensuring the agents operate within secure, well-defined parameters is crucial to prevent both errors and malicious exploitation.

A Strategic Play in the Race for Intelligent Insurance

Convr's launch places it at the forefront of a burgeoning trend. Market analysts predict rapid growth in the adoption of Agentic AI, with Gartner forecasting that by 2028, at least 15% of day-to-day work decisions will be made autonomously through this technology, a dramatic increase from virtually zero in 2024. The insurance industry, with its data-rich environment and complex decision-making workflows, is a prime candidate for this transformation.

The competitive landscape is heating up as numerous insurtech firms and even established tech giants begin to explore agentic capabilities. Convr's strategic focus on deploying pre-built, user-friendly agents specifically for commercial P&C underwriting positions it as an early mover in this specialized market.

"Unlike traditional automation tools that wait for user commands... Agentic AI workflows proactively gather data, flag risks, fill forms and recommend actions – operating much like a digital team member within the workbench," Stammen stated. This proactive capability is what Convr is betting on to deliver a competitive advantage, accelerating the industry's long-awaited shift from manual processes to a future of truly intelligent, technology-driven underwriting.