Just raised $7 million to solve insurance talent crisis through AI

The insurance industry is facing a shortage of personnel. Professionals known as underwriters (professionals in charge of assessing risks and deciding whether an insurer should accept or reject a policy, as well as defining the conditions under which it is insured) are retiring, fewer and fewer young professionals are joining the business, and companies are trying to fill the gap with workflow management tools. At the same time, the volume of applications is growing. The gap between the industry's needs and its capacity to respond is widening rapidly.

What does a subscriber do?

An underwriter is an insurer's professional in charge of analyzing the risks presented by each insurance application. His main function is to determine whether the company should accept that risk, under what conditions and at what price.

To make this decision, he evaluates technical information, the client's background, claims statistics and internal rules. Based on this analysis, it defines coverages, exclusions, limits and premiums, ensuring that the business is profitable and sustainable for the company.

In addition, the underwriter works together with producers, brokers and other internal areas, resolving doubts and adjusting conditions when necessary. It is a key role because it balances the commercial need with the financial security of the insurer.

How can artificial intelligence help the insurance industry?

Artificial intelligence has arrived at an opportune moment. However, the opportunity does not always imply a clear strategy.

Founded in 2020, Pibit.AI is driving a transformation within the industry. The company expanded its proprietary subscription platform, CURE, which automates data extraction, enrichment and risk identification. It also gives subscribers a unified workspace. Today, its customers process billions of dollars in applications per year without needing to increase staffing, a major shift for an industry marked by manual review. The company also announced a $7 million Series A investment round led by Stellaris Venture Partners, with participation from Y Combinator and Arali Ventures.

Founder Akash Agarwal watched his father deal with endless paperwork and for years thought the insurance industry was unrecoverable. Eventually, he realized that "the problem was never the industry. Insurance is incredibly unstructured and, for years, everyone assumed it couldn't be automated. Back then, I thought this industry was immutable. Now the technology exists to solve problems that insurers have faced for decades."

The technology managed to catch up. The workforce did not. To move forward without draining its own resources, the industry needs another way to approach the problem.

Here are three steps insurers need to take now

Redesign the role of junior analysts.

The industry needs to transform the work of junior risk analysts. They can no longer bemere data managers, but must act as true analysts. In the past, new talent learned by intensive practice: they reviewed documents, researched risks, enriched applications and developed intuition through repetition. Today, artificial intelligence systems have begun to take over much of those initial tasks. They analyze documents, collect data and detect red flags even before a person reviews the file.

Platforms such as Pibit.AI's CURE clearly show the speed at which this change is progressing. If the core tasks are automated, then the role has to change as well. Junior analysts should focus more on decision making, fundamental analysis and portfolio planning, and less on administrative tasks. From day one, their work should focus on professional judgment.

2. Design a structured training path

Artificial intelligence should accelerate learning, not replace it. Insurers need clear training models to deal with the real complexity of underwriting work: edge cases, ambiguous risks, conflicting signals and situations where human reasoning remains key. Automation can shorten the time needed to process data, but professional judgment is only built with guided practice.

Training programs need to combine the results AI delivers with human review, mentored decision analysis and case-based learning. The new generation of underwriters can't just validate what a machine suggests. It has to learn to understand risk, not become an auditor of automated systems.

3. Make the work motivating

Young professionals do not shy away from the insurance industry because of its difficulty, but because from the outside they see it as monotonous. Policy underwriting seems like a slow, routine process, far removed from the real consequences. Artificial intelligence can change that perception, but only if the industry actively rethinks how it works.

Pibit.AI customers in different market segments, such as HDVI, Shepherd Insurance, RMS Insurance Brokerage, Kineticand Method Insurance Company, have already begun to see the operational impact of incorporating this technology. They reported much faster underwriting cycles, higher productivity per underwriter and improved claims performance. For insurers and general insurance agencies (MGAs), these kinds of results translate into more capacity, sustained growth and a clearer reading of risks.

Adam Price, CEO of Kinetic, noted that the platform helped his team handle a very high volume of annual claims without increasing operating costs. Because of that, they were able to grow premiums significantly, as they can respond more quickly and consistently. "Pibit.AI helps us manage over $1 billion worth of requests...because we can get quotes and quotes in an agile way," he said.

What's next?

The industry is at an inflection point. Newer underwriting agencies and brokers adapted faster, driven by the need for specific tools for specialized risks. Large insurers also started to move in that direction, not on their own initiative, but because falling margins - caused by tighter combined ratios - made any inefficiency unsustainable. Artificial intelligence is already becoming the new standard.

However, adopting technology is not the same as evolving. AI can make insurance underwriting more agile, accurate and scalable. But it cannot train a new generation of professionals. Nor can it convince anyone to join an activity that still conveys the feeling of belonging to another era.