Crafting the ideal agent profile

AI-powered recruiting tools begin by analyzing the traits of top-performing agents, including customer retention rates, policies sold, and geographic reach. Many insurers already house extensive internal data on their workforce—now is the time to put it to good use.

This internal data can then be cross-referenced with external factors such as prior sales experience, education history, professional networks, and family background in insurance. These metrics amalgamate to form an “ideal agent profile.”

By comparing candidates against the ideal agent profile, insurers can generate a clear ranking based on how closely each prospect aligns with key traits. This ranking allows insurers to allocate their time and resources more efficiently, focusing on candidates with the highest potential.

AI-powered recruitment tools don’t just evaluate overall potential—they also predict where candidates will fit best within the organization once hired. For example, agents transitioning into insurance from industries such as retail, real estate, or financial services may excel in roles such as customer retention specialist, sales producer, and commercial insurance advisor, respectively.

Beyond career background, the algorithm can analyze personality traits—such as persistence, follow-up skills, and comfort with digital tools—to help determine which roles new agents are most likely to thrive in.

Be mindful of bias

While AI-powered recruitment offers clear advantages over its manual counterpart, it isn’t a panacea, and it falls short of perfect, especially when it comes to bias.

The algorithm attempts to determine which traits actively drive an agent’s success (causation) and which are merely associated with it (correlation). However, it can sometimes mistake one for the other.

For example, if an insurer has historically hired more male agents, an AI-driven model might unintentionally favor male candidates by default, reinforcing existing disparities rather than correcting them.

To counteract this, insurers must continually audit their AI-driven recruitment models to ensure that selection criteria are based on job performance rather than demographic patterns. This requires greater transparency in data collection and algorithmic decision-making.

Additionally, capable human capital is needed to guide AI in distinguishing signal from noise.

First recruitment, then overhaul onboarding and training

Ideally, AI-powered recruitment should be just one component of a broader effort to optimize onboarding and training. When these two functions remain outdated, insurers risk alienating the valuable agents they’ve already invested in.

This is especially important because younger generations often stereotype insurance as a stuffy, Luddite field. Demonstrating that the industry is tech-forward from day one can be a powerful recruitment and retention strategy.

Using AI to streamline onboarding involves suggesting training coursework custom-tailored to new hires’ specific knowledge gaps. It can also automate licensing and compliance verification, pre-fill application and appointment paperwork, streamline background checks, and seamlessly integrate new agents into quoting and CRM systems.

Onboarding shouldn’t feel like pushing new agents off a cliff and hoping they’ll fly—it should be more like gradually removing the training wheels. For example, if an agent struggles with understanding policy exclusions or mastering CRM tools, AI-powered onboarding can identify these weaknesses before they lead to reputational damage for the insurer.

By continuously reinforcing learning in key areas, AI helps create more well-rounded agents while reducing the burden on managers and training personnel.

Related: Clients open to AI: Advisors encouraged to embrace technology, study finds

Grappling with the talent crisis

The insurance industry is facing a talent crisis. Over the next 15 years, half of the current workforce is set to retire, leaving more than 400,000 positions unfilled. Yet, the next generation isn’t eager to step in—less than 4% of millennials would even consider a career in insurance.

Even those from the younger generation who are interested in insurance often become disillusioned by the industry’s outdated inefficiency and resistance to change. Many leave within the first two years—before they reach the threshold of profitability for their agency. To prevent this, insurers can leverage AI-driven analytics to identify new hires at risk of leaving and intervene proactively.

For instance, an AI model can track how often a new agent engages with training materials, logs into the CRM, and follows up with leads. If these metrics indicate disengagement, the system can flag the agent for additional support or intervention.

However, the AI model doesn’t limit its real-time monitoring to low performers—it also identifies top producers, making them prime candidates for targeted coaching and mentorship programs. This ensures they have a clear path for advancement, don’t stagnate, and receive the recognition and rewards they deserve—preventing them from seeking opportunities elsewhere.

Freeing recruiters to do what they do best

While AI-powered recruitment seems like an obvious choice for the insurance industry, large-scale adoption has been slow—whether due to resistant executives or the growing pains of refining algorithms.

Early 2024 estimates place the market value of AI recruitment technology at $661.5 million, with projections to reach $1.1 billion by 2030. It’s an approach with significant room for growth. An AI-driven overhaul of recruiting shouldn’t alarm recruitment personnel or fuel unfounded fears of large-scale layoffs.

These models are just tools—they still require human expertise to operate effectively. Recruiters should embrace them, as AI frees up time to focus on the human elements: building relationships with new recruits, pitching opportunities, making agents feel welcome, and mentoring them once they’re onboard.

Phil Brown is VP of Strategic Alliances at Vymo, a global insurance IT platform provider. He can be reached at [email protected]