AI Is Reshaping Insurance Recruiting’s Time Economics

By Nathan Brooks

Interview scheduling ranks as the second-biggest time sink in insurance hiring, behind only applicant screening, according to Nathan Brooks. His account shows AI already compressing work across drafting, matching, scheduling and interview preparation, while employers retain responsibility for accuracy, voice and compliance.

Brooks says AI recruiting is top of mind for agencies that want to find good talent faster. Job seekers welcome the technology as well, he says, because the volume of information online can make finding the right career harder.

One sign of that shift is how candidates now approach pay. One of the most common things Brooks's team hears, he says, is: “I went on ChatGPT to ask what I should make.” Brooks cautions against projecting too far because technology changes quickly; his conclusions reflect current uses rather than a distant forecast.

Where AI enters the hiring process

Candidates and companies use AI to write cover letters, resumes, job descriptions and job advertisements. Brooks says the tools ease anxiety for people who lack confidence in creative writing. They also help applicants align their materials with market conventions.

More important for recruiters, Brooks says, the tools are interactive. Users can refine a draft for a specific job, situation and set of keywords rather than start from a generic template or impersonal sample.

For recruiters, this changes drafting from template completion to continuous tailoring. The result is faster production, but the workflow still ends with a human edit.

For employers, AI does not remove editorial responsibility. Brooks advises editing generated job descriptions to carry the employer's voice, avoid appearing to copy another company's advertisement and comply with internal and external regulations.

Resume review calls for more caution. Brooks says it can be hard to tell at first glance whether a CV received AI assistance. He recommends additional vetting when the language seems out of place, does not reflect the standard way insurance professionals speak or conflicts with what the recruiter knows about the market.

How AI changes matching and scheduling

Brooks's team often sees a large, unexpected influx of applications. He attributes much of that pattern to AI that learns job-seeker behavior and then pushes new openings similar to ones they applied to before. He says this can help the employer and candidate when keywords accurately match experience and requirements.

Agency owners, Brooks says, hope AI embedded in agency management systems will eliminate tedious backroom servicing. He expects HRIS and recruiting software to put AI behind three core tasks:

• Resume screening: HR teams want help reviewing incoming applications.
• Candidate sourcing: AI can help teams identify potential candidates.
• Initial interviews: Software can support early conversations with applicants.

AI also appears on company careers pages through features such as “Chat With Us.” Brooks says those tools can match people more quickly with job openings, extending the use of AI into candidate-facing service.

Interview setup is a major target for time savings. Brooks says setting up interviews takes considerable time, second only to screening applicants. Many companies use interview schedulers, while some programs use a virtual assistant for initial phone interviews.

Brooks said, “What I really like are features to summarize interviews.” In his experience, summaries cut documentation work and make previous interview notes available to everyone involved in the hiring process.

What does this change for recruiters and candidates?

AI also changes what happens before a candidate walks into an interview. Candidates can ask it to research a company, compare their skills with a job description and identify likely questions. Practice programs can simulate interviews, and AI can suggest questions for the candidate to ask.

Brooks presents these tools as preparation aids for job seekers. For candidates, that means more research before they speak with a hiring team.

Compensation remains the sharpest change in candidate behavior, in Brooks's view. The salary question often reflects a relocation decision, a cost-of-living comparison or a desire to feel paid appropriately.

Brooks notes that a quick Google search can also generate a large amount of compensation information, although the result may be imperfect. He says hiring leaders should understand the tool because pay remains one of the most uncomfortable topics in interviews and can derail the process.

For recruiters, Brooks's account makes the practical shift clear: AI now touches the chain from the wording of an ad to the questions a candidate asks and the notes left after an interview. It does not remove human judgment: employers still need to test keyword matches against real experience, check regulated content and prepare for pay discussions candidates may already have researched.

Brooks is not forecasting a distant replacement for recruiters. His near-term case is narrower: software can remove documentation and coordination work now, while hiring leaders still own the decisions on job fit, regulated content and compensation.