Artificial intelligence is no longer a distant idea in talent acquisition. From automated CV screening to chatbots handling candidate queries, AI tools are fast becoming part of recruitment processes. For insurers facing talent shortages and growing competition, the promise of faster, more efficient hiring is tempting.

But as AI’s influence grows, so do the challenges. While these tools can support high-volume hiring, their limitations become clearer when applied to senior, C‑level, and board appointments—roles that require nuance, judgement, and relationships that technology alone cannot deliver.

What should insurance leaders know about AI in recruitment as we move into 2025? And how can they balance innovation with responsibility?

The Growing Role of AI in Insurance Recruitment

Insurers are already experimenting with AI in areas such as:

• Screening thousands of applications to identify promising candidates
• Using chatbots to answer basic candidate questions
• Applying predictive analytics to assess potential fit based on historical hiring data

A 2024 HR Tech Insights survey found that 78% of large enterprises now use AI in recruitment, up from 55% in 2022. That shows rapid adoption of technology across the board. Meanwhile, another report noted 44% of organisations use AI in talent acquisition, and it can reduce time-to-hire by roughly 50%.

These tools undeniably help tackle administrative bottlenecks, but senior hiring requires a different level of care—where AI’s limits become most evident.

Top Challenges of Using AI in Talent Acquisition

1. Bias in AI Algorithms

AI systems are trained on existing data—and that data often carries systemic biases. Research from the University of Washington found that large language models favoured white-associated names 85% of the time, female-associated names just 11% of the time, and never preferred Black male-associated names over white male ones.

2. Lack of Transparency and Explainability

Many AI recruitment tools are "black boxes"—they make decisions without offering clear explanations. That becomes a major problem in senior hiring, where executives and boards expect clarity and accountability. A survey from ResumeBuilder found 85% of hiring managers believe AI is valuable for screening, but the final decision should always rest with humans .

3. Regulatory and Compliance Pressures

Across the globe, regulators are stepping in. The EU's AI Act labels hiring algorithms as "high risk," demanding strict oversight. In the U.S., the EEOC has issued guidance on avoiding discriminatory outcomes from AI tools. For insurers operating in multiple regions, missed steps could lead to legal or reputational fallout—especially for high-profile senior appointments.

4. Candidate Experience Risks

Automation can speed things up, but it may also make processes feel detached. Scheduling hiccups, for example, can push senior candidates away. According to a HR Dive study, 62% of senior-level candidates in the U.K. withdrew from hiring processes due to delays. Around 54–64% of senior candidates also report feeling less engaged or recommending the employer less if faced with poor communication. This shows why the candidate experience really matters at the top levels.

5. Skills Gaps in HR Teams

It's not plug-and-play. HR teams need skills to manage and understand AI tools. Without that knowledge, there's a risk of over-reliance and missing human insights—especially when evaluating leadership qualities. Investing in upskilling is essential, but even then, human judgment remains vital for senior-level hiring.

Why Senior Hiring Requires a Human Approach

AI can process data and spot patterns. But senior hiring is about understanding cultural fit, emotional intelligence, leadership style—qualities that don’t appear in CVs or data dashboards.

At the C-suite and board level, success depends on relationships, strategic alignment, and discretion. Executives expect a process that reflects the complexity of the role and the organisation’s culture. These human dimensions are areas where AI still falls short.

Best Practices for Insurance Leaders Navigating AI in Recruitment

To strike the right balance, insurers should:

• Audit AI systems regularly for fairness and accuracy.
• Choose ethical vendors who focus on transparency and bias reduction.
• Keep humans involved during key decision stages, especially for senior roles.
• Combine AI with personal engagement to ensure the candidate experience feels tailored and respectful.

Looking Ahead: The Future of AI in Insurance Talent Acquisition

AI will continue to evolve, helping insurers manage high-volume hiring and administrative tasks. As tools become more advanced, they may even help map talent pools or highlight emerging skill gaps.

However, leadership hiring will always demand human connection. These appointments are too nuanced, too strategic to rely on algorithms alone. Insurers that combine AI’s efficiency with expert-led search practices will be best placed to build strong, future-ready leadership teams.

Final Thoughts

AI has its place in modern hiring, but it isn’t suited for every type of role. Senior, C‑level, and board appointments need personalised, relationship-driven processes. At Eliot Partnership, we blend deep insurance sector experience with a tailored approach to help clients find leaders who not only meet requirements but also shape the future of their organisations.

At the end of the day, people still hire people.