The pace of AI adoption is accelerating across almost every business. For insurance, an industry often characterized by legacy systems and caution, this moment represents a tipping point.

AI introduces a strategic opportunity. It asks insurers to rethink how they operate, how they serve customers, and, crucially, how they build the teams that will carry them into the future. The winners won’t be those who wait for clarity; they’ll be the ones who act with intent and intelligent risk-taking, investing in the right people, structures, and partnerships to make AI work for them.

From data to disruption: How AI is reshaping insurance

At the core of AI is data. In that sense, insurance is uniquely positioned to lead in the age of the bot. While insurance is not the most technologically advanced industry, it has a historical reliance on the ability to capture, analyze, and act on data in order to be profitable.

Risk profiling, pricing, underwriting and claims – all of these hinge on data quality and interpretation. And this deep-rooted dependency is what’s becoming a competitive advantage.

Over the last five years, we’ve seen the emergence of new leadership roles, such as the Chief Data Officer and Chief Data Scientist. These functions, once rare, are now central to any forward-thinking insurer. Increasingly, they’re also becoming the natural home for AI strategy and oversight, bridging the gap between technical capabilities and commercial application. These are the leaders who can take AI from buzzword to business asset.

Where AI is gaining traction

While some AI use cases still feel futuristic, many are already transforming the insurance lifecycle. The most obvious is the automation of labor-intensive, manual tasks, and the opportunities for AI here are seemingly endless.

Some of the key AI use cases we hear from our clients are:

• Underwriting: AI is being used to automate simpler underwriting decisions, freeing underwriters to focus on complex, high-value cases that require human judgment.
• Claims: In lower complexity scenarios, AI tools are accelerating claims handling, including triaging, validating and even settling cases at speed.
  Operations and HR: From automating administrative tasks to supporting recruitment processes, AI is already streamlining internal functions.

What these examples have in common is simple: AI isn’t replacing people, it’s enabling them. It’s reducing the friction of manual, repetitive tasks and giving experts more time to apply their expertise. In a people-driven sector like insurance, this distinction matters.

Despite the dramatic headlines, we’re not looking at a future of brokerless transactions or robot-led underwriting any time soon. Just ask any seasoned underwriter if their client relationships can be replicated by an algorithm. You’ll get a firm no.

Waiting on regulation vs. building AI readiness

All this said, uncertainty is a barrier. A common reason insurers hesitate to implement AI at scale is the lack of regulatory clarity. Firms are waiting for standards to be defined before investing in tools or talent. It’s an understandable instinct, but also a risky one.

Regulation will catch up. It always does. But firms that wait for the rulebook before they act are likely to find themselves left behind. Now is the time to build internal capabilities, frameworks and controls, led by data governance and security functions like the Chief Information Security Officer (CISO).

The most forward-thinking organizations are testing and learning today, creating agile governance models that allow them to adapt as regulation evolves.

Insurtech’s role (and the rise of AI-as-a-service)

For traditional insurers who may not have the resources to build bespoke AI systems from scratch, the rise of insurtechs is a milestone moment.

These nimble, innovation-led companies are developing niche AI capabilities tailored to the industry’s needs. For example, in areas like claims automation, AI can now handle standard or low-risk cases from start to finish, allowing adjusters to focus on high-severity or contentious cases. This doesn’t just reduce time and cost; it mitigates risk and improves service.

Equally important is the shift toward AI-as-a-service. An expanding ecosystem of specialist providers is enabling insurers to access advanced AI functionality without major infrastructure overhauls, which democratizes access to innovation and shortens the path from idea to impact.

The talent gap: Insurance needs new minds

All of this potential hinges on people. We’ve had huge success bringing digital, data and advanced analytics talent into insurance from sectors that are considerably more advanced – like tech and media. It’s not a hard sell. For us, the key attraction point for candidates has been the scope of opportunity to make a meaningful impact in an industry that’s ripe for transformation.

The real challenge lies in identifying talent that can truly translate their skills into solving insurance-specific problems. It’s one thing to code a brilliant model, it’s another to understand how that model performs in the context of risk tolerance, regulation and client trust.

That’s why diversity of thought in leadership is so essential. In insurance, where things have largely been done the same way for decades, we need disruptors – in the form of senior talent who aren’t afraid to challenge the status quo, who will question the “why” behind processes and who won’t accept “because we always have.”

The next frontier: Internal AI academies?

We have previously seen a similar shortage of talent when “new” functions were created. Five years ago, it was Data Science. To fill that gap, some firms created internal data science “universities” to cross-train existing staff, build communities of practice and develop long-term capability in-house.

I would not be surprised to see a similar model emerge at some of the larger global insurers when it comes to tackling the AI talent gap.

As demand for AI fluency grows, firms that invest in building internal knowledge will be best positioned to scale responsibly. Internal AI academies or capability programs could help insurers fix the skills deficiency, accelerate adoption and embed AI thinking into every function.

AI is a partner, not a threat

In insurance, AI offers immense potential to elevate human expertise. It can bring us closer to customers, accelerate decision-making and reduce operational drag. But it cannot replace trust, or replicate judgment, or build relationships.

We should be wary of the more outlandish fears – like brokers being replaced by bots. That narrative misunderstands what makes this industry work while preventing it from reaching its full potential.

The firms that will thrive in the AI-powered future are those who act now. To speak about building that team (one that can lead, adapt and thrive in this new era) contact me directly. Let’s talk talent.