AI is forcing a workforce rethink: is insurance ready to adapt?

AI is redefining the insurance workforce, pushing leaders to rethink roles, skills and accountability to stay competitive in a changing industry.

In brief

• AI is redefining the insurance workforce, shifting how judgment, accountability and value creation are distributed across roles, functions and operating models.
• As generative and agentic AI mature, insurers must move beyond automation to redesign insurance work around human AI collaboration and decision stewardship.
• Insurers that treat AI as a workforce transformation—not a technology upgrade—can build a more resilient, future ready insurance workforce.

Insurance roles and skills have remained largely static or evolved slowly for years. That pace is changing. Now, the rise of generative and agentic AI across the insurance value chain has the potential to cause significant disruption for the insurance workforce. 

That could affect everything from how insurers interact with policyholders, to the skills needed in the workforce and the volume of roles required to support. In many cases, these changes will also materially affect productivity, cost structures and service quality, making workforce decisions inseparable from financial and customer outcomes.

To win in the long run, insurers should think beyond technology investments to create the conditions necessary to convert tools to performance and build talent workforce strategies accordingly.

AI is poised to reshape insurance roles and skills 

While AI has dominated Canadian insurance headlines lately, the real business and workforce impacts have remained limited. That will not last. 

Since 2024, generative AI has moved beyond experimentation and begun to embed itself in enterprise workflows, going beyond traditional AI capabilities like data prediction and analysis to creating new content such as text, images, code and ideas, and augment human productivity. 

As these tools mature, insurers should expect measurable gains in cycle time reduction, throughput and decision consistency — provided AI is embedded into day-to-day work rather than used sporadically.

Agentic AI takes this momentum even further. This class of AI systems can actually perceive its environment, reason about it and take actions to achieve specific goals. Simple AI agents can now perform the role of a personal assistant; more complex agents might eventually steer a self-driving vehicle.

Within insurance, many expect agentic AI to enhance customer experiences, better identify risks, make decisions about pricing or claims and even lower cost bases. As those capabilities become mainstream, they’ll likely impact the workforce in two main ways:

From augmentation to agentic task ownership

Work augmentation

For example, humans can use gen and agentic AI to complete tasks, cut down manual labor and speed up work. We’re already seeing this across industries. For example, 54% of employees are using AI for basic tasks like searching for information; 38% say they use it to summarize documents. In insurance, this form of augmentation is often the first step towards productivity uplift, but on its own may not deliver sustained value without changes to roles, incentives and performance expectations.

Agentic task ownership

Agents will become part of the team. With human oversight, these agents can reduce workload, speed up processes and more. These more advanced use cases can create even greater value, but only 5% of employees are currently using AI as a thought partner in this way. As agentic task ownership expands, insurers will need to be explicit about where accountability sits, when human judgment must override AI outputs and how regulatory expectations for explainability are met.

How AI is reshaping roles across insurance

These capabilities are starting to change insurance, an industry that has long relied on manual work despite past technology investments. 

The World Economic Forum shows insurance has seen the biggest increase in AI training completion, rising 22% from 2023 to 2025, far outpacing most other industries.

Insurers are also optimistic. The EY-Parthenon CEO Outlook Survey shows 45% of insurance leaders expect AI and digital investment to be the most important driver of resilience and adaptability. But optimism alone isn’t enough. Many organizations still struggle to move beyond pilots due to skills gaps, technical debt and unclear ownership.

To realize that potential, though, insurers will need people who are capable of extracting far more value, using AI as a thought partner rather than a tool. That requires a culture shift that learning alone cannot achieve. Without connecting technology with behaviour change, insurers run the risk of investing in training their employees only to see them default to the same old work habits. 

To succeed, insurers need to design a way of working that supports AI innovation, provides effective resources and empowers people to experiment purposefully with well-defined parameters. 

AI is set to reshape roles and skills

Within insurance organizations, emerging AI shifts are redefining what needs to happen for teams to work effectively and meet high customer expectations. In turn, leaders must rebalance where judgment lives and how accountability is distributed. This rebalance will vary by function and maturity, requiring different operating and governance models as AI moves from assisted to supervised and, eventually, agented work. 

This has different implications across functions and teams. For example:

• Sales: As sales become more complex, people must evolve into omnichannel distribution specialists. That means managing and optimizing various distribution channels, from online to mobile to agents, to create seamless customer experiences across all touchpoints. 
• Sales and service teams: They may need upskilling and other support to navigate AI-automated workflows like chatbots and AI assistants. As digital self-service and AI ramp up, we will likely see contact centre and service-oriented role reductions as the war for talent heats up across the front office.
• Underwriting: The introduction of AI-driven tools will require underwriters to focus less on individual risks and comprehensively manage a book of business. Doing so will require additional data skills to address embedded insurance products in nontraditional settings and enhance customer experience.
• Claims: Claims specialists will need more thoughtful workforce planning models as they become “claims concierges,” combining human and digital experience with ownership of the customer journey. We could see a polarization of skills as the middle office moves to a hybrid human-AI operating model. 
• Finance: Finance professionals and actuaries will need better data manipulation, process automation and visualization skills to complement AI capabilities. While these roles have typically been stable, people must now offset increasing regulatory demand by using improved technology. These roles will evolve into financial results stewards, working across finance, actuarial, IT and data to understand results from end to end.
• Data and technology: To achieve AI’s potential, insurers will need to modernize infrastructure so these professionals can effectively use AI and other emerging technologies. They must also go beyond making their people comfortable with AI to improve its responsible use, so they can serve as ethics officers who address bias, fairness and transparency.

Insurers that treat AI as just a technology deployment risk reinforcing existing ways of working and realizing only incremental gains. Those that treat it as a workforce and operating model transformation have an opportunity to unlock step change improvements in productivity, customer experience and resilience. That requires difficult choices: redefining roles, redistributing judgment, investing in new skills while protecting human expertise, and holding leaders accountable for modelling the best use of AI.

This is ultimately a leadership test. The organizations that succeed will be those that make AI a deliberate part of how work is designed, how performance is measured and how trust is built — with employees, customers and regulators alike. The insurance workforce of 2030 is being shaped now, one decision at a time. 

The question for insurers is simple but consequential: are today’s choices preparing people to work alongside AI — or merely adding another tool to yesterday’s model?