Skip to content

Talent Strategy Will Shape AI Transformation Success

Author

Lisa Stevens
Director of Executive Development
LIMRA and LOMA
lstevens@loma.org

August 2026

Artificial intelligence (AI) is rapidly reshaping the insurance industry. While insurers are investing heavily in data and technology, few are addressing the most critical factor determining success: talent. AI implementation is not primarily a technology challenge but a workforce transformation.

According to McKinsey, most companies are investing in AI, yet only about 1% believe they have reached maturity, suggesting that the primary gaps lie with leadership alignment and workforce readiness rather than tools. At the same time, Accenture cites that 90% of insurance executives plan to increase AI spending. However, fewer than 10% of companies have significantly redesigned roles to reflect AI opportunities, with only 40% of employees feeling equipped for new ways of working.

This disconnect is impacting outcomes. While AI adoption has moved beyond experimentation, Deloitte finds that 76% of insurers have deployed generative AI in at least one function. Yet, many organizations are struggling to convert use cases into enterprise value. For insurance leaders, success will be determined not by how much they invest in AI, but by how effectively they prepare the workforce to use it.

Rethinking Ways of Working

Insurers must fundamentally rethink how work is accomplished. AI does not eliminate jobs; it breaks them into tasks. Routine activities such as data intake and document processing are increasingly automated, while decision-based work, including risk assessment and complex claims resolution, remains human-led with AI augmentation. Across underwriting, actuarial and claims, work has already shifted toward AI-assisted decision-making models, with new roles emerging.

The transformation is accelerating. PwC research suggests that skills required for AI-exposed roles are evolving 66% faster than other jobs, fundamentally reshaping how organizational capabilities must be developed. At the same time, career paths are changing. Entry-level roles, historically the foundation for growing expertise, are increasingly affected by automation, raising concerns about how next-generation talent will build core capabilities. Rather than focusing on job elimination, executives should focus on task-level transformation by clearly defining what work can be automated or augmented, as well as what remains uniquely human.

Talent Is Business Strategy

As insurers scale AI, a new pattern is emerging: The primary challenge has shifted from technology to workforce capability. Access to skills and the ability to drive adoption at scale are now key factors. Human capital is increasingly the scarcest resource in insurance transformation, requiring the same level of rigor as business strategy. Yet execution remains uneven. McKinsey reports that while 90% of insurance executives acknowledge the need to reinvent workforce capabilities, only 25% have made progress. At the same time, a quarter of leaders cite shortages of skilled talent as a primary barrier to capturing value from AI investments, according to Insurance Business. Organizations that align talent and technology, however, achieve stronger outcomes. In some cases, AI-enabled underwriting and decision-support tools have delivered productivity improvements of up to five times, but only when paired with workflow redesign and intentional workforce enablement.

The New Workforce Emerges

The future workforce is often referenced in research as AI builders, AI translators and AI users. While attention is focused on technical talent, broader and more transformative impacts of AI will be felt across the broader workforce. McKinsey research shows that today’s technologies could automate up to 57% of current U.S. work hours, underscoring that the greatest value will come not just from specialists, but from enabling frontline employees to effectively work alongside AI.

However, AI is not reshaping all roles equally. In insurance and financial services, it is driving the difference between higher value, more complex professionalized roles and more routine democratized roles. This shift is already seen in compensation trends. McKinsey notes that the wage premium for AI skills in financial services is 53%, which is below other sectors, suggesting that the industry is maturing in how it recognizes and rewards AI capability. 

This transformation is not specifically about workforce reduction. Accenture finds that more than 80% of underwriting executives expect AI to create new roles, reinforcing that change is as much about job creation and redesign as it is about efficiency. The future workforce will not be smaller but fundamentally rebalanced toward new skills and human-AI collaboration.

Behind Other Industries

Despite momentum, insurance continues to lag other sectors in workforce transformation. A key challenge is the gap between ambition and execution, with industry research indicating a discrepancy of more than 60 percentage points between AI intent and implementation. Culture and internal structural factors also play a role. While important, industry focus on risk and regulatory compliance can often slow AI experimentation and adoption. These challenges are compounded by legacy systems and highly specialized roles, which limit flexibility and speed. Despite significant investment, many employees feel unprepared to use AI tools effectively and lack confidence in output, resulting in inconsistent adoption.

Learning from Other Industries

While insurance faces unique challenges, the industry does not need to navigate transition alone. Based on peer discussions, lessons can be learned from other industries further along in aligning talent with AI:

  1. Technology leaders treat AI as a core enterprise capability, embedding fluency across the workforce and accelerating adoption while reducing reliance on scarce specialists. Insurers, by contrast, often confine AI expertise to small teams, limiting scale and reinforcing the need to make AI literacy a foundational enterprise competency.
  2. Banks have navigated similar regulatory complexity by integrating compliance, governance and innovation from the outset, enabling faster and more confident deployment. Their experience demonstrates that governance should be built alongside AI as an enabler, not imposed afterward as a constraint.
  3. Retail and e-commerce organizations have rearchitected customer journeys and operations around AI, unlocking real-time decisioning and personalization. This highlights the importance of redesigning end-to-end workflows rather than layering AI onto legacy processes.
  4. Manufacturers have proactively reskilled their workforce to operate alongside automation, improving adoption, retention and resilience. Their approach underscores that reskilling is a strategic investment — not a reactive response to disruption.
  5. Professional services firms have developed translator roles that bridge business and technology, ensuring AI capabilities are applied in real-world contexts. This reinforces the need to accelerate talent to operationalize AI across the enterprise.

Across industries, the leaders in AI distinguish themselves by making workforce transformation a core pillar of strategy.

An Industry-Defining Moment

To accelerate workforce readiness for AI transformation, the industry can take seven actions:

  • Conduct task-level work assessments
  • Build strategic workforce plans aligned with AI investments
  • Scale reskilling programs in AI and data literacy
  • Redesign end-to-end workflows
  • Develop AI translator roles to bridge business and technology
  • Strengthen governance capabilities
  • Lead change with clarity and purpose

AI represents a pivotal opportunity for the industry beyond efficiency — to reimagine how risk is assessed, how customers are engaged, and how value is delivered. Realizing this potential will require more than technology investments. Insurers that lead will be those that understand AI transformation as fundamentally human, demanding new roles, capabilities and ways of working.

Insights based on publicly available research from McKinsey, Deloitte, Accenture and PwC.

 

Did you accomplish the goal of your visit to our site?

Yes No