AI Upskilling in Insurance: Boosting careers and building business

Why upskill?

The rationale for AI upskilling is increasingly supported by hard data:

• For professionals, AI training can lead to bigger salary increases, faster promotions, and greater job security.¹ 
• For insurers, it can unlock productivity gains,²  reduce operational costs,³  and improve customer satisfaction.⁴ 
• For both, it is a hedge against obsolescence in a rapidly digitizing industry.

For the insurance professional: Salary, security, and mobility

A 2025 survey by Nexford University stated that US professionals who use AI daily earn 40% more than those who do not.⁵  This is more pronounced for younger workers. Among Gen Z employees, 45% of daily users received a promotion in the past year and earn 47% more on average annually than their peers who never use it.⁶  

The rationale behind the data is simple: AI frees employees to focus on strategy, creativity, and decision-making, tasks often linked to raises and promotions. 

The benefits of AI upskilling go beyond short-term financial gains. New career paths in insurance are starting to open for those with AI skills, such as AI ecosystem manager.⁷  Upskilled professionals are also generally more resilient. With 73% of employers prioritizing AI-skilled hires, those with credentials are better positioned to land and keep jobs.⁸   

For the insurer: ROI, efficiency, and engagement

An AI upskilled workforce, combined with other technological improvements, is projected to boost labor productivity by up to 3.4% annually through 2040.⁹  On the other side of the ledger, an AI-empowered employee base could deliver cost reductions of up to 40% through automation and improved efficiency.¹⁰  

That is just part of a multifaceted return on investment for insurers. Other benefits include: 

• Recruitment savings – Upskilling reduces recruitment costs, saving 70%-92% on average compared with hiring a new or replacement employee.¹¹ 
• Retention – 94% of employees say they are more likely to stay at companies that invest in their development.¹² 
• Customer outcomes – When done well, digitally upskilled employees provide a better customer experience. Companies that provided a quality digital experience received higher customer satisfaction scores than those that did not.¹³ 
• Revenue growth – Industries more exposed to AI today had three times higher revenue growth per worker than those in industries without such exposure.¹⁴ 

Insurance vs. other sectors

These outcomes are especially relevant in insurance, where data-driven decision-making is central to high-value activities such as underwriting, claims, and fraud detection. 

The insurance industry faces some unique AI challenges. Insurance is generally keeping pace with other industries in AI training, but there are further opportunities and caveats: 

• Investment – 78% of insurers plan to increase upskilling budgets, slightly ahead of the cross-sector average.¹⁵
• Talent gap – With fewer AI specialists than tech or finance, insurance relies heavily on internal upskilling.
• Dual expertise – Upskilling veteran professionals today creates a rare blend of domain knowledge and technical fluency.
• Ethical edge – Programs such as Deloitte’s include modules such as “Trustworthy AI” that reflect the importance of specialized AI training for insurance’s regulatory environment.¹⁶ 

Compared to sectors such as healthcare and retail, insurance is well positioned to lead in responsible AI adoption. How can insurances professionals gain these AI skills and what avenues can insurers promote to those looking to grow? 

Learning pathways that deliver

The first step for insurance professionals is to make sure they are in the AI arena. This means building a foundation in machine learning, prompt engineering, AI ethics, and regulatory implications. From there, insurance-specific applications – such as GenAI-powered underwriting and fraud detection – require deeper expertise.

Professionals who combine technical fluency with industry-specific expertise are increasingly seen as indispensable. Beyond that, those who can communicate AI’s strategic value across departments are well positioned for leadership roles.

AI upskilling is not one-size-fits-all. Insurance professionals can choose from a range of options based on time, cost, and career ambition. For example: 

Workplace-based training

On-the-job learning offers immediate relevance. Employees can join pilot projects, collaborate with technical teams, and apply AI tools directly to insurance data. This approach builds practical skills while demonstrating initiative.

Professional certificates

Short courses and modular programs offer flexibility. Platforms such as Coursera and Udacity provide insurance-relevant content, while LinkedIn Learning offers more than 150 AI certificates. Specialized programs include:

• CFTE’s Generative AI for Insurance
• LSIB’s AI for Insurance Professionals
• Deloitte AI Academy, which has trained over 58,000 professionals and achieved 40% Gen AI fluency across its workforce¹⁷ 

These programs typically require 4 to 40 hours and often lead to measurable career benefits.¹⁸ 

Graduate programs

For those seeking deeper expertise, university-level programs offer comprehensive training. Examples include:

• UT Austin’s AI & Machine Learning Certificate (six months)
• Columbia University’s AI in Business & Finance Certificate (eight weeks)
• Stanford and MIT’s AI graduate tracks

These programs prepare professionals for strategic roles in data science, risk modeling, and digital transformation. They also are most likely to boost an insurance professional’s career trajectory toward leadership roles. 

Conclusion: A strategic imperative

AI upskilling is more than a career move; it is a growing strategic imperative. For insurance professionals, it is a key that can unlock increased opportunities and career security. For insurers, it is a growth strategy.

As one insurance innovation lead put it, those who do not adopt and learn AI “run the risk of becoming replaceable,” while those who embrace it “reap the benefits.”¹⁹ 

In insurance, that means professionals who blend AI savvy with industry expertise will be in high demand as underwriters, actuaries, claims managers, and executives of the future.

Listen to the Underwriting Evolved podcast featuring co-author Michael Hill on balancing AI innovation with oversight, and contact RGA to explore AI-driven partnerships.