Research Report
How insurers drive revenue by deploying AI with intent
Five actions turn ambition into growth
5-minute read
June 24, 2026
In brief
- When applied strategically, AI presents insurers with a game-changing opportunity to shift from reactive service providers to proactive enterprises.
- To understand how to maximize the return on investment of AI in insurance, we surveyed 263 senior executives across Life, Commercial, and Personal P&C.
- Five actions set leaders apart. Research reveals that those who employ a combined AI, business and people strategy will gain the competitive edge.
The critical context
Eighty-one percent of the organizations we surveyed have achieved at least a 5% improvement in gross written premiums so far from data and AI initiatives across their organizations, with 7% achieving improvements over 20%, driven by better pricing, personalization and cross-selling.
As insurers continue using AI to improve the bottom-line, they’re also achieving faster underwriting cycle time and improving accuracy and pricing, resulting in lower loss ratios. They’re doing this by scaling repeatable, high-value use cases in areas such as underwriting and claims where data is stronger and returns are clearer.
However, our survey found that less than a third (32%) of insurance executives placed ‘Driving revenue growth and business expansion’ in their top three areas driving their AI and data investments.
32%
of insurers prioritize revenue growth and business expansion
In most cases, the enterprise as a whole is still missing out. It’s time to begin taking a more holistic approach. Doing so would drive revenue growth, business expansion and productivity targets far more purposefully; it would also address the need for sustainable, inclusive insurance.
Research snapshot
To explore the potential impact of AI in all its forms in insurance and discern how to maximize its return on investment, we surveyed 263 senior insurance executives (133 Property & Casualty; 130 Life & Annuity) across the Americas, Europe and Asia, and conducted in-depth interviews with 15.
01
Align AI use to the business strategy
to ensure it contributes directly to enterprise-wide goals
Insurers need to treat AI as a business capability tied directly to P&L outcomes. This requires adopting business-led, performance-driven AI models and aligning strategy, investment and execution to scale use cases across the enterprise rather than within isolated functions.
23%
of insurers have achieved enterprise-wide AI integration.
02
Expand AI skills across the workforce
to combine technical and business knowledge
“People readiness is more difficult than the technology itself. The challenge is helping employees see AI as an enabler, not a threat.” — Senior Technical Architect at a large global insurer
83%
of insurers report moderate to severe gaps in AI–business translation skills.
03
Evolve the talent ecosystem
to include people-led agent-to-agent workflows
Instead of adding AI to existing workflows, Zurich Spain has redesigned core processes so they can be executed end‑to‑end by AI, integrating decision‑making, routing, data enrichment, and exception handling within a single operating model. The program stands out for pairing workflow transformation with governance and integration to deliver faster service, lower cost, and broader enterprise adoption. Quotation turnaround reduced from hours/days to minutes, boosting conversion rates and broker satisfaction. Plus nearly 90% of employees use AI every day, supported by dedicated generative AI trainers.
68%
of insurers believe integrating AI agents into core workflows will transform roles.
04
Adopt a two-speed data strategy
to modernize legacy systems while supporting AI technologies
Insurers need a two-speed strategy, where short-sprint wins deliver immediate efficiency gains while the organization builds enterprise-grade capabilities over the longer-term for sustained value creation.
“There’s a ‘garbage in, garbage out’ reality. AI use cases are actually helping expose the inconsistencies that need to be fixed first.” — Director of Enterprise Initiatives at a large insurer
50%
of insurers cite legacy integration as their primary challenge when it comes to deploying appropriate data and AI at scale.
05
Formalize a proactive compliance mindset
to turn ethical design into a competitive advantage
“We’re establishing frameworks that ensure compliance readiness—when new regulation comes, we’ll already be there.” — Global Head of Data Management at a large global insurer
56%
have already implemented formal AI governance frameworks, establishing the industry as a leader in responsible AI development.
Slow and steady doesn't win this race
The majority of insurers plan to continue increasing AI investment at a measured pace, with spending patterns that favor steady expansion over transformation. This approach will drive incremental gains, but bolder moves are needed to secure lasting advantage. The next maturity leap in AI use will have far greater implications for future success.