The insurance industry is undergoing a significant transformation driven by advancements in artificial intelligence (AI). Our latest thought leadership piece, "Intelligent Insurance: A Blueprint for Creating Value Through AI-Driven Transformation," explores how AI is reshaping the insurance landscape, offering new opportunities for innovation, efficiency, and customer engagement.
AI has been a part of the insurance industry for some time, but its adoption varies significantly based on insurance type, geography, and the distinction between legacy insurers and insurtech disruptors. The emergence of generative AI, along with the next wave of autonomous and agentic AI systems, is unlocking entirely new possibilities for innovation across the sector.
However, while some insurers are doubling down on AI investment to drive competitive advantage, others remain cautious due to regulatory concerns, legacy constraints, or uncertainty about AI’s long-term impact on their business models.
This growing divide between AI leaders and more conservative adopters will shape the future trajectory of AI-driven transformation in insurance.
Uses of AI in non-life insurance
Non-life insurers, dealing with high-frequency claims in areas like auto and home insurance, have been using AI primarily for back-office functions such as fraud detection, real-time risk assessment, automated claims processing, and dynamic pricing. Their focus is on speed and operational efficiency, using structured external data such as telematics, Internet of Things (IoT), and geospatial risk analysis.
In contrast, life insurers managing long-term risks rely on biometric, medical, and behavioral data to assess longevity and morbidity. AI is revolutionising their underwriting processes by automating risk segmentation, integrating electronic health records, and utilising predictive analytics to refine policy pricing and assessment.
What can AI do for insurers?
AI is more than a technology investment for insurers — it is a transformative catalyst for redefining strategy, culture, and operations. To fully unlock its potential, insurers must overcome inertia, embrace its possibilities, and embed AI as a core driver of customer-centric and sustainable growth.
Life insurers are integrating wearable data and wellness tracking to personalise policy pricing, rewarding healthy behaviors. AI is also improving claims automation by identifying fraud, analysing death certificates, and streamlining payouts through machine learning.
Beyond underwriting and claims, AI is transforming longevity modelling and regulatory compliance in life insurance. Predictive analytics powered by AI can assess life expectancy, detect disease onset, and optimise risk stratification, enabling insurers to refine pricing and payout structures.
However, these solutions are often developed to solve a specific problem, but there is an opportunity to quickly adjust for wider use across the value chain. Generative AI and autonomous agents could empower organisations to enhance actuarial models, deliver personalised insurance cover, or even increase the pace of insurance claims.
But this will likely require an enterprise-wide view, breaking down organisational silos and using AI to monitor and mitigate its own risks.
AI’s role in decision-making
The rise of agentic, autonomous AI agents represents a fundamental shift in how insurance companies will operate, interact with customers, and manage risk. Unlike traditional AI, which primarily enhances efficiency through automation and analytics, these next-generation agents can independently make decisions, execute complex tasks, and continuously learn from interactions.
In insurance, this means policies that dynamically adjust based on real-time risk factors, claims that are processed and settled instantly without human intervention, and customer service that is hyper-personalised, context-aware, and available 24/7.
The potential extends beyond operational improvements — agentic AI can redefine entire business models, enabling insurers to proactively mitigate risk, optimise pricing dynamically, and provide unprecedented levels of customer engagement.
AI investment concerns
However, our research finds that insurers are still grappling with legacy operating models, technical debt, and linear workflows, which are ill-equipped to handle the dynamic nature of AI innovation.
Data is fragmented and often locked in functional-specific systems. Rigid hierarchies and siloed functions create choke points that impede cross-functional collaboration, slow decision-making, and limit agility.
Concerns about the rapid pace of technology development and caution over the AI-specific risks are causing hesitancy: 75 percent of insurance executives in our survey are concerned that investments they make now may be rendered obsolete in the near future.
Insurers are also hesitating when it comes to build or buy decisions and worried that a vendor may release a better version. When coupled with concerns over the unknown risks, AI leaders are unsure where and when to focus their investments.
How insurers should proceed
To navigate these challenges and unlock AI’s transformative potential, insurers must design an AI strategy that aligns with core competencies and unlocks value. This involves establishing a bold vision for AI that guides a disruptive transformation roadmap, building trust into the transformation process, creating sustainable technology and data infrastructure, and fostering a culture that uses AI to uplift human potential.
By addressing these barriers progressively, insurers can unlock AI’s transformative potential while mitigating risks. This framework helps ensure that AI becomes a sustainable and strategic enabler for long-term growth, competitiveness, and resilience.
If you're struggling to integrate AI into your insurance business, contact our team below. With years of experience in the insurance sector, we understand the challenges and opportunities you face. Get in touch today; we'd be delighted to hear from you.
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