Poll results: Geopolitical concerns make way for AI and technology risks

The risk management landscape is undergoing a profound transformation, as revealed by poll results from The Leadership Forum, RiskMinds Insurance, and the Global Risk Regulation Summit.

While geopolitical uncertainty continues to dominate the concerns of risk leaders, a new force is rapidly reshaping priorities: artificial intelligence and technology-related risks are claiming an increasingly prominent position in the risk management agenda.

Key takeaways

• Geopolitical uncertainty remains the top concern at 31.8%, but technology and AI-related risks are rapidly gaining prominence in risk management priorities.
• In the insurance sector, technology risks top risk managers’ concerns, with 40.4% focusing on managing technology, AI, and cyber risk.
• Traditional tasks consume most resources in insurance: RCSAs (34.2%) and risk MI reporting (31.6%) dominate resource allocation despite growing emphasis on innovation.
• AI's greatest potential in insurance lies in personalisation, stress testing, and underwriting optimisation, each capturing 22.2% of responses for revolutionary risk management applications.
• Skills shortage is the primary barrier to safe AI scaling in the insurance sector, with 44.7% citing lack of qualified personnel as the most pressing challenge.
• Regulatory engagement in AI adoption is largely absent: 60.7% report regulators in "wait and see" mode, yet almost all respondents desire dedicated AI regulation or clarification for existing regulations that may apply to AI.
• Critical gap exists between industry needs and regulatory support, creating opportunity for collaboration to enable safe, responsible AI innovation in risk management.

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Geopolitical uncertainty still reigns supreme

Geopolitical uncertainty remains the paramount concern for risk leaders, with 31.8% of respondents identifying it as their top worry. This persistent anxiety reflects the ongoing volatility in global affairs, trade tensions, and regional conflicts that continue to impact business operations worldwide. However, compared to 2024’s survey where 60% of respondents identified geopolitical risk as their biggest challenge, the margin by which geopolitical concerns lead has narrowed considerably, signalling a fundamental shift in the risk landscape.

Close behind geopolitical uncertainty, cyber and technology resilience concerns capture 20.9% of responses, while responsible use of AI and AI governance accounts for 12.8%. Together, these technology-related concerns represent a substantial portion of risk leaders' attention, marking a departure from previous years when such issues occupied a smaller share of the risk agenda.

Technology takes centre stage in the insurance sector

The insurance sector presents an even more dramatic picture of this technological shift. A striking 40.4% of insurance risk managers identify managing technology, AI, and cyber risk as their top-of-mind concern. This elevated focus reflects the insurance industry's unique vulnerability to technological disruption and cyber threats, as well as its growing recognition of AI's transformative potential.

The efficiency of the risk function emerges as the second-highest concern at 32.7%, suggesting that insurance professionals are grappling with the dual challenge of managing new technological risks while simultaneously optimising their operational effectiveness. Managing capital effectively rounds out the top three concerns at 17.3%, while traditional worries like climate risk management and ESG capture only 1.9% of responses, indicating a clear prioritisation of immediate technological challenges over longer-term environmental considerations.

Resource allocation in insurance: The burden of traditional tasks

Despite the growing focus on AI and innovation, the most resource-intensive activities remain firmly rooted in traditional risk management practices. Risk and control self-assessments (RCSAs), including control testing, consume the largest share of first and second line resources at 34.2%. Risk management information (MI) reporting, including Own Risk and Solvency Assessment (ORSA), follows closely at 31.6%.

This concentration of resources on foundational risk activities highlights a critical tension: while organisations recognise the importance of innovation and AI adoption, they still need to be heavily invested in maintaining traditional risk frameworks due to regulatory expectations. As many industries are finding new use cases for generative AI to improve on efficiencies, can traditional tasks like these also be innovated? The challenges of this becomes apparent as we find out more from the insurance sector and the wider risk regulatory community attending RiskMinds.

AI's revolutionary potential: Beyond the basics

When it comes to AI's transformative impact on insurance risk management, respondents see the greatest potential in areas distinct from their current resource-intensive tasks. Three use cases tie for the top position at 22.2% each:

• hyper-personalisation of products for cross-selling and up-selling
• stress testing and scenario analyses
• underwriting optimisation

These applications represent AI's ability to enhance decision-making, improve customer targeting, and strengthen analytical capabilities.

Reporting and data management follows at 17.8%, suggesting recognition of AI's potential to streamline the very activities that currently consume significant resources. Personalised customer outreach and marketing captures 6.7%, while regulatory management (4.4%), KYC/customer onboarding (2.2%), and fraud management (2.2%) round out the perceived opportunities.

The challenge of safe AI scaling in the insurance sector

The path to realising AI's potential is fraught with obstacles. The most pressing challenge, identified by 44.7% of respondents, is the shortage of skills and people within risk functions who possess the ability to implement AI safely. This skills gap represents a fundamental barrier to AI adoption and highlights the urgent need for talent development and recruitment strategies.

Concerns about appropriate risk management, controls, and oversight to enable "human in-the-loop" supervision account for 26.3% of responses, reflecting anxiety about maintaining adequate governance as AI systems become more autonomous. The need for fit-for-purpose governance and adjustments to existing frameworks captures 18.4%, while compliance concerns and alignment with external parties represent 10.5% of responses.

The regulatory gap: A call for guidance

Perhaps most striking is the disconnect between industry needs and regulatory engagement around AI adoption and governance. A substantial 60.7% of respondents describe their regulator as being in a "wait and see" mode, with engagement feeling mostly one-sided. An additional 21.4% characterise their regulator as very risk-averse and acting as a barrier to progress, while 14.3% report that regulators claim to be pro-innovation but impose difficult-to-meet requirements. Only 3.6% experience active regulatory collaboration on AI best practices.

Despite this regulatory vacuum, the industry clearly desires guidance. While 23.8% believe there should be dedicated AI regulation for banks, 35.7% want AI-specific clarification of current regulations, and another 35.7% support AI regulation only to address clear gaps. Only 4.8% believe existing regulations already sufficiently cover AI.

This paradox – regulatory hesitance coupled with industry demand for clearer frameworks – represents a critical opportunity for collaboration. As AI continues its rapid evolution, bridging this gap will be essential for enabling safe, responsible innovation in risk management.

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