The insurance industry is poised for a new era of artificial intelligence-driven innovation and growth. From GenAI and deep learning to increasingly autonomous agentic systems, insurers are investing in intelligent technologies to streamline underwriting, personalise risk pricing, detect fraud and enhance customer experience. However, regulatory uncertainty is slowing deployment.
According to Accenture, GenAI alone could add up to £59 billion to the UK’s GDP by 2038 – largely driven by the insurance industry. As things currently stand, Accenture notes a significant deployment gap, however, with only 8% of firms scaling AI initiatives despite 83% piloting projects – a shortfall it says is driven in part by regulatory concerns.
Insurance innovation in EMEA
For insurers in Europe, the Middle East and Africa, there is a mixed picture when it comes to innovation and regulatory activity. While the EU is setting the global benchmark for AI regulation with its pioneering AI Act and robust data protection regime, parts of the Middle East and Africa have yet to put in place regulatory frameworks for AI.
The EU AI Act, adopted in 2024, is the world’s first comprehensive AI regulation, categorising AI applications by risk – prohibited, high-risk and limited-risk – and imposing varying obligations accordingly. For insurers, high-risk AI includes systems that influence eligibility for credit, insurance underwriting and claims decisions. These systems must comply with stringent transparency, risk management, data governance and human oversight requirements. In certain contexts, the use of GenAI and large language models will require specific disclaimers and safeguards, particularly to prevent misuse or hallucination.
Navigating AI Regulation
The Digital Operational Resilience Act (DORA), which entered into force in 2025, mandates financial institutions – including insurers – to bolster IT resilience and cyber security, including those using AI systems. AI introduces new operational risks such as model drift, adversarial attacks and data leakage. DORA requires firms to map and monitor their critical ICT systems, including any AI-driven platforms involved in claims processing, fraud detection or customer interaction.
The General Data Protection Regulation (GDPR) remains a fundamental consideration for AI deployment for insurers. Article 22 addresses automated decision-making and profiling, giving individuals the right not to be subject to decisions based solely on automated processing if those decisions produce legal or similarly significant effects. This is directly relevant to insurers using AI for pricing, eligibility and claims settlement, as these may count as significant under GDPR. The law requires firms to ensure transparency, allow human intervention and justify the rationale behind decisions – a task that becomes more complex with deep learning models.
Post-Brexit, the UK is pursuing what it calls a “pro-innovation” approach to AI regulation. Instead of a centralised AI law, the UK has opted for sector-led guidance, allowing financial regulators to tailor rules based on use cases. In April 2024, the Bank of England and Financial Conduct Authority issued a joint AI Discussion Paper, outlining expectations on model governance, accountability and data ethics. The focus is on trust, explainability and proportionality – similar in spirit to the EU AI Act, but more flexible.
AI Deployment
Accenture’s UK-specific findings show a considerable upside to AI deployment: It found that 71% of insurance working hours could be enabled by AI, with potential productivity gains of up to 30%. However, 30% of UK financial executives cite regulatory uncertainty as the primary barrier to scaling, despite strong sectoral governance, risk and compliance capabilities.
Across the Middle East and Africa, AI regulation remains nascent but fast-moving. The UAE has positioned itself as a regional AI leader with its National AI Strategy 2031 and AI Ethics Guidelines, while Saudi Arabia’s Saudi Data & AI Authority (SDAIA) has issued a national data and AI governance framework. In Africa, policy fragmentation remains an issue, although Kenya, South Africa and Nigeria are actively drafting AI policies that aim to balance innovation with ethical oversight. These regions are seeing growing use of AI in fraud detection, telematics and customer engagement, but data infrastructure limitations and skills shortages slow adoption. Most regulatory attention today focuses on data privacy, fairness and AI literacy, with future laws likely to follow the EU’s lead on risk-based classification.
Global influence
As the world’s first comprehensive AI regulation, it is perhaps unsurprising that the EU AI Act is shaping global discourse on AI governance. Its risk-based framework, harmonisation of transparency obligations and enforcement mechanisms have drawn interest from regulators in Japan, Brazil, Canada and beyond.
For EMEA insurers, the Act’s influence means that even non-EU operations may eventually face EU-style compliance pressure, particularly for cross-border services, model training, or cloud deployments involving EU data subjects.
In an industry that is synonymous with risk assessment, it is no surprise that insurers are among the most cautious yet intrigued adopters of AI. To close the deployment gap and unlock multi-billion-pound gains, the industry must navigate evolving regulatory regimes – balancing speed with diligence and innovation with trust.
About RNA Analytics
RNA Analytics is a multi-award-winning global actuarial and risk management firm and software vendor headquartered in Reigate, United Kingdom. The RNA Analytics Team is located across the United Kingdom, South Korea, Japan and Hong Kong, and provides actuarial and risk management consulting services to financial institutions around the world.
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