Closing the Protection Gap: How Technology and AI Can Unlock Insurance Access
Across the world, billions of people still live without meaningful insurance. The “protection gap” is often discussed in statistics, but behind every number lies a human story: families facing devastating medical costs, farmers left vulnerable to failed harvests, or gig workers who lose their income overnight. Insurance should be a safety net — yet for too many, it remains out of reach.
The question we must grapple with is this: can technology — and in particular artificial intelligence — help us close that gap?
AI, mobile platforms and data innovation are already reshaping how products are designed, who they reach, and how they are delivered. The opportunity is immense, but the challenge is to ensure these capabilities genuinely extend protection to underserved communities, rather than reinforcing exclusion in a more digital form.
The key themes shaping this challenge include:
Regulation as both enabler and barrier
Regulation can accelerate innovation, with sandboxes in the UK, Singapore and Kenya enabling safe experimentation in micro-insurance. At the same time, evolving frameworks such as the EU AI Act and the FCA’s Consumer Duty remind us that fairness, explainability and inclusion must be baked into AI models. Striking the right balance — between protection and access — is critical if technology is to serve vulnerable populations.
Reaching untapped markets
Billions remain uninsured, often due to affordability, cultural barriers or lack of trust. Mobile platforms, embedded services and partnerships with governments are unlocking new ways to engage these communities. Telco distribution models are especially powerful, allowing cover to be embedded into mobile usage, payments and everyday digital interactions — meeting people where they are, rather than asking them to come to us. AI’s role here is to surface needs hidden outside conventional datasets, guiding the design of products that fit local realities.
Designing the right products
Insurance must be simple, transparent and affordable. Parametric policies — which pay out automatically when measurable events occur — build speed and trust. Pay-as-you-go and micro-policies are particularly relevant in informal economies. AI has the potential to personalise these offerings at scale, but only if we actively address bias in the underlying data. Too often in established insurance markets, datasets reflect only certain communities or geographies, and models trained on them risk hardwiring exclusion. Tackling that bias must be a priority if AI is to deliver on its inclusive promise.
Making distribution real
Embedding insurance into services people already use — from mobile money to agricultural inputs to transport networks — offers powerful reach. Telcos, digital wallets and community platforms can all act as gateways to protection for new customer bases. AI-driven onboarding, multilingual interfaces and digital tools lower barriers to entry. Yet human intermediaries remain essential: trust and understanding are built as much through relationships as through algorithms.
The lesson is clear: AI is a powerful enabler, but it cannot act alone. It can help us design, price and distribute insurance in smarter ways — but true inclusion also requires empathy, cultural understanding and local trust.
If we succeed in combining these elements, insurance becomes more than a product. It becomes a platform for resilience — enabling families to invest, farmers to grow, and workers to face the future with confidence. Inclusion is not just a commercial opportunity; it is a societal imperative.
The protection gap is one of the great challenges of our time. With imagination, partnership and responsibility, AI can help us close it — and in doing so, redefine the role of insurance as a catalyst for shared progress and security.
