Indian Insurance at 3.7% of GDP: McKinsey Sees AI Reshaping Sales, Underwriting, Claims and Servicing
Indian insurance is poised for an AI-driven transformation as McKinsey examines opportunities to improve efficiency across the value chain.
Indian insurance penetration stands at 3.7% of GDP, with McKinsey highlighting AI’s potential to transform sales, underwriting, claims and customer servicing.
NEW DELHI – Indian Insurance: Indian insurers can apply artificial intelligence across four areas of their business, namely sales and distribution, underwriting and pricing, claims management, and customer servicing, to improve productivity and profitability, according to a new McKinsey report. India’s insurance penetration stands at 3.7 per cent of GDP, compared with a global average of 7.3 per cent, and the report says the next phase of growth will depend on how well insurers embed AI into everyday operations rather than run isolated pilots.
The report, titled “India’s new insurance track: The marathon becomes an AI-led decathlon”, was published on September 23, 2026. It argues that the contest for Indian insurers is shifting from a single long race to a multi-discipline one, where success depends on coordinated progress across service, distribution, underwriting, claims, actuarial science, core technology and talent.
Indian Insurance: Protection Gap and Margin Pressure
Indian Insurance: India is on course to become the world’s third-largest economy by the end of the decade, with nominal GDP expected to approach $7.3 trillion by 2030. The report says insurance has not kept pace with that expansion. The number of in-force individual life insurance policies has stayed at around 330 million between fiscal 2017 and fiscal 2025, even as banking, payments and investment products widened their reach. The shortfall in penetration is concentrated mainly in non-life insurance.
Recent policy changes could help. The Sabka Bima Sabki Raksha (Amendment of Insurance Laws) Act, 2025, operational since February 2026, has raised the foreign direct investment ceiling for insurers and intermediaries from 74 per cent to 100 per cent. A GST Council decision effective September 22, 2025, removed the tax on individual term life and health insurance premiums, cutting annual premium outgo by up to 18 per cent for retail policyholders. The insurance regulator has also set up a dedicated working group, as of June 2026, to develop an industry-wide approach to AI adoption, oversight and risk management.
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Growth, however, has not translated evenly into earnings. In life insurance, the top four private insurers recorded new business premium growth of roughly 12 to 16 per cent a year over fiscal 2022 to 2026, but value-of-new-business margins narrowed by three to four percentage points, with one exception. Between fiscal 2022 and 2025, new business premium grew at about 14 per cent a year while operating expenses rose around 20 per cent. In general insurance, productivity at the top five private multiline insurers, measured as premium per unit of employee expense, fell 2.5 per cent a year over fiscal 2022 to 2026, even as premiums grew about 12 per cent annually.
Indian Insurance: Four Areas Where AI Can Be Applied
The report identifies AI-led interventions across four parts of the insurance value chain and assesses them by business impact and the time they may take to deliver results.
In sales and distribution, it points to conversational sales enablement and agentic direct-to-consumer journeys, along with better activity intelligence for frontline managers and proactive renewal tools to improve advisor productivity and policy persistency. In underwriting and pricing, where manual processes still slow decisions, it suggests AI-enabled intake, risk assessment and decision support. For commercial lines, it says AI can automate submission processing and help insurers respond faster to brokers.
In claims management, which the report describes as an important differentiator of profitability in general insurance, the interventions include intelligent claims triage, detection of fraud, waste and abuse, network optimisation and claims automation. In motor insurance, it also mentions repair-network optimisation. In customer servicing, it highlights personalised and proactive servicing aimed at reducing the friction that affects retention, as customer expectations increasingly follow those set by banking and e-commerce.
The report adds that priorities differ by segment. Distribution productivity, underwriting and persistency matter most for life insurers. Underwriting, claims and network economics are the focus for health and retail general lines, while underwriting transformation is the main lever for commercial lines.
Indian Insurance: Moving from Pilots to Scale
The report says the main constraint on AI’s value is no longer the availability of technology but the ability to embed successful use cases into the operating model at scale. It says the greatest gains come when AI reshapes entire workflows rather than individual tasks, and it cites six capabilities common to organisations that have scaled AI: business-led road maps, evolved talent models, redesigned ways of working, flexible technology foundations, enterprise-grade data assets, and disciplined adoption and scaling.
For Indian insurers specifically, it lists five factors to consider. These are making use of the country’s digital public infrastructure for AI-enabled decision-making and customer engagement, completing full workflow transformations instead of scattered use cases, taking a selective and modular approach to the AI ecosystem, keeping business heads accountable for outcomes with technology, data and risk teams in support, and building a culture of rapid experimentation before wider rollout.
Common data definitions, enterprise-wide data platforms, strong governance and structured change management are described as the foundation for deploying AI at scale. The report concludes that the race ahead remains long, but the next phase will require coordinated progress across every part of the business, with AI changing how those functions work together.
