Agentic AI can solve insurance tech challenges, says McKinsey report

Agentic AI can transform tech modernisation in the insurance sector by addressing cost, complexity, and risk, a McKinsey report finds. It automates legacy upgrades, creating a repeatable, scalable, and value-compounding model for insurers.

Agentic AI presents an opportunity to fundamentally transform how technology modernisation is carried out in the insurance industry by helping companies address long-standing challenges related to cost, complexity and operational risks, according to a report by McKinsey and Company.

The report stated that modernising core technologies in the insurance sector has long been viewed as essential, but insurers have often delayed such projects due to concerns around implementation risks, high expenses and operational disruptions.

How Agentic AI Reshapes Modernisation

According to the report, agentic AI can reshape the modernisation process by automating and coordinating various stages of software transformation and legacy system upgrades.

The report highlighted that agentic AI systems can interpret legacy artefacts, generate structured documentation, create and validate code or configurations, run tests and coordinate workflows across the software delivery lifecycle. It stated "Insurers have long understood the need to transform their core technologies. So, why haven't they? Agentic AI may finally make the difference.... Agentic AI, drawing on experience from large-scale AI transformations, presents the opportunity to fundamentally transform how modernisation is done end-to-end by capturing legacy knowledge at scale, compressing rework loops, and improving predictability across testing, reconciliation, and cutover".

A New, Scalable Modernisation Model

It said these capabilities can help insurers capture legacy knowledge at scale, compress rework loops and improve predictability across testing, reconciliation and system cutovers.

The report further explained that agentic AI enables autonomous or semi-autonomous software agents to perform specific tasks while maintaining auditable outputs and human oversight controls. According to the report, this could allow insurers to move away from expensive one-time modernisation programmes toward a more repeatable and scalable modernisation model.

The report added that once core AI agents are built and governed, their reuse across multiple modernisation projects significantly lowers costs. This changes the economics of modernisation and allows insurers to view technology upgrades as a coordinated portfolio of opportunities across the wider technology estate rather than isolated migration projects.

Gaining a Competitive Advantage

According to the report, insurers that combine reusable AI capabilities with strong governance and platform discipline can accelerate the decommissioning of legacy systems while maintaining operational control.

The report stated that the key advantage of agentic AI is not only faster software coding but also the creation of a "structurally different and value-compounding modernisation model". It further noted that insurers adopting agentic AI at an early stage could gain a competitive advantage by improving the financial viability and scalability of technology modernisation programmes.

The report added that the technology may finally help insurers build the modern technology backbone that the industry has long considered essential for future growth and efficiency. The findings are based on large-scale AI transformation work, including projects developed within QuantumBlack, McKinsey's AI division. (ANI)

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