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Agentic AI Could Transform Insurance Tech Modernization, Says McKinsey

A McKinsey report highlights agentic AI as a transformative tool for insurance tech modernization, addressing cost, complexity, and risk. It automates tasks like legacy interpretation, code validation, and workflow coordination. Reusable AI agents lower costs, shifting from one-time projects to scalable models. Early adopters may gain a competitive edge in building efficient, modern tech backbones.

Key Points: Agentic AI to Cut Insurance Tech Modernization Costs

  • Agentic AI automates and coordinates software transformation
  • Reduces costs by enabling reusable AI agents across projects
  • Captures legacy knowledge and compresses rework loops
  • Improves predictability in testing, reconciliation, and cutover
3 min read

Agentic AI may help insurers reduce cost, complexity of tech modernisation: Report

McKinsey report says agentic AI can reduce cost, complexity, and risks in insurance tech modernization, enabling scalable upgrades.

"Insurers have long understood the need to transform their core technologies. So, why haven't they? Agentic AI may finally make the difference. - McKinsey Report"

New Delhi, May 8

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.

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".

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.

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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Reader Comments

P
Priya S
Sounds promising, but I hope this doesn't mean more job losses in the IT sector. Already our techies are struggling with offshoring. Agentic AI should be a tool for augmentation, not replacement. The human oversight part is critical. 🤔
V
Vikram M
As someone in insurance IT, I can tell you that legacy modernisation has been a nightmare forever. Every project goes over budget and takes years. If this can automate even half of the legacy code analysis and testing, that's a massive win. Good direction, McKinsey.
J
James A
Interesting perspective, but they always say AI will fix everything. The real challenge in India is regulatory compliance and data privacy. IRDAI will need to be on board. Still, I'm cautiously optimistic. Let's see the proof in the pudding.
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Siddharth J
This reminds me of the 2000s when we tried to modernise with BPM tools. It didn't stick. But the AI approach here—capturing legacy knowledge at scale—could be different. The key will be whether Indian insurers actually invest in building these agents properly, or just buy a half-baked solution.
K
Kavya N
Finally some good news for the insurance sector! Our public sector insurers especially need this. LIC has so many legacy systems that it's a miracle they run at all. Agentic AI could help them modernise without disrupting customer service. Hope they act fast. 🇮🇳

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