Majesco highlights AI reshaping insurance operating models

Reinsurance News reports that Majesco has released a 2026 strategic priorities report finding that insurers prioritising AI, generative AI and agentic AI - the 'Leaders' segment - are widening the competitive gap over Followers and Laggards. Denise Garth, Chief Strategy Officer at Majesco, stated: "As insurers enter the Intelligence Era, the competitive gap between Leaders and the rest of the market is widening." The report links Leader status to lower expense ratios, better operational performance, and stronger innovation output. The research finds Leaders align core system modernisation with operating model redesign as a single programme, whereas many peers address them separately, limiting transformation value.
What happened
Reinsurance News reports that Majesco released a 2026 strategic priorities report examining how insurers are reinventing operating models and technology foundations amid rising costs, new risks, and accelerating AI adoption. The research categorises insurers into Leaders, Followers and Laggards and finds that Leaders are moving beyond isolated pilots to broader transformation built on cloud and AI-native technology foundations. Majesco links Leader status to lower expense ratios, improved operational performance, enhanced customer experience, stronger talent retention, and increased innovation.
Key finding - the widening gap
Denise Garth, Chief Strategy Officer at Majesco, said: "As insurers enter the Intelligence Era, the competitive gap between Leaders and the rest of the market is widening. Leaders are not simply modernising technology - they are reinventing how their businesses operate and leveraging native cloud and AI core software to unlock agility, operational efficiency, and new growth opportunities" (Business Wire). The report identifies that Leaders execute core modernisation and operating model redesign as a synchronised programme, while many Followers and Laggards continue to treat them as separate efforts, limiting the value of their transformation investment.
Editorial analysis - technical context
Adoption of generative AI and agentic AI in insurance implies material lift in data, model operations and integration work before business value scales. Companies that move from pilots to enterprise use typically address data lineage, feature engineering maturity, model monitoring, and production retraining pipelines. The report aligns with wider observed patterns: cloud-native platforms, API-driven model serving, and governance tooling satisfying regulatory and underwriting auditability requirements tend to be common enablers.
Industry context
Industry trade reporting and vendor surveys have increasingly flagged a divide between early adopters who embed AI into core underwriting, claims automation, and customer workflows and slower adopters who run isolated pilots. This report is vendor-sponsored primary research - findings should be read as indicative of directional trends rather than independently benchmarked outcomes.
What to watch
- •Whether Majesco or independent researchers publish anonymised metrics quantifying the cited expense ratio and operational improvements.
- •Signals from insurers on productionising generative AI for claims and policy servicing, including governance, explainability, and third-party model use.
- •Regulator guidance addressing agentic AI workflows and auditability of AI-driven decisions in regulated insurance contexts.
Scoring Rationale
Vendor-sponsored thought leadership report covered by a single trade outlet. The findings corroborate broader industry trends around AI adoption in insurance but represent Majesco primary research rather than independently verified benchmarks. Solid context for insurance AI practitioners but not a frontier technical breakthrough.
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