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Majesco to quadruple AI investment to expand, accelerate P&C roadmap

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Majesco, a technology provider known for its cloud-native and AI-native solutions for P&C and life and annuity/health insurers, has strengthened its dedication to the P&C space with plans to expand investments and accelerate its product roadmap.

The company detailed new initiatives to build a next-generation AI-powered SaaS cloud platform tailored for property and casualty insurance carriers.

The announcement follows Majesco’s recent surge in investment in the L&AH market. The company is currently increasing its focus on property and casualty insurance through Strategy 2026, designed to support significant progress while maintaining customer advancement and protecting its competitive position.

Majesco describes the current insurance industry as a transition to the smart era, characterized by rapid advances in artificial intelligence that surpass previous technological milestones. While contemporary SaaS platforms remain important, the company believes insurers now need systems built with AI at their core to support improved efficiencies, faster execution and stronger results across the business.

With its broad customer community, broad domain knowledge, mature property and casualty insurance products and early leadership in applied AI, Majesco believes it is well-positioned to lead the industry toward a new wave of AI-native capabilities. These platforms are designed to help insurers enhance profitability, streamline operations, expand opportunities and remain competitive as expectations rise.

Majesco plans to quadruple its investment in AI-related developments by 2026 to accelerate the enhancement of its property and casualty insurance portfolio. The first priority is to build an AI-native platform to increase the speed to value across the core system, data and user experience layers, while continuing to expand Majesco Copilot and Agentic AI.

Key goals include significantly reducing implementation time, expanding self-service options, reducing total cost of ownership and embedding continuous intelligence in underwriting, policies, billing, claims and loss control.

The company emphasizes that these advancements will be based on structured, safe and responsible AI standards. Customers can expect a steady stream of updates that simplify change, improve insight generation and shorten cycle times by supporting faster innovation and earlier engagement without adding complexity. Majesco expects these efforts to have a meaningful impact by 2026 and lay the foundation for long-term AI-native P&C intelligence solutions designed to improve accuracy, reliability and overall performance.

Majesco reiterates that its commitment to P&C is stronger than ever. Its strategy, investment and execution plans reflect a focus on delivering real business benefits securely and at scale, resulting in faster deployments, more efficient day-to-day operations, improved user experience and stronger financial performance for insurers adapting to changing market demands.

Manish Shah, president and chief product officer of Majesco, added: “Our recent investment and expansion into L&AH solutions reflects the opportunity to provide AI-native solutions to more insurance industries, rather than abandoning property and casualty insurance.”

“Our significantly increased investment in P&C in 2026, quadrupling our AI workload, will deliver an AI-native platform that enables insurers to move faster, operate leaner, compete better and innovate with confidence. Our message is simple: Majesco’s P&C leadership is growing, our innovation is accelerating, and our customers will feel the impact in months, not years.”

Majesco’s cloud-native and AI-native platform for L&AH and P&C is designed to deliver ongoing value to insurers seeking advanced capabilities, the financial stability of a technology partner and the expertise of years of dedicated industry support. The company was recognized by Quadrant Knowledge Solutions as a 2025 Artificial Intelligence Leader for L&AH and P&C Core Solutions.

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