Majesco, a provider of AI-native and cloud-native software solutions for the insurance industry, has released a new thought leadership report examining insurers’ strategic priorities for 2026.
Titled Strategic Priorities 2026: The Frontier Insurer in the Intelligent Era of Insurance, the report is based on Majesco’s primary research into how insurers are approaching technology investment and business transformation.
According to Majesco, insurers are placing increasing emphasis on artificial intelligence, generative AI and agentic AI as they seek to address both operational and strategic objectives.
The research suggests a growing divide between organisations identified as Leaders, Followers and Laggards, with more advanced insurers moving beyond limited AI pilots towards broader business transformation supported by automation, intelligence-driven processes and operating models built on cloud and AI-native technology foundations.
Majesco’s findings indicate that insurers classified as Leaders are integrating AI more deeply into their business strategies, with the company associating this approach with lower expense ratios, improved operational performance, enhanced customer experiences, stronger talent attraction and retention, increased innovation and improved long-term competitiveness.
“AI is rapidly becoming the new divider between Leaders versus Followers and Laggards in insurance,” commented Denise Garth, Chief Strategy Officer at Majesco.
“Insurers leading are redesigning their operational model leveraging a cloud and AI-native core technology foundation that deeply integrates AI into the business and redefines them as a Frontier Insurer that achieves unprecedented agility and value creation faster than traditional companies. For an industry like insurance—data-intensive, regulated, highly competitive and often challenged financially—the stakes and opportunities are high, but the potential business value and outcomes are even greater.”
Majesco states that insurers continue to face a range of pressures, including rising operating costs, increasing risk exposure, talent shortages, ageing technology infrastructures and profitability challenges. The company argues that AI and generative AI have the potential to influence virtually every area of the insurance value chain, from underwriting and claims management to policy servicing and fraud detection.
According to Majesco, improvements delivered through AI at an individual task level can generate wider benefits across the organisation. The company suggests that efficiencies gained through automation and intelligence-led decision-making may contribute to greater agility, lower operating costs and stronger financial performance over time.
The research identifies AI as an increasingly important business priority for insurers heading into 2026, with cost management, operational efficiency, customer experience and AI capability development becoming more closely aligned. Majesco also reports that insurers with more mature AI programmes are extending their lead through greater adoption of analytics, generative AI, agentic AI and practical business applications, creating an increasingly significant competitive distinction within the market.
Majesco further notes that generative AI is seeing some of its strongest adoption in customer servicing, claims and underwriting functions, where it is being used to streamline processes and increase operational capacity. The report also highlights growing interest in agentic AI, as insurers assess its potential to automate workflows, coordinate activities and support decision-making across the enterprise.
The company emphasises that long-term success with AI will depend on the strength of underlying data capabilities. Majesco’s research points to data maturity, governance, integration and risk management as key factors that will determine whether insurers are able to scale AI initiatives effectively and realise sustainable value from their investments.
Majesco concludes that insurers investing in cloud and AI-native technology foundations, modernising core systems and redesigning operating models to support collaboration between employees and AI technologies are likely to be better positioned to improve efficiency, strengthen competitiveness and respond to changing demands.
