The Insurance Data and Analytics Divide — Those Who Have It and Those Who Don’t

Data and how we interact with it are a critical core business value proposition for most companies, including insurers. Data modernization in insurance is crucial to unlock its value.

Insurers gather and ingest data. We apply insurance data analytics that will inform our decisions. We act on those decisions and repeat. To improve our business processes, we continually seek refinements in how we improve data gathering and the use of analytics to continually optimize the business. But this isn’t the way it works everywhere.

The risk-averse nature of insurers, along with their focus on underwriting margins, profitability, reserves, and solvency, can restrain their ability to transform, optimize, and innovate. Investing in both today’s and tomorrow’s business is increasingly critical for carriers to elevate their operational excellence, innovate and create products that address new risks, new demographic needs, and protection gaps, and rethink the insurance value proposition—making insurance more transparent, reliable, accessible, and resilient. 

It requires rethinking the operating business model and technology foundation to enable agility, speed, and innovation in a new era of insurance and risk. For all insurers, it requires a leap into the data and analytics-driven future, not the slow, incremental pace that engenders comfort. 

The result of insurers resisting the change of their foundation and focus on data-analytics is a growing disparity between those insurance companies who have it and those that don’t — those that have access to the data, the technologies, and personnel to leverage the data, and those who don’t have the resources (or haven’t prioritized them) – often times limited by the lack of a next-gen architecture and foundation within their current operations.

We can stereotype these insurance companies by considering the data gap between “the haves” and “the have-nots.” The haves have been making strides. The have-nots are waking up to the fact that they are lagging behind, with a rapidly expanding gap due to the pace of AI technology change and adoption. There is hope, however, for the have-nots. Two related trends could help in closing the gap and leveling the playing field:

1. The democratization and demonetization of insurance data, and
2. The availability of AI, GenAI and Agentic AI embedded within core insurance systems.

Looking at both trends together, we can begin to form a vision of the future — where data will be accessible, operational insights readily available, and processes will be automated within the intelligent insurance analytics software. It’s already happening to some degree, but what will it be like for insurers once the processes are seamless and unhindered? What does the future of data and analytics in insurance look like? How is GenAI and Agentic AI closing the insurance operational gap?

The Democratization and Demonetization of Data Accelerates

Data has always been the lifeblood of the insurance industry, but today it is a vital asset in our digital world and increasingly crucial across every part of the insurance value chain. But access to data continues to be challenging and expensive.

From siloed data to limited access to core operational data, consolidation of data providers, and access at a price for 3^rd party data providers, the insurance data divide is creating competitive and market opportunity differences between those with access to data and those without.

For some insurers today, the cost of 3^rd party data can be one of the largest operational expenses they have.

The democratization and demonetization of data is emerging as a key trend to break down the barriers and make data more accessible, understandable, and actionable to anyone. And most importantly, it is available for GenAI and Agentic AI within the business processes across the value chain that drives operational efficiencies. Five areas are emerging that together are empowering the democratization and demonetization of data.

Intelligent Core Solutions

Intelligent Core solutions provide access to all operational data (as compared to limited pre-defined data) from the systems into a data lake, making it available for use across the spectrum of analytics – BI, AI/ML models, GenAI and Agentic AI.

Core Solution Contributory Databases

Next-gen solution providers are creating contributory databases of all the operational data from their systems used by their customers in the cloud, anonymized to be used in the development of embedded AI/ML and LLM models from the solution provider, helping to eliminate the need to buy some data or models, but more importantly enabling them to leverage the LLM models used by GenAI and Agentic AI.  

Embedded Analytics

This is a next-gen data and analytics strategy and foundation leveraging a data lakehouse of all data from systems with real-time updates, embedded business intelligence within the workflows, and with capabilities for personalized dashboards, embedded AI/ML models built or from partners, and GenAI and Agentic AI across all workflows. This eliminates fragmentation and cost as they are embedded and included with the solutions, rather than as an “add-on” with limited business impact.  Embedded analytics reduces the complexity of insurance operations and costs, across the value chain to drive consistency, quality and real business optimization impact.   This is a game-changer that can help to level the playing field.

AI and now GenAI and Agentic AI Adoption

AI and now GenAI and Agentic AI adoption are accelerating the democratization of data by making it accessible and understandable for both technical and non-technical users. AI, GenAI and Agentic AI capabilities can consume and analyze vast datasets – both structured and unstructured, identify trends and patterns, create scores and insights, and create new levels of automation to drive operational efficiencies that have not been achievable through transformation initiatives.  

Next-Gen Data Provider Options

There is a quiet emergence of a new data management approach. It leverages data mesh technology and blockchain that distributes data ownership and creates domain-oriented data offerings that can be queried and shared as well as managed closer to the source, enhancing quality, security, and governance. It will eliminate the multiple layers of cost for the same data that is prevalent across the industry and with most traditional 3^rd party data providers. 

The impact of democratization and demonetization of data, coupled with new analytics, will help drive down data and analytics costs and eliminate the cost multiplier effect from use of the data by multiple entities, while making access and usage of advanced data and analytics available to any type or size of organization. The have-nots can now create an insurance data and analytics strategy and have confidence that it will make them more profitable and competitive.   

AI, GenAI and Agentic AI Propel Real Business Optimization and Value

An October 2024 Boston Consulting Group report noted that while just 4% of companies have developed cutting-edge AI capabilities across functions and consistently generate significant value, an additional 22% have implemented an AI strategy, built advanced capabilities, and are beginning to realize substantial gains.[i]  The report further notes that over the past three years, AI leaders achieved 1.5 times higher revenue growth, 1.6 times greater shareholder returns, and 1.4 times higher returns on invested capital while also excelling in non-financial areas like patents filed and employee satisfaction.

What differentiated them as leaders? There were six key characteristics, including:

1. Focus on core business processes for competitive advantage
2. They are more ambitious and look beyond productivity to AI-driven revenue growth and workforce enablement
3. Integrate AI into both cost and revenue generation efforts
4. Invest strategically in a few high-priority opportunities to scale and maximize AI’s value
5. Focus efforts on people and processes over technology and algorithms
6. Moved quickly to focus on GenAI and Agentic AI

Integration of AI, GenAI and Agentic AI into insurance business processes and insurance system solutions, and workflows is transforming every aspect of the industry to provide detailed guidance, assessments, and recommendations, driving improved productivity and accelerating  employees’ knowledge and performance. It can simplify complexity, streamline processes, enhance decision-making processes, provide transactional guidance, and drive operational productivity and optimization that has not been seen since the initial automation of insurance decades ago.

It is the innovation catalyst needed to help insurers stay ahead of market trends, risk shifts, customer demands, and technological advancements, giving them the confidence to navigate complexities with ease and significantly improve business operations and results. Early benchmarking results show 10-20 times productivity improvement that can revolutionize the operations and customer servicing, while driving quality, consistency, and operational efficiency. It can lower unit costs and expense ratios, which subsequently can improve product pricing and competitive market position.

In addition, at a time when 50% of the insurance industry professionals are expected to retire by 2030, it can accelerate onboarding and bend the learning curve for employees. AI, GenAI and Agentic AI are breaking barriers, rethinking business operations, and creating a new era of operational excellence. Focusing GenAI and Agentic AI on the business operation is reducing costs and improving productivity, enabling faster product launches, enhancing risk management, and redefining what’s possible in insurance.

AI, GenAI and Agentic AI are real, with real results emerging and poised to be a game-changer for the insurance industry. Frontrunners and leaders are outpacing others and will redefine the future of insurance by taking the lead with this.

For the haves and the have-nots, the ability to capitalize on data democratization and demonetization, and AI, GenAI and Agentic AI are their integration and use within intelligent insurance systems. Majesco has wrapped these capabilities into our Core Next-Gen Intelligent Core Insurance Software Solutions in order to release their functionality and propel insurers into the future of operations, product development, data-driven insights, and next-level automations. The timing is right. As the insurance industry turns over its knowledge base of talent and prepares to fit its products to the next generation of customers — digital transformation and applied insurance data insights will make it possible.

Dig into more trends that are affecting insurance and your organization. Be sure to read
8 Trends Shaping the Future of Insurance in 2025 today.  

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[i] “AI Adoption in 2024: 74% of Companies Struggle to Achieve and Scale Value,” BCG, October 24, 2024, https://www.bcg.com/press/24october2024-ai-adoption-in-2024-74-of-companies-struggle-to-achieve-and-scale-value