I love music and listen to it all the time! Do you listen to music? How has your music listening experience changed over the years? Did you carry around CDs or cassettes? Do you still have LPs? Did you own an early iPod with a mini hard drive that you could feel clicking and spinning in the palm of your hand? Are you old enough to have spent a few Saturdays at the record shop?

At the heart of these questions, we find the issue of business models, technology foundations and trending customer demands. The business of music and insurance isn’t as far apart as it may seem, especially when you consider that both are now part of the customer digital experience.

In 2022, Apple stopped selling the iPod. In the early iPod days, audio tracks were purchased. You had to own the tunes to carry them with you. In 2006, Spotify and other streaming services carved out a new business model. In fact, the new model ultimately used Apple’s technologies against it. You could load the Spotify app on the iPod touch, and you could listen to a much wider array of music.

Apple had to respond by purchasing another streaming company and rebranding it, but it was competitively lagging. Spotify had been perfecting its model and experience. Once the hardware (the iPod) became obsolete technology and the business model (purchase) went out of fashion, the company had to adapt or lose that part of its business. Apple is once again strong and in the running, but it may never recover the ground it lost due to its slow transition to a new music reality.

Business Models and Synchronization

Insurers are likewise wrestling with some of the same conundrums. Delivering business value out of a marketable idea has always been, on some level, about synch:

• New insurance business models must be synchronized with the technologies that empower and facilitate them, or they will perform poorly or fail.
• Technologies must “understand” business models and customer needs or they do not create value. For example: AI strategy for insurance must include insurance data governance and data quality management.
• Both new business models in insurance and technologies must adapt to market trends, business trends and tech trends, or they will be outmoded and become irrelevant to the people and businesses they serve — and unintelligible to the people who use them.

Hence, the need for insurance executives to quickly make strides within redefining insurance business models that embed and leverage AI, but to do it in a way that incorporates three key strategic areas — business, technology and marketing — while anticipating future needs.

Agentic AI and GenAI are critical for modern insurance industry operations. But current AI pilots aren’t giving many insurers measurable business results and current implementations are stalling. Many insurers are beginning to ask, “Where’s the promised ROI?”

The answer relates to sync, not task optimization. The business model and AI must be part of a broad strategy — not a tactical initiative — that establishes a foundation for creating and leveraging business value. It includes redefining the business model and leveraging advanced technology as cooperative forces. It requires a look at culture, talent, growth planning and partnerships. The benefits are many for insurers prepared to change more than just isolated processes. To illustrate, we will look at new insurance business models and new technology in insurance, and see how they relate. You can read more about these trends in Majesco’s recent Thought Leadership report, 2026 Trends Vital to Compete and Accelerate Growth in a New Era of Insurance.

High-Performance Operating Business Models Unlock Insurance Growth Strategies

While your strategic goals and growth plans may be the right ones, is your business operating model built to achieve them?

More than likely, no.

Most insurance operating models were crafted over decades around a myriad of constraints, business assumptions and challenges. The operating model evolved to support this legacy construct by layering in technologies over legacy with the hope of optimization.

But the result has been inefficient and sometimes unprofitable. Employees and operations are often constrained by a layered, complex technology foundation that has increased costs rather than decreasing them.

McKinsey research indicates that even high-performing companies have a 30% gap between their strategy’s full potential and what is actually delivered, which can be attributed to shortcomings in their operating models. Insurers need to change the economics for loss ratios, expense ratios, risk selection, and risk prevention.[1]

The old methods of modernization have not achieved the results needed. We lacked focus on the areas of true differentiation, like products, underwriting, and channels, and thought our “secret sauce” was all our internal customized business processes. This resulted in a lot of software customization that added cost, impacted agility, and increased long-term costs for upgrades (if even possible with the customization) and maintenance.

Today, insurers must take advantage of out-of-the-box capabilities and automation in place within core, particularly with intelligent automation using GenAI and Agentic AI that redefine and optimize the business processes and operating model to levels we have not seen before. Embracing this automation requires strong leadership and change management, rather than whiteboarding a future state that does not take advantage of the rich capabilities and automation available. Furthermore, limiting the customization ensures easy and cost-efficient upgrades for new innovations and automation.

Transitioning to a new operating model is necessary but is not without risks that must be addressed. The new business model must take advantage of groundbreaking technologies, such as IoT, GenAI, Agentic AI, next-gen cloud platforms, and others, to redefine and optimize new business processes and methodologies.

The right business operating model can turn strategic potential into market-beating results and open the door to a wonderland of possibilities that enable agility, scale, operational optimization, and innovation in a fast-changing market and a new era of insurance.

AI Strategy + Intelligent Tech Enable Real Business Value and Optimization

We have entered an era of intelligent insurance operations. GenAI and Agentic AI are more than new tools—they are strategic catalysts with inconceivable business value. They have the ability to improve everything, from risk and safety to operations and profits. Making the case for GenAI or Agentic AI based on just one or two business functions misses the AI point. The question isn’t, “How will we use AI?” It is “How won’t we use AI?” How fast and how broadly can we adopt and reimagine our business models?

The rapid proliferation of data, coupled with AI, is reshaping the insurance industry by unlocking business value and the potential to transform, optimize and innovate business operations in every sector. It will elevate customer experiences, improve risk assessment, underwriting, billing and claims, and foster talent retention and acquisition. It will offer a new level of business value and optimization that delivers real business value and outcomes.

Current AI Strategies are Yielding Negligible Returns

While AI adoption is surging, ROI is lagging. Why?

Adoption has gone mainstream – In early 2025,

78% of organizations reported using AI in at least one business function, up from 72% in early 2024 and just 55% in 2023.[2]

Returns not following suit – A landmark MIT/

NANDA study found only 5% of GenAI pilots deliver measurable financial returns, while a staggering 95% stall without impacting P&L.[3]

The reason isn’t poor tech, it’s poor strategy

AI failures suffer from flawed strategies, unclear objectives, or misaligned expectations— not a lack of technology.

A broad strategic approach establishes a foundation that leverages GenAI and Agentic AI across the entire value chain, from providing guidance and answering questions to specific use cases for complex areas. AI reduces operational costs in areas such as claims, underwriting, billing, and policy administration. It improves operational efficiency and can substantially impact expense ratios and strengthen overall financial metrics. The broad strategy—not a tactical one—unlocks the compounded benefits that far exceed the sum of individual task improvements.

Agentic AI and GenAI are critical for modern insurance industry operations. With rising operational costs, increased risks, talent shortages, outdated technology and profitability challenges straining insurers’ financial performance, AI is poised to transform every aspect of the business.

What begins as isolated improvements in task execution and data insights becomes a strategic multiplier that drives competitive advantage, agility, and long-term profitability. These aggregated gains translate into a compelling case for adoption. These are not speculative future benefits. Leading companies have made bold moves toward AI transformation. AI is playing an increasingly greater role in innovation. The trick for insurers is to see AI as a part of innovation’s foundation and not as a random tool applied to lagging areas within a static business model.

In a recent Best’s Review interview with Edin Imsirovic, he shared that companies are realizing measurable benefits from innovation efforts. They looked at the AM Best innovation categories and compared them against actual operating metrics. What they found is a gap between innovators and non-innovators. Innovation leaders are growing their premiums on average by about 12% as compared to the industry average of 7%. This is an improvement on expense ratios, where ten years ago innovators had a 1-point advantage, but today that has increased to a 4-point advantage, and innovators have grown their surplus at twice the amount.[4]

Despite interest and enthusiasm, many insurers are still evaluating pilot programs and fragmented point solutions, lacking a strategic plan to maximize the value of AI across the organization. Success requires leadership and the willingness to rethink the business.

Much of the success and failure of AI initiatives will fall upon the readiness of insurance technology partners. The key characteristics of AI and GenAI partners should include:

AI & Innovation Readiness — Is the partner advancing rapidly in native AI capabilities purpose-built for insurance operations? Do they have a clear AI strategy and market-ready offerings? This can make a difference in how quickly you can leverage automation and data-driven insights for growth and efficiency.

Cloud Native Adoption – Are most of your partners’ customers running live in the Cloud and are they up to date on the most recent releases to enable faster innovation, lower maintenance burden, and predictable and rapid upgrade cycles?

Selection Criteria — Are you selecting a partner for the future, or for yesterday’s criteria? Functional parity today matters less if the vendor isn’t building the native AI capabilities you’ll need in the next 2–3 years.

Procurement Process — Is your procurement process rewarding tradition over innovation? A partner should be financially strong and have a track record of executing innovation quickly.

It’s still about the experience.

How will your customers, in the next year, perceive your abilities to keep them at the forefront of the insurance experience? Can you improve their digital insurance experiences so much that they laugh at what they used to go through? Will AI, GenAI and Agentic AI not just improve operations, but satisfy your customers and your employees?

How can insurers supercharge their strategies with AI?

Majesco is supplying insurers with a native AI and cloud foundation in our P&C and L&AH intelligent core solutions that facilitate the needed business model change and take full advantage of what the technologies offer. We are looking into the future to manage each step, making sure that our insurance partners stay competitively and operationally ahead for their customers who are speeding into the future.

Where is your organization in the decision process? Are you ready to move or content to watch as others move ahead? Become a part of the conversation and get a glimpse of where the industry is heading with AI and GenAI. Be sure to read Majesco’s latest Thought Leadership report, 2026 Trends Vital to Compete and Accelerate Growth in a New Era of Insurance and tune in to a timely Majesco webinar, where four of today’s top industry experts discuss Harnessing the New Era of Insurance Innovation and Operations for Real Business Value.

[1] Krivkovich, Alexis et al., “A new operating model for a new world,” McKinsey & Company, June 18, 2025, https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/a-new-operating-model-for-a-new-world

[2] Alexandrea, Jordana, “How many companies use AI in 2025? Key statistics and industry trends,” Hostinger, May 16, 2025, https://www.hostinger.com/tutorials/how-many-companies-use-ai

[3] Estrada, Sheryl, “MIT report: 95% of generative AI pilots at companies are failing,” Fortune, August 18, 2025, https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/

[4] Chordas, Lori, “AM Best’s Imsirovic: Data Modernization, Not Algorithms, Emerges as Bottleneck for Insurers,” October 16, 2025, https://news.ambest.com/newscontent.aspx?altsrc=108&refnum=269942