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Avoiding Operational Chaos: Crafting a Holistic Strategy for Implementing GenAI and Agentic AI
Technology’s inceptions are often chaotic. In fact, we look back on many first technology developments as “follies.” From the first flying machines to the first light bulbs and even the first computers — engineers were envisioning as they were iterating — as if a fog were hanging over their logic and reason, only to be lifted by someone who finally “got it right” for both form and function. Then, the real race was on. Product teams would form. Developers would take the technologies to their furthest ends, begging, borrowing, emulating, and creating faster than the competition.
At some point, the competition would begin to dwindle due to a lack of resources, expertise and investment to keep pace. The products would rapidly improve. The technology would fulfill its highest purposes. The chaos would fade into operation, then optimization, always with some customization, as most technologies found new niches for use and profit.
Artificial intelligence (AI) is not a new phenomenon but it is new enough to still look and feel chaotic. Many businesses have been using it for years, primarily for predictive modeling. But recent advancements, notably the introduction of Generative AI (GenAI) nearly 3 years ago in November 2022, have catapulted it into the mainstream.
The May 2025 RBC report, “The Software Investor’s Handbook to AI,” notes GenAI is a seismic technology landscape change, the fourth seminal shift over 40 years following the Internet, Cloud, and Mobile, with major implications for technology, businesses and society.[1] Don’t believe it? Search for the number of data centers currently under construction to handle AI.
GenAI and Agentic AI are revolutionizing business operations and processes across industries, redefining what is possible in terms of speed, scale, operational efficiencies, consistency, quality, and strategic decision-making. Some companies are piloting the technology as a “bolt on” capability that has targeted, yet limited impact. In contrast, others are embedding it across their business solutions that drive their operations to automate and streamline workflows, improve employee productivity, enhance customer engagement, drive down operational costs and expense ratios, which will improve profitability, competitive pricing, and market positioning.
AI for insurance is the transformative technology of our lifetimes.
Majesco’s recent thought-leadership, A Powerful Chain Reaction: The Financial and Operational Impact of GenAI and Agentic AI Across the Insurance Value Chain, outlines how insurers must set forth a strategy to capture the full value of AI—GenAI and Agentic AI—across the entire business operation to achieve new levels of cost efficiencies and productivity that will drive down expense ratios that make them competitive in a rapidly changing marketplace. To help insurers envision real-life applications and the value of AI for insurance, Majesco use cases and benchmarks are given for both P&C and L&AH intelligent solutions that can be used to assess the business value and impact for the organization.
Though our overall goal was to paint a holistic portrait of the power of AI and GenAI for insurance, Majesco dived into detailed tasks for the use case for functional areas including Product, Quote, Underwriting, Issue, Servicing, Billing, Claims and Loss Control. You’ll find these benchmarked tasks within the report.
Enter the chaos
For an industry like insurance—data and process intensive, regulated, highly competitive, and often challenged financially—the stakes and opportunities are high, but the potential business value and outcomes are even greater. As insurers consider use cases for GenAI and Agentic AI, the possibilities are limitless. However, there is a move that can limit AI’s potential — plugging AI as an “add on” for a specific use case limits the overall operational and business value, which could lead to organizational chaos for insurance, where insurers once again opt for silos instead of solidarity.
A broader strategic approach establishes the foundation to leverage AI across the entire value chain is much more impactful, offering consistency and quality that protects the organization from the sporadic, independent AI capabilities. Imagine having AI capabilities for policy and billing but not for claims or for certain lines of business units and not for others because they use non-intelligent solutions. Imagine the impact on staff.
As insurers consider the AI opportunity, they must focus on keeping the end-to-end value chain in mind and use enterprise strategies to reap the full rewards for operational growth, flexibility, value, and profit.
A complete operational innovation catalyst
AI, GenAI and Agentic AI are critical for modern insurance operations. With rising operational costs, increased risks, talent shortages, outdated technology and profitability challenges straining insurers’ financial performance, competitiveness and growth, AI, GenAI and Agentic AI are poised to transform every aspect of the business. By enhancing the performance of individual business tasks—claims adjudication, underwriting, policy servicing, fraud detection—AI generates efficiencies that compound within a functional area and across the enterprise. What begins as isolated improvements in task execution becomes a strategic multiplier that drives competitive advantage, agility, and long-term profitability.
AI is the innovation catalyst needed to help insurers stay ahead of market trends and technological shifts, allowing them to constantly rethink the business model for a new era of insurance. The rapid proliferation of data coupled with AI solutions for insurance will reshape the insurance industry by unlocking business value and the potential to transform, optimize and innovate business operations beyond anything previously seen. It will elevate customer experiences, improve risk assessment, underwriting, billing and claims, and foster talent retention and acquisition.
According to Bain & Company, insurers deploying GenAI in claims management are already realizing a 20–25% reduction in loss-adjusting expenses and a 30–50% decrease in claims leakage.[2] Similarly, in Life, Annuity & Health (L&AH) insurance, AI is streamlining underwriting processes, accelerating policy issuance, and improving customer satisfaction—all while lowering overhead costs.
These measurable gains, when aggregated across the enterprise, translate into a compelling case for adoption. These are not speculative future benefits; they are being realized today by leading companies who have made the needed bold moves toward AI transformation.
Despite interest and enthusiasm, many insurers are still evaluating pilot programs and fragmented point solutions, lacking a strategic view and plan to maximize the value of AI across the organization. However, some insurers are partnering with trailblazing GenAI and Agentic AI-powered intelligent solutions like Majesco Intelligent Core for P&C and L&AH that provide a strategic foundation across the entire value chain, provides access to all the operational data, leverages embedded analytics, including AI models, BI, GenAI and Agentic AI to maximize investment and business outcomes.
John Chambers, Founder and CEO of JC2 Ventures and the former CEO of Cisco Systems, has said that the pace of AI adoption will be 5 times faster than the internet, so the window for experimentation is fast closing. The need to rapidly adopt and avoid the risk of falling behind—like Google search—is accelerating, with significant revenue and market implications.
Insurance AI, GenAI and Agentic AI are the business “new facilitators”. They communicate. They decide. They anticipate and work at speed with unprecedented levels of intelligence. They are redefining what’s possible in insurance.
AI, GenAI and Agentic AI Growth — The Case for Rapid Adoption
GenAI and Agentic AI represent a distinct inflection point. It is not simply an enhancement to traditional AI—it is a leap forward in capability, accessibility and business impact. They are being deployed across industries and companies to rethink and revolutionize the way businesses operate, benefiting both customers and the businesses themselves.
According to Gartner, over 80% of enterprises are expected to have GenAI in production environments by 2026.[3] PwC’s 2025 Global AI Jobs Barometer report found that industries most able to use AI achieve three times higher growth in revenue per employee compared to industries less likely to use AI (see Figure 1).[4] The report noted that Financial Services is one of the largest employers of AI-skilled workers, second only to the Information, Communication and Technology industry.[5]
Figure 1: Impact of AI usage levels on growth in revenue per employee (PwC)
Even more interesting is the rapid acceleration in revenue growth of the industries using AI since the introduction of ChatGPT 3.5 in 2022, as seen in Figure 2. In only two years, these industries changed from productivity laggards to leaders.[6] The acceleration is convincing evidence that investments in AI are paying off.
Figure 2: Impact of AI usage levels on revenue growth (PwC)
GenAI and Agentic AI: Insurance’s perfect match
Insurance’s dependency on document-heavy, data-rich business processes makes it ideal for automation from underwriting guidelines to claims forms, policy documents, applications, and customer communications.
GenAI can summarize large volumes of information in seconds, simulate decisions, generate explanatory content for customers, and assist agents and underwriters with real-time insights. Agentic AI is an autonomous agent that can make its own decisions. These agents are goal-oriented within their defined environments, able to complete their tasks and reach out to the human when they need help, rather than the other way around.
The current divide of using AI or not by insurers is highlighted in an October 2024 Boston Consulting Group report. The report notes 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.[7] Furthermore, 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.
AI’s impact on profit — Insurers should think decisively and holistically.
GenAI and Agentic AI are more than new tools—they are a strategic catalyst. The choice is no longer whether to adopt AI; it’s how fast and how broadly insurers will adopt and reimagine their business models. Those who act decisively will reap outsized returns. Those who wait will struggle to remain relevant in a radically reshaped industry.
As insurers consider use cases for GenAI and Agentic AI, all considerations should keep a broad strategic approach rather than a point solution one. Insurers who choose to think and act strategically—rather than tactically—can unlock compounded benefits that far exceed the sum of individual task improvements.
The operational and financial impact of this cumulative value is profound. The demand and need to drive down operational costs and improve profitability are underscored in our annual Strategic Priorities research, which found both to be insurers’ most important top-of-mind issues the past three years (Figure 3), highlighting the real opportunity for AI.
Figure 3: Insurers’ most important 2025 top-of-mind issues
Survey question & scale: How important or top of mind are these topics to your company? 1=Not at all; 10=Very much
Reducing operational costs in areas such as claims, billing, underwriting, and policy administration not only improves operational efficiency but can also substantially impact expense ratios, which subsequently strengthen overall financial metrics. End-to-end process optimization leads to leaner cost structures and improved expense ratios, which leads to improved profitability, combined ratios and competitive pricing.
GenAI and Agentic AI are ushering in a new era of intelligent and optimized insurance operations—one where processes are efficient and effective, decisions are data-driven, and employees are empowered with real-time insights and automation to elevate the customer experience that will drive retention and loyalty.
Unlocking the Cumulative AI Advantage: A Roadmap
GenAI and Agentic AI’s ability to reason and make autonomous decisions means it can extract insights from data and then turn those insights into action directly within business workflows—enabling the data-driven enterprise of the future.
For insurers, this requires new operating models that are AI and data-driven have the opportunity to leverage the full value of GenAI and Agentic AI, creating value across the entire value chain that can accumulate significant ROI in terms of time savings that can drive down expense ratios, which in turn can improve profitability and market competitiveness with pricing that can take advantage of lower costs.
Unfortunately, we are seeing numerous one-off solutions for GenAI and Agentic AI. This limits the potential operational impact and has the potential to reintroduce chaos to technologies that are on their way to refinement.
Instead, insurers must look at GenAI and Agentic AI as catalysts for enterprise-wide transformation and operational optimization. GenAI and Agentic AI value compounds over time as insurers embed them into more workflows across the entire value chain, extending business value beyond time and cost savings to include improved decision quality, faster innovation, employee satisfaction, and stronger customer loyalty.
As insurers select their vendors, they need to have an AI vision of scaling the business across the entire value chain to achieve measurable and impactful business results. As an example, if your policy and billing solutions have embedded GenAI and Agentic AI, but your Claims solution does not … consider the operational issues that creates – departments that are the haves or have nots, limited overall expense reduction, challenges with employees and differences in customer service. Instead of a well-oiled machine, it is challenged by the inconsistency.
Embracing GenAI and Agentic AI will help insurers redefine what it means to be agile, customer-centric, and future-ready. AI use will reduce operational costs, improving expense ratios and profitability. It will improve product pricing due to lower expenses that will create market competitiveness and growth. It will help attract, retain and onboard the best talent as we see 40% of the insurance workforce retire. It will improve customer and agent experiences by empowering the front-line with the information they need to deliver quality and consistent service.
Majesco has taken the strategic approach with AI, GenAI and Agentic AI across the entire solution portfolio to accelerate the business value and outcomes for our customers. It is real. It is here. It is amazing.
Need proof? Be sure to download Majesco’s thought-leadership, A Powerful Chain Reaction: The Financial and Operational Impact of GenAI and Agentic AI Across the Insurance Value Chain,for use cases and benchmarks split out by P&C and L&AH. Then, be sure to join us for our upcoming webinar, The Next Wave of Intelligence in Insurance Operations.
[1] “The Software Investor’s Handbook to AI (Artificial Intelligence),” RBC Capital Markets, May 9, 2025, https://www.rbcinsight.com/wm/Share/ResearchViewer/?SSS_5F3593D701731DCBE759BBDA903DFEA0
[2] Donnelly, Keith, et al, “The $100 Billion Opportunity for Generative AI in P&C Claims Handling,” Bain & Company, October 2024, https://www.bain.com/insights/100-billion-dollar-opportunity-for-generative-ai-in-p-and-c-claims-handling
[3] “Gartner Says More Than 80% of Enterprises Will Have Used Generative AI APIs or Deployed Generative AI-Enabled Applications by 2026.” Gartner Press Release, October 11, 2023, https://www.gartner.com/en/newsroom/press-releases/2023-10-11-gartner-says-more-than-80-percent-of-enterprises-will-have-used-generative-ai-apis-or-deployed-generative-ai-enabled-applications-by-2026
[4] “The Fearless Future: 2025 Global AI Jobs Barometer,” PwC, June 3, 2025, https://www.pwc.com/gx/en/issues/artificial-intelligence/ai-jobs-barometer.html (accessed June 4, 2025).
[5] “PwC’s 2025 Global AI Jobs Barometer: Industry Insights,” PwC, https://assets.turtl.co/pdfs/tenant=pwc/ai-jobs-barometer-industry.pdf (accessed June 4, 2025).
[6] PwC, “The Fearless Future: 2025 Global AI Jobs Barometer,” op. cit.
[7] “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