Insurance transformation in action: Bajaj General Insurance
Bajaj General Insurance in India presented the incredible transformation work they have accomplished.
As part of the Qorus Innovation in Insurance Awards 2026, we selected a few of the insurance players whose projects impressed us the most. Among them, Bajaj General Insurance in India presented the incredible transformation work they have accomplished.
What transformation strategy has your organization led in recent years?
Bajaj General led a deliberate, enterprise wide transformation to reimagine how insurance services are designed, delivered, and scaled-placing accessibility, intelligence, and trust at the core. The vision was to move from fragmented, manual, and time bound operations and CX to a unified, AI led, digital first operating and Customer First model that serves customers seamlessly, anytime and in any language.
The transformation spans business and operating models (AI driven self service replacing agent dependency), technology (cloud native, API orchestrated platforms embedded with AI, NLP, and GenAI), customer experience (24×7, multilingual, omni channel journeys), and workforce enablement (automation of routine work, real time insights, higher value roles).
Equally critical was a culture shift-from process centric execution to customer centric innovation, continuous learning, and data led decision making. This strategy has fundamentally reshaped resilience, scalability, and inclusion, delivering measurable impact at both enterprise and societal levels.
What prompted this strategic transformation?
The transformation was prompted by a convergence of rising customer expectations, market disruption, and operational constraints.
Customers and farmers increasingly demanded instant, transparent, and multilingual access to services, while traditional, agent dependent models proved slow, error prone, and difficult to scale-especially during peak seasons, crises, or natural calamities.
At the same time, competitive pressure from digital first players exposed the limitations of fragmented systems and manual workflows. Internally, growing volumes, legacy platforms, and workforce fatigue signaled the need for a more resilient and future ready operating model. The leadership team recognized that incremental improvements would not suffice. The long term goal was to build an enterprise that could scale intelligently, operate continuously, and serve inclusively-without proportional increases in cost or risk. This required a fundamental shift toward AI led, data driven, and platform based operations, making transformation a strategic imperative rather than a technology upgrade.
What have been the most significant changes implemented, and how were they led?
The most significant change was a decisive shift from fragmented, manual operations to an AI led, platform driven enterprise model.
Technologically, we embedded AI, NLP, Voice, and GenAI directly into core customer and claims journeys-moving beyond pilots to business critical systems that operate 24×7 at scale. Legacy, siloed processes were replaced with API orchestrated, cloud native platforms enabling real time integration, resilience, and surge handling.
Organizationally, the operating model shifted from agent centric execution to digital self service at scale, freeing employees to focus on complex, value adding work. Leadership sponsored cross functional squads spanning CX, technology, operations, and compliance, ensuring speed without compromising governance. Culturally, leadership championed a move from process adherence to customer outcome ownership, backed by data driven decision making, experimentation, and continuous learning. This top down commitment transformed AI from a tool into a core enterprise capability.
What unique or key transformation practices do you follow to ensure success?
Our transformation success is anchored in a disciplined set of execution practices that combine speed, scale, and governance. We adopted Agile, product centric delivery, with cross functional squads spanning CX, technology, operations, and compliance-enabling rapid experimentation, continuous releases, and clear outcome ownership.
A cloud native PaaS strategy underpins scalability and resilience, allowing elastic capacity during peak seasons without infrastructure or workforce strain. DevOps practices ensure faster time to market while maintaining security, regulatory compliance, and platform stability. We actively collaborate with fintech and AI partners, blending startup agility with enterprise rigor to accelerate innovation in areas such as NLP, ASR, and GenAI. Continuous monitoring, analytics driven feedback loops, and monthly model refinements ensure solutions evolve with customer behaviour. Most critically, leadership reinforces a “build–measure–learn” culture, embedding transformation into everyday decision making rather than treating it as a one time program.
How has your workforce been engaged and transformed through this journey?
Our workforce was central to the transformation-not a downstream recipient of it. We invested heavily in upskilling existing teams across AI literacy, agile delivery, data driven decision making, and digital CX, ensuring business and technology roles evolved together. Selective recruitment augmented this with specialist capabilities in AI, cloud, and analytics, while leadership development programs equipped managers to lead cross functional, product led teams.
To support adoption, we shifted ways of working-from hierarchical delivery to empowered, mission driven squads with clear outcome ownership. Real time dashboards, AI enabled tools, and simplified workflows reduced manual effort and increased confidence in decision making. Culturally, leadership emphasized experimentation, learning from failure, and customer outcome accountability over process adherence. As a result, employee engagement improved, attrition in high stress roles reduced, and teams transitioned from repetitive execution to higher value, insight driven work, creating a more skilled, motivated, and future ready workforce.
What measurable outcomes demonstrate the success of your transformation?
The transformation has delivered measurable, enterprise wide impact across customer experience, operations, workforce effectiveness, and inclusion. Digitally, over 95% of service interactions are now handled through AI led self service channels, enabling 24×7 availability and handling peak demand without incremental manpower. Claim and query resolution times reduced by 50–99%, while first time success rates exceeded 80%, significantly improving accuracy and trust.
Customer outcomes strengthened materially, with CSAT exceeding 4.5/5 and NPS improving by over 15 points, reflecting faster, simpler, and more transparent journeys. Operationally, automation reduced manual effort and error rates by ~60%, delivering sustained efficiency gains. For employees, routine workload reduction enabled a shift to higher value roles, improving engagement and productivity. From an ESG perspective, multilingual, always on digital access expanded inclusion-empowering rural and underserved users at scale. Collectively, these outcomes validate the transformation as durable, scalable, and value creating.
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