Published on November 4, 2025

Agentic AI Powered Modernization for Digital Transformation in Financial Services

This report brings together the voices of 20 senior leaders from the Financial Services industry in Bengaluru (India), who shared their experiences on preparing for Agentic AI. At the heart of the conversation was one theme: without data modernization, digital transformation cannot move forward. Leaders spoke candidly about the hurdles of moving away from legacy systems, the need for stronger governance, and the urgency of building AI-ready infrastructure that can scale. Their perspectives offer a grounded look at how financial institutions are rethinking data strategies to turn the promise of Agentic AI into real business impact.

CXO UNPLUGGED- BLR AUGUST Edition
Insights from the MongoDB and Accenture roundtable hosted by AIM

Agentic AI is moving from concept to practice across India’s BFSI landscape. At the MongoDB and Accenture roundtable hosted by AIM, senior leaders from major banks and insurers emphasized that data foundations and modernization are the critical enablers for Agentic AI and broader AI adoption. They discussed how agents can orchestrate workflows, augment human judgment, and drive transformation, but only when the underlying data and platforms are ready.

BFSI leaders converged on five key takeaways:

Modernization is non-optional: AI outcomes correlate strongly with cloud-native, multi-model data platforms, secure-by-design architectures, and front-to-back digitization.
Rise in Adoption: Adoption in Operations, CX, underwriting, and IT productivity is rising quickly; however, there are clear concerns in risk, compliance, and regulatory reporting, where Agentic patterns require strong guardrails, explainability, and human oversight.
Data realities define the ceiling: Siloed legacies, incomplete digitization in small markets, lack of real-time data pipelines, and a missing semantic middle constraint scale. Agents can help modernize data, but cannot fully substitute for sound data foundations.
Architectures are shifting: Enterprises are moving toward a layered agent stack design with orchestrator agents that interface with users and coordinate flows, domain super-agents that encapsulate business logic and tools in specific areas such as underwriting or KYC, and utility agents/tools for retrieval, extraction, calculators, and policy checks. Alongside this, they are adopting multi-model databases with native search, vector retrieval and re-ranking close to data, and enabling progressive interoperability with mainframes (legacy core IT systems).
Global Capability Centers (GCCs) are reinvention engines: Indian GCCs combine scale, talent, and partner ecosystems, enabling fast experimentation, risk-managed rollout, and institutionalization of new ways of working.

This report synthesizes the roundtable dialogue into a detailed narrative, beginning with the state of adoption of Agentic AI in organizations. It then explores the data and platform modernization journey that underpins successful deployment, followed by operating-model shifts and how Agentic AI is delivering measurable value.

BFSI CXOs, GCC leaders, and data/platform owners aiming to convert pilot momentum into enterprise‑grade orchestration will find concrete patterns, guardrails, and decision criteria to progress safely and at speed. Readers should download the full report for details on case examples and the complete playbook.