Why Agentic AI Is the Missing Link in BFSI's Digital Transformation
Sandeep Khuperkar is a visionary technology leader with over 28 years of experience in enterprise technology and more than 20 years in open source. He spearheads innovations like UnifyAI and AgenticAI, driving enterprise AI transformation across the BFSI sector. A mentor, speaker, and open-source advocate, he champions purposeful AI and holistic well-being.
In this exclusive interaction with M R Yuvatha, Senior Correspondent at siliconindia Startupcity, Sandeep Khuperkar shares insights on how Agentic AI is set to redefine digital transformation in the BFSI sector by bridging the gap between automation and autonomous intelligence.
For more than two decades, digital transformation in financial services has been a long relay from mainframe modernization to mobile-first experiences and now cloud migrations. Yet, despite this constant reinvention, many banks and insurers quietly acknowledge that transformation still feels unfinished.
The reason isn’t the absence of technology. It’s that digitalization has largely automated tasks, not thinking. The tools have modernized, but the workflows remain linear, driven by human coordination, dependent on manual judgment, and constrained by legacy logic. In a world that demands instant intelligence and frictionless execution, that model is showing its age.
The next breakthrough may lie in Agentic AI the emerging form of artificial intelligence designed not just to compute, but to decide and act. It could well be the missing link that helps BFSI move from automation to autonomy.
From Automating Tasks to Enabling Thinking Systems
So far, the industry’s use of AI has been anchored in prediction. Models could score credit, identify potential fraud, or forecast churn powerful capabilities, but essentially reactive. They waited for inputs, provided probabilities, and left the final call to human teams.
Agentic AI changes this dynamic. It introduces agency the ability for intelligent systems to reason, plan, and take multi-step actions in real time. These agents don’t just provide answers, they can handle end-to-end workflows while staying aligned with human oversight.
This moves enterprises from fragmented automation to intelligent orchestration.
A claims assistant no longer stops at anomaly detection; it can coordinate investigations, summarize findings, and suggest next actions. A risk agent can gather live context, simulate outcomes, and refine its understanding from feedback. It’s not just automation it’s adaptive execution.
Bridging the Transformation Gap
Across BFSI, one recurring challenge stands out: innovation happens in pilots, but scaling it across the organization remains elusive. AI-driven projects often stall after proof-of-concept because they struggle to integrate into core systems or comply with complex governance models.
This isn’t a failure of vision it’s a limitation of design. Most legacy processes were created for human operators, not for intelligent agents. Data sits in isolated systems, governance operates in silos, and AI models end up disconnected from live business flows.
Agentic AI directly addresses this gap. It acts as a connective layer that enables intelligent systems to collaborate with data, applications, and people in real time. Rather than replacing existing systems, it complements them stitching intelligence through the fabric of the enterprise.
Agentic AI isn’t just about automating tasks, it’s about enabling systems that can think, decide, and act.
Why BFSI Is Ready for Agentic AI
Few industries are as naturally suited for this evolution as BFSI. The sector already operates on clear logic, mature controls, and data-rich environments the very ingredients Agentic AI needs to succeed. Three reasons stand out:
1. Structured complexity is already mapped
Every lending, underwriting, or claims process follows a well-defined sequence of actions and exceptions. This structured nature makes it easier for intelligent agents to navigate and learn within safe boundaries.
2. Strong governance frameworks exist
Financial institutions already operate with embedded risk, compliance, and audit structures. Agentic AI can use these as guardrails, ensuring that autonomy remains accountable.
3. Data depth and context are inherent
With transactional, behavioral, and document-based data continuously generated, the sector holds a unique advantage. Agentic systems can use such diverse inputs to make contextually relevant decisions in real time.
In short, BFSI already has the discipline, data, and defined processes that intelligent agents need to demonstrate tangible, scalable impact.
How Agentic AI Reimagines Digital Transformation
1. From Automation to Orchestration
Traditional automation operates within predefined rules. Agentic AI goes further interpreting natural language, extracting insights from documents, and taking contextual actions across systems. It behaves like a digital workforce, capable of managing complete workflows under organizational policies.
2. Human Oversight Becomes the Core Principle
Instead of replacing people, Agentic AI builds them into the loop. Every process becomes a partnership machines handle the scale and repetition, humans provide judgment and empathy. This ensures speed with accountability.
3. Decision-Making Turns Continuous
Agentic systems don’t work in snapshots. They learn and evolve continuously refining fraud patterns, adjusting underwriting criteria, and improving efficiency with every outcome. Transformation becomes an ongoing capability, not a one-time initiative.
4. Infrastructure Becomes AI-Native
To truly benefit, enterprises will need data and application layers that can securely host intelligent agents alongside traditional workloads. Future-ready BFSI infrastructure will be context-aware embedding observability, compliance, and adaptive learning into its core.
The Human Factor
The real test of Agentic AI won’t be technological it will be cultural. Financial institutions that have long treated AI as a standalone tool will need to embed it into their organizational DNA.
This shift requires leadership that views AI not as a project, but as a capability shared across business, technology, and operations.
That means empowering teams to experiment safely, rewarding collaboration over hierarchy, and building trust in AI through transparency and explainability. The organizations that manage this balance between human insight and machine autonomy will unlock the full promise of intelligent systems.
From Silos to Systemic Intelligence
Beyond efficiency, Agentic AI encourages a deeper organizational shift: systems thinking.
Agents act as connectors between functions for example, a fraud-detection agent collaborating with a claims-processing agent and a compliance agent. Each focuses on its domain, but together they deliver outcomes that no isolated function could achieve.
This kind of collaborative intelligence isn’t futuristic it’s the natural progression of how data, reasoning, and enterprise logic converge.
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Building the Future, Together
Realizing this vision will require collaboration across the ecosystem.
Governments can enable innovation through regulatory sandboxes and open standards.
Industry leaders can co-create frameworks for interoperability and ethical AI.
Academia can advance the foundations of reasoning and safe autonomy.
Only through this collective effort can Agentic AI evolve in a responsible, human-aligned way.
Looking Ahead
So far, digital transformation in BFSI has focused on digitizing processes.
Agentic AI can digitize intelligence itself.
It transforms static workflows into living systems that think, act, and adapt. It brings enterprises closer to the idea of an AI-native organization one that doesn’t just use intelligence, but operates on it.
The institutions that embrace this early will set the benchmark for the next era of financial innovation not because they have more data or bigger budgets, but because they finally connect the missing link: intelligence that acts, evolves, and amplifies human judgment at scale.
