We stand at a defining moment in the evolution of customer experience in banking. The convergence of generative AI, Agentic AI-based workflows, and digital orchestration is not just incrementally improving how we serve customers – it is fundamentally redefining what customers expect from their banking relationships and what banks and financial institutions can deliver at scale.
The Strategic Context: Why Gen. AI in CX Matters Now: The Macro Forces Reshaping Banking CX
Three structural shifts are converging to make generative AI not just desirable but essential for competitive banking:
First, customer expectations have fundamentally changed. Research from KPMG’s Global Customer Experience Excellence study shows that 97% of consumers have been impacted by inflation and cost-of-living pressures, yet 61% remain willing to pay more to organisations they perceive as ethical and customer-centric. In India, this translates into customers who are simultaneously fee-sensitive and loyalty-driven—they will switch banks over poor service, but they will stay and deepen relationships when they feel understood and valued.
Second, digital adoption has reached critical mass. UPI transactions, mobile banking penetration, and digital lending have moved banking interactions from branch-led to channel-agnostic. Customers now expect the same speed, personalisation, and convenience they experience with e-commerce platforms. Traditional IVR systems and email-based support are no longer acceptable—customers expect instant, contextual, and conversational engagement.
Third, the economics of scale have fundamentally shifted. KPMG’s research highlights that technology has often been deployed to deflect customers into low-cost channels without ensuring those channels deliver quality experiences. The result has been declining customer experience scores globally. Generative and agentic AI solutions offer a way out of this trap: they enable us to scale intelligent, empathetic interactions without proportionally scaling headcount or infrastructure costs.
Why Gen. AI is Central to Digital Transformation
Global AI investment is exploding, creating the foundation for Gen. AI-led CX in banking.
This growth underpins why boards are prioritising AI as a strategic, not incremental, lever in digital transformation.
For Indian banks and NBFCs, this means AI-first CX is not a niche experiment; it is where competitive advantage and cost efficiency are heading.
The Evidence: What Generative AI Delivers in Banking CX: Global Research and Expectations
Cisco’s 2025 global research on agentic AI in customer experience surveyed nearly 8,000 business and technical decision-makers across 30 markets. The findings are unambiguous:
- 93% believe agentic AI will enable technology partners to deliver more personalised, proactive, and predictive services.
- 88% are confident that agentic AI–led customer experience will help their organisations achieve strategic goals.
- 81% expect vendors that deploy agentic AI strategically to gain a competitive advantage.
More striking is the speed at which customers expect this shift. Respondents predict that,
- 56% of their interactions with technology partners will be handled by agentic AI within 12 months,
- rising to 68% within three years and **79% within a decade.
Global Hall of Fame: Maybank, KBank, first direct:
KPMG’s CX Hall of Fame highlights banks like Maybank (Malaysia), KBank (Thailand) and First Direct (UK) that use AI not to replace human connection but to orchestrate it more intelligently. These institutions deploy AI for:
- Proactive nudges (bill reminders, savings opportunities)
- Autonomous banking (automated top-ups, payment scheduling)
- Personalised in-app guidance that feels human, not robotic
Crucially, these banks maintain top-tier customer satisfaction scores while operating leaner support models – proof that AI-led CX, when designed correctly, enhances both experience and economics simultaneously.
Gartner reinforces this, predicting that by 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention, reducing customer service operational costs by approximately 30% in many organisations.
The Leadership Imperative
Multiple research initiatives on AI-driven transformation in financial services marketing emphasises that leadership-centred models – combining transformational, adaptive, and strategic leadership – are essential to translate AI capability into sustained customer value.
In practice, this means:
- Setting CX-led, not tech-led strategies. Gen. AI initiatives must be anchored in measurable customer value -NPS, CLV, complaint resolution time, and collections cure rates -not just “we deployed a chatbot.”
- Cross-functional squads. CX transformation cannot be owned by IT alone. The most successful AI programmes bring together business, risk, operations, compliance, data, and IT teams from day one.
- Executive sponsorship with authority. When the CFO, CRO, and Chief Customer Officer jointly sponsor an AI initiative, data silos break down rapidly. When delegated several levels down, initiatives tend to remain stuck in pilots.
Data as the Strategic Bottleneck
KPMG, citing Gartner, reports that 85% of AI implementations fail, largely due to poor data quality. This is not an exaggeration -Gen. AI is only as intelligent as the data it can access.
If customer interaction history resides in one system, product holdings in another, and servicing notes in a third -all disconnected -the AI cannot deliver context-aware, personalised responses.
Successful deployments require:
- Unified customer data platforms with API-first integration to core banking, CRM, LOS, and collections systems.
- Strong data governance with clear ownership, quality standards, and refresh cycles.
- Continuous feedback loops where AI interactions are logged, analysed, and used to retrain models.
PwC’s work on generative AI in banking similarly emphasises that data is the “fuel” for Gen. AI -without clean, governed, contextual data, even the most sophisticated models underperform.
Responsible AI: Non-Negotiable in BFSI
In a regulated sector like banking, Responsible AI is not a “nice to have” -it is table stakes. KPMG outlines an eight-principle framework covering fairness, explainability, accountability, security, privacy, safety, data integrity, and reliability.
Practically, this means:
- Bias testing and fairness audits
- Explainability protocols
- Human-in-the-loop for high-stakes decisions
- Audit trails
The Path Forward: From Pilots to Production at Scale
- Design Around Journeys, Not Tools
- Set Measurable CX and Cost Targets
- Blend Human and AI to deliver a seamless and frictionless experience.
- Invest in Data, Governance, and Change Management
- Move Fast but Move Responsibly!
Also Read: Creating Customer-First NBFCs Through Digital Transformation
Conclusion: The Strategic Imperative
Generative and agentic AI are not future technologies – they are production-ready, proven, and rapidly becoming baseline expectations in banking customer experience. Gen. AI is reshaping banking by making services more secure, efficient, and customer-friendly while automating repetitive tasks and reducing operational costs. Banks across the spectrum have shown that when Gen. AI orchestrated experiences, not just reduce cost, it also improves loyalty, advocacy, and lifetime value (CLTV).
For Indian banks and NBFCs, the opportunity is clear: Deliver instant, contextual, multilingual, and humanized service at a fraction of today’s cost-to-serve.
Views expressed by: Mahendra Bindra, Head – Customer Excellence, Unity Small Finance Bank Ltd
Elets The Banking and Finance Post Magazine has carved out a niche for itself in the crowded market with exclusive & unique content. Get in-depth insights on trend-setting innovations & transformation in the BFSI sector. Best offers for Print + Digital issues! Subscribe here➔ www.eletsonline.com/subscription/
