One of the most important corrections in BFSI technology strategy arrived in June 2025, when Gartner predicted that by 2027, 50% of organisations that planned to significantly reduce their customer service workforce due to AI will abandon those plans. (Source: Gartner, June 2025) This isn’t AI failing to deliver — it’s executives discovering that the most powerful model isn’t human replacement. It’s human amplification.

The 95% of customer service leaders who plan to retain human agents are building something more sophisticated than a chatbot layer: they’re designing a hybrid operating model where AI handles everything it can handle well, and humans handle everything that requires genuine judgment, empathy, and relationship depth. In BFSI, this distinction matters enormously.

What AI Handles Well in BFSI Customer Service

The most important exercise any BFSI contact centre leader can do right now is an honest audit of their interaction volume by complexity and emotional load. The evidence consistently shows that the highest-volume, lowest-complexity interactions — balance inquiries, statement requests, address changes, basic fraud alerts, payment confirmations, policy renewals — are the ones where AI delivers the fastest, most measurable returns.

McKinsey estimates generative AI could reduce human-serviced contacts by up to 50% in banking, telecommunications, and utilities through exactly this kind of deflection. (Source: McKinsey, 2025) At Aflac, Pega-powered self-service automation alone reduced operational costs by $4 million per year. (Source: Pega.com/customers/aflac) These outcomes are achieved not by replacing agents but by ensuring that agents are never handling work that a well-designed AI system could handle better.

What Humans Do Better — And Always Will

Gartner identifies three capabilities that agentic AI will not replace in BFSI customer service: the ability to handle genuinely novel situations with no precedent in training data; the ability to deliver authentic empathy in moments of customer vulnerability; and the ability to exercise regulatory judgment in ambiguous or contested situations.

For a customer calling about a mortgage payment deferral during a family bereavement, the data processing can be automated. The conversation cannot. For a private banking client navigating an estate, the document retrieval and eligibility checking can be AI-driven. The relationship management cannot.

Gartner’s three trends shaping the future of customer service through 2028 emphasise exactly this point: automation will handle inbound volume; AI assistants will augment human agents with real-time guidance; and the quest for customer value will shift service from transaction processing toward outcome-focused advisory. (Source: Gartner, June 2025) The winning BFSI institutions will be those that deploy AI for the former and invest in human excellence for the latter.

The Agent Wellbeing Dividend

One of the most undervalued benefits of AI-augmented BFSI customer service is its impact on agent wellbeing — and the operational benefits that flow from improved agent experience. 74% of contact centre agents are at risk of burnout. In BFSI, where interactions involve financial stress, fraud, and complex regulatory queries, this statistic likely understates the reality.

Deloitte’s research shows that AI-supported agents are 35% less likely to feel overwhelmed during customer calls. (Source: Deloitte, AI Customer Service Report, 2025) When agents are less overwhelmed, they’re more accurate. When they’re more accurate, compliance improves. When compliance improves, regulatory risk decreases. The wellbeing dividend from AI-augmented BFSI service operations is measurable across every level of the P&L.

Pega’s Unified CSR Desktop directly addresses agent cognitive load: one view, full customer context, real-time AI guidance, and automated post-call wrap-up — removing the primary sources of agent stress without removing the agent.

Designing the BFSI Human-AI Partnership

The practical design of a high-performing human-AI customer service model in BFSI involves four decisions: which interactions are fully automated; which are AI-initiated with human escalation available; which are human-led with AI support; and which are exclusively human. Getting this taxonomy right — and routing every interaction to the right tier automatically — is the orchestration challenge that Pega solves.

Novitates works with BFSI clients to design this interaction taxonomy, implement Pega’s routing and escalation logic, and measure outcomes across every tier. The result is a service operation that is simultaneously more efficient, more compliant, and more human — not less.