Gartner’s most consequential prediction for BFSI leaders isn’t about contact centres or chatbots. It’s about the fundamental restructuring of how buying and service decisions get made. By 2028, 90% of B2B buying will be AI agent intermediated, pushing over $15 trillion of B2B spend through AI agent exchanges. (Source: Gartner, Strategic AI Predictions for 2026 and Beyond, October 2025)

For banks, insurers, and financial services providers, this prediction requires a complete rethinking of the customer relationship. When your institutional clients’ procurement teams are replaced by AI agents that evaluate, select, and transact autonomously — your service model, your pricing structure, and your product discoverability must all adapt accordingly.

What AI Agent Intermediation Means for Financial Services

The transition to agent-intermediated commerce is already visible in B2B financial services. Corporate treasury teams are piloting AI agents that monitor market conditions, execute FX hedges, and initiate supplier payments. Insurance procurement platforms are testing agents that compare policy terms, negotiate premiums, and execute coverage changes — without human approval at every step.

By 2030, Gartner forecasts that 20% of monetary transactions will be programmable — enabling autonomous commerce and machine-driven financing. (Source: Gartner, October 2025) The technical infrastructure for this future — including the Model Context Protocol (MCP), Agent-to-Agent (A2A) Protocol, and Agentic Commerce Protocol (ACP) — is being developed and deployed right now.

For BFSI customer service teams, this creates an urgent question: are your service APIs, your product data structures, and your resolution workflows designed to be consumed by AI agents — or only by human users navigating a web interface designed in 2019?

The Products Designed for API-First Commerce Will Win

Gartner is explicit: products designed with composable microservices, API-first, cloud-native, headless architectures will establish a significant competitive moat in the agent-intermediated economy. (Source: Gartner, October 2025) In practical terms, this means a financial institution whose loan products, insurance policies, or investment accounts are accessible via clean, well-documented APIs — with real-time pricing, eligibility logic, and instant fulfilment — will be the one that AI agents discover, recommend, and transact with.

Forrester adds a critical warning: enterprises will defer 25% of planned AI spending into 2027 as fewer than one-third currently link AI initiatives to tangible P&L changes. (Source: Forrester, Predictions 2026, October 2025) The BFSI firms that overcome this paradox are those that invest in platforms with proven ROI — not experimental tools.

This is precisely why Pega’s orchestration-first architecture, which connects front-end service experiences to back-end systems via clean workflow APIs, positions BFSI institutions for the agentic future without requiring a complete infrastructure replacement.

The Trust Economy: Verifiable Data as Currency

In the AI agent-intermediated economy, verifiable operational data becomes a currency. Agents will only transact with institutions whose data is accurate, real-time, and trustworthy. An AI agent that recommends an insurance policy with stale pricing, or a bank loan with inaccurate eligibility criteria, loses trust immediately — and that trust doesn’t return.

Gartner describes this as a “trust-based economy where API-driven architectures and verifiability are prerequisites for participation.” (Source: Gartner, October 2025) For BFSI customer service, the implication is straightforward: the institutions that invest now in real-time data synchronisation, accurate product information, and verifiable service APIs will be the ones that AI agents route customers to. The institutions that don’t will be systematically excluded from agent-mediated discovery.

Novitates’ implementation of Pega Customer Service includes deep integration with core banking systems, policy management platforms, and real-time pricing engines — ensuring that every customer interaction, whether initiated by a human or an AI agent, is powered by accurate, live data.

Preparing Your BFSI Service Model for 2028

The strategic roadmap is clear: audit your service APIs for agent-readiness; invest in orchestration platforms that connect service workflows to real-time data; build compliance and verification capabilities that meet the trust requirements of agent-mediated transactions; and deploy AI-powered service channels that demonstrate proven outcomes today.

The institutions that treat the 2028 Gartner prediction as a planning horizon — not a distant warning — will be the ones that own the AI agent-intermediated financial services market. The rest will be playing catch-up in a market that has already moved.