By Sudhir Nambiar
The checkout experience has taken on new meaning. What used to be a clean handoff from bank to merchant is now a high-sensitivity, high-stakes moment — a frontline test of trust for customers and the financial institutions powering the transaction. As digital payments expand into broader financial services, embedded finance, real-time networks and AI are reshaping expectations. Customers are not just completing a purchase. They are evaluating whether the systems supporting them are smart, secure and aligned to their intent.
A new layer of complexity is also rising fast: agentic commerce, where AI agents act independently on behalf of users. According to a 2025 market report, the agentic commerce market is projected to reach $5.19 billion by 2033, growing at a compound annual rate of more than 32% from 2021. Financial institutions must now design experiences that serve real people and the AI acting on their behalf. This shift will reshape payment flows, risk models and the infrastructure that banks must build to support them.
Fixing friction at the root
Persistent design and infrastructure flaws increasingly undermine the expectation of seamlessness at checkout. Small errors compound: Rigid payment options, cryptic error messages, forced redirects for security verification multifactor authentication and manual data entry can all diminish customer confidence in seconds.
These issues quietly erode trust. A failed transaction may quietly downgrade a customer’s view of banks. These moments often reflect a misalignment between front-end interfaces and back-end logic handling routing, authorization or fraud detection.
Banks must address these gaps directly by enabling smarter, context-aware responses and real-time retry logic built into the payment fabric itself.
Preparing for AI agents to act independently
AI agents now have the ability to act independently on behalf of a user, guided by predefined preferences, risk settings and contextual awareness. These agents are not simply bots but rather decision makers equipped with secure credentials and policy awareness that lets them choose what is supposed to be the right action at the right moment. They will request payments, flag suspicious activity or switch payment methods — all in real time and without human prompts.
Major networks, including Visa and Mastercard, are laying the groundwork for this future. Visa’s “Intelligent Commerce” and Mastercard’s “Agent Pay” initiatives aim to standardize how these agents interact with payment infrastructure, using tokenized credentials and intelligent verification systems.
For banks, this means:
- Supporting agent credentialing.
- Enabling permission-based transaction frameworks.
- Interpreting intent, both human and machine, and applying compliance logic at the edge.
This new mode of interaction demands payment systems that are fully policy-aware and dynamically responsive. Systems must understand not just what users want, but what their agents are authorized to do and under what conditions.
Financial institutions that delay in preparing for these autonomous financial flows risk being left behind by systems optimized for machine speed and machine logic.
Using real-time rails as intelligent layers
Real-time payments are a core enabler of agentic commerce. Unlike traditional rails, RTPs carry metadata and confirmation signals, allowing immediate downstream updates.
Today, FedNow and Clearing House’s RTP network both offer:
- Instant clearing and settlement.
- Metadata-rich messages (e.g., invoice data, account selection hints).
- Support for innovations including “request to pay” pull notifications.
An AI agent managing bill payments can use RTP to guarantee timing, route around low liquidity or avoid duplicating a transaction. Banks must support both rails and build retry and failover logic that allows seamless handoffs between them, especially for time-sensitive or policy-restricted payments.
Embedding clarity, control and context into payment stacks
For banks, designing checkout isn’t about tweaking UI. It’s about rethinking the infrastructure that enables fast, confident, policy-aware decisions at every step of a transaction.
Clarity means helping customers and their AI agents understand what is happening, what their options are and what actions they can take. If a card is declined, the system should guide the next step, not drop the session.
Control means giving users the power to adjust not just at the surface, but deep within preferences, payment methods and approval settings. Agents might need to pause a recurring payment, reroute a bill through a different account or switch rails in real time.
Context means knowing the transaction environment (location, device, past behavior) and shaping the options accordingly. This reduces false declines, improves fraud detection and allows smoother retries across networks.
AI is the orchestration layer that turns this intelligence into real-time action. When integrated with the bank’s payment systems, AI can flag anomalies, suggest alternatives or switch methods without breaking flow or requiring re-authentication.
Banks that deliver on this framework will support better checkout while also enabling new forms of customer interaction, where trust is earned through intelligence and adaptability at every touchpoint.
Creating intelligent checkout systems
Agentic systems cannot operate effectively on yesterday’s data or hardcoded logic. They require a live, responsive backend that adapts to each context and transaction condition. That starts with real-time observability — not just static dashboards, but telemetry that AI agents can act on instantly.
This includes:
- Modular back-end services that update agent policy engines dynamically.
- Clear retry logic and routing paths that shift based on transaction context.
- Visibility into device signals, payment history and user behavior patterns.
But intelligence must also be operational. Banks should simulate these systems under pressure, testing how agentic flows perform at peak load, how they respond to fraud triggers and what happens when fallback rails are needed. These environments should replicate real-world conditions, including AI-human-machine interactions.
Finally, no system is intelligent unless it’s compliant. Banks must embed regulatory awareness into every decision loop, mapping out what agents are allowed to do, recording actions for audit and providing clear opt-in, opt-out and rollback controls for users.
Getting these systems right is not optional. It’s the foundation that makes the next-generation checkout experience not just possible, but trustworthy.
Intelligent checkout is the next competitive edge
Speed and convenience once defined great checkout. Now, intelligence does. As AI agents begin to manage financial flows on behalf of users, the definition of a seamless experience shifts.
Banks that meet this moment by embedding adaptability, transparency and agent-aware systems will not only reduce friction. They’ll transform checkout from an endpoint into a relationship moment.
Trust, once eroded by small mistakes, can be rebuilt through smarter flows. And in a future where AI, payments and identity collide, banks that lead here will own the rails that everyone else relies on.
Sudhir Nambiar is managing director and financial services leader for North America at Brillio.
