Context
Artificial Intelligence is moving in digital payments from being an assistant to becoming an authorised agent.
Traditional AI mainly helps users by detecting fraud, answering queries or recommending payment options. Agentic AI can go further by taking predefined actions—such as comparing products, selecting a payment method and completing an authorised transaction on behalf of the user.
In India, the National Payments Corporation of India (NPCI) is developing a proposed Unified Agent Protocol (UAP) and an AI-agent registry to support trusted agent-led payments over UPI.
What Is Agentic AI?
Agentic AI refers to AI systems capable of independently planning and executing tasks within rules set by the user.
In commerce, this creates agentic commerce, where an AI agent may:
Understand need → Compare options → Select product/service → Choose payment route → Execute authorised payment
For example, a user may allow an AI agent to purchase groceries within a fixed monthly budget. The agent can act automatically as long as the transaction remains within predefined conditions.
How Is It Different from Traditional AI?
- Traditional AI: recommends or assists; the user performs the final action.
- Agentic AI: can execute the action itself within predefined permissions.
The user does not surrender unlimited financial control. Spending limits, merchant restrictions and authentication rules can define the agent’s authority.
India’s Emerging Agentic-Payment Ecosystem
- Unified Agent Protocol
NPCI is reportedly developing UAP to establish identity, consent and accountability for AI agents transacting over UPI.
A proposed registry could help verify authorised agents and monitor their activity.
- UPI HELP
NPCI’s UPI HELP Assistant already uses AI for:
- payment-related queries;
- transaction-status checks;
- complaint tracking;
- management of UPI mandates.
However, final decisions remain with the customer or issuing bank, highlighting the importance of human and institutional oversight.
Why Does Agentic AI Matter?
- Automated Transactions
Routine or recurring payments can be executed automatically within predefined limits, reducing repeated user intervention.
- Personalised Financial Decisions
An agent can compare:
- prices;
- payment instruments;
- rewards;
- spending limits;
before selecting the most suitable option.
- Programmable Commerce
Transactions can become condition-based rather than merely user-initiated.
For example, an agent may purchase a product only when:
Price falls below a set level + Budget limit is available + Approved merchant condition is satisfied
This makes payments responsive to pre-set rules.
Key Risks
- Consent ambiguity: Whether the agent acted within the exact authority granted by the user.
- Fraud and privacy: AI agents may handle sensitive financial and behavioural data.
- Liability: Responsibility may be unclear if an autonomous transaction is incorrect or unauthorised.
Way Forward
- Permission-based autonomy: Define transaction limits, merchant categories and time restrictions.
- Verified agent identity: Use trusted registries and auditable digital credentials.
- Human override: High-value or unusual transactions should require explicit user confirmation.
FAQs
Q1. What is Agentic AI?
AI capable of independently planning and executing tasks within predefined user permissions.
Q2. What is agentic commerce?
Commerce in which an AI agent can search, compare, order and potentially pay on behalf of a user.
Q3. What is UAP?
A proposed NPCI framework for trusted and accountable AI-agent transactions over UPI.
Q4. Does Agentic AI get unlimited access to user money?
No. Its authority can be limited through spending caps, merchant rules and authentication requirements.
Q5. What is the main regulatory concern?
Ensuring consent, accountability, security and consumer protection when AI agents execute financial transactions.
