Introduction
The world of payments has steadily been reducing friction over the years, starting with cash, then moving on to cards, then digital wallets, and finally the one-click payment option. Every one of these developments has made payments faster, smoother and more convenient. In each step along this path however, one underlying principle always held true, which is that the ultimate financial decision still rested with a human being.
Recent developments, notably by major payment networks, hint that the next phase of financial innovation may be about more than just simplifying payments-it may be about changing who makes purchasing decisions in the first place. In April 2025, Visa rolled out Visa Intelligent Commerce, allowing AI agents linked with platforms like ChatGPT, Anthropic Claude, and Microsoft Copilot to browse for products, make purchase choices, and execute transactions without direct human input. Around the same time, Mastercard released its own Agent Pay framework. Designed to support self-governing commercial payments through an ecosystem of connected devices and AI agents.
The Rise of Agentic AI in Financial Services
The use of AI in financial services is not new; the industry has for long leveraged it to detect fraudulent activities, perform credit risk assessment, Monitor transactions, identify suspicious activity, and monitor accounts. Until recently, the aforementioned functions have been solely performed as decision-support tools, that is, tools assisting humans make their decisions, rather than acting as actual decision makers.
Agentic AI represents an interesting departure from this paradigm; Instead of just providing recommendations, a given AI agent can be delegated a broader objective, then formulate and pursue an optimal strategy that may involve complex decision-making. A consumer could task an AI agent to “handle my recurring subscription services”, “find the cheapest travel deals” or “replenish my household supplies when stocks run low”.
The AI then makes choices from multiple available alternatives, pays for a selected item, and continues on its assigned goal without requiring approval at each step of the process. Such a prospect has evident benefits; reduced transaction costs, improved efficiency, personalized purchases and a seamlessly smooth consumer experience, for the consumer, and streamlined procurements, enhanced operational efficiency and faster decision-making process for a business, but the same benefits present novel governance issues. The choices they make can be driven by algorithms, proprietary models, or enormous datasets of consumer behaviour that the end-users themselves may have little or no access to, and so the shift from human-directed to AI-driven payments raises issues beyond simple Cybersecurity and operational risk into the very territory of consumer autonomy, accountability, and fairness.
Consent, Accountability, and the "Moral Crumple Zone"
A core principle underlying most modern financial regulation is the notion of consumer consent. Whether the regulation stems from consumer protection law, banking or financial services regulations or data protection laws, legal frameworks presuppose that individuals consciously consent to the financial transactions that impact them. Autonomous financial agents challenge this paradigm by altering the context in which consumer consent is sought and granted.
While it is possible to get a consumer’s consent to let an AI agent manage his travel booking transactions or subscription services, it is unclear whether this translates to consent over the AI agent’s autonomous decisions with regard to every individual booking or transaction in pursuit of that broader task. It is imperative to differentiate authorization from delegation; if a consumer makes a purchase by keying in his card details, it is quite straightforward as to where responsibility lies. If an AI agent makes an autonomous purchase decision with its own algorithm based on its own unique perception of what a ‘best buy’ entails, by paying with his linked account without requiring human review at the point of transaction, then the interpretation of his consent is undeniably different.
Privacy, Profiling, and Financial Autonomy
Agentic AI systems, by their nature, require access to substantial amounts of personal data, in order to successfully make purchases. An AI agent will need information about a consumer’s purchase history, income levels, location data, travel habits, subscription preferences, and behavioural trends. The more information the AI agent is fed about a consumer, the better it will be able to predict and execute future transactions and purchases for that user.
Traditional payment systems were built to simply record past transactions, while agentic AI is built to analyse, learn from and optimize future behaviour. As a result, financial data becomes the key for prediction, rather than mere recollection. This has implications for profiling and manipulation. An AI agent that intimately understands consumer preference could wield significant power to influence purchasing behaviour.
In addition, a consumer might find it difficult to distinguish between when an AI agent is making an informed purchase choice on behalf of the consumer and when an AI agent is pushing them towards a specific purchase. For banks and tech companies these may initially seem to be ethical concerns but will likely also pose serious compliance risks given heightened expectations on data governance, particularly as regulators look to enhance the oversight of AI-driven systems.
The Regulatory Challenge Ahead
The arrival of agentic AI is a phenomenon of the kind we have observed throughout the history of technology development. Innovation appears first, followed by regulation. Most existing rules on payments, banking and consumer protection were developed at a time when human consumers retained direct control over purchasing decisions. Agentic AI systems represent a fundamentally new paradigm, with control over such decisions delegated to AI systems.
This does not necessarily imply the development of a completely new regulatory framework, as core principles regarding transparency, accountability, fiduciary duties and consumer protection remain equally relevant, but their implementation will likely need to evolve significantly. Globally regulators have begun to move in this direction, from the OECD’s AI Principles on transparency and human-centricity, to the NIST AI Risk Management framework for assessing and managing risks, and within India the Digital Personal Data Protection Act, 2023 reflects a push towards accountable data handling, of which agentic financial systems will become a prominent component.
AMLEGALS Remarks
The emergence of agentic AI is more than a technological advancement, it marks a shift in the role of individual decision-making in financial transactions. For the first time, established payment networks are creating systems where algorithmic execution will drive purchases beyond simple recommendation. While the benefits for efficiency are undeniable, these should not overshadow the inherent legal and ethical implications, as key concepts such as consumer consent, accountability, and autonomy take on a new meaning within the context of autonomously executed payments.
Fintechs, banks and e-commerce businesses should see agentic AI not just as a business opportunity but also as a governance challenge that needs to be proactively managed. Companies with a clear strategy for transparency, human oversight, data protection and accountability will undoubtedly be better positioned to adapt as regulations inevitably mature.
For any queries or feedback, feel free to connect with Hiteashi.desai@amlegals.com or Khilansha.mukhija@amlegals.com