Transactional AI assistant: the intelligent agent for commerce

Virtual assistants have long been confined to making appointments or finding simple information. The advent of thetransactional AI assistant transforms this relationship: now, intelligent agents are able to carry out an end-to-end transaction on behalf of the user. They search for products, compare offers, fill the shopping cart, validate payment and follow up, while respecting the preferences and budget defined by the user. This chapter analyses how these assistants work, their benefits and the precautions to be taken.

What is a transactional AI assistant?

A transactional AI assistant is an intelligent agent that manages the entire purchasing cycle for a good or service. Given an instruction (“Book me a plane ticket to Barcelona”, “Buy a pair of shoes on sale”), it carries out searches, compares prices, checks availability, requests confirmations if necessary, and finalizes the transaction. The Visa Intelligent Commerce platform illustrates this trend: it allows users to set spending limits, while AI agents manage purchases (product search, vacation booking, shopping order). These agents perform routine tasks, while customers retain the final decision, and the AI agent market is expected to grow by 45% a year.

Agentic commerce and trust

The transition to this model, sometimes called agentic commerce, is based on trust. An article by Visa points out that AI agents are becoming the new commerce interface: they search, select, buy and manage transactions on behalf of consumers. For these agents to be accepted, three pillars are put forward:

1. User control: the customer sets limits (budget, product range, purchase conditions) and can validate or cancel the transaction.
2. Payment security: use of tokenization and passkeys to protect card information and reduce fraud. Payments are made via secure infrastructures.
3. Agent verification: platforms implement authentication protocols to ensure that the agent carrying out the transaction is authorized by the user.

These practices aim to build trust between the user, the agent and the merchant. In a context where malicious bots are proliferating, it is crucial to guarantee the authenticity and integrity of transactional agents.

Operation and technologies

Transactional assistants are based on several building blocks:

• Intelligent search: the agent queries several databases (e-commerce sites, comparators, marketplaces) to find the most relevant offers. It uses scraping techniques, APIs and machine learning to understand demand.
• Comparison and negotiation: some agents can negotiate prices or apply coupons. They calculate ancillary costs (delivery, taxes) to assess the total cost.
• Payment integration: the agent connects to a payment platform (virtual card, tokenized bank account) and automatically fills in the information. Technologies such as tokenization protect the user’s card.
• Tracking and after-sales service: after the transaction, the agent tracks deliveries, manages returns and contacts customer service if necessary.

These functions require a secure connection to merchant services, multi-factor authentication and rigorous management of personal data.

Benefits for consumers and businesses

Customer side

• Time-saving: the wizard handles the search, comparison and transaction, reducing manual steps.
• Optimizing expenses: by comparing prices and applying coupons, the agent helps you save money.
• Personalization: the agent knows the user’s preferences and budget, and proposes customized offers.
• Accessibility: the elderly and the disabled benefit from an assistant who simplifies shopping.

Merchant side and payment providers

• Increased conversion rate: transactions are smoother and faster, reducing cart abandonment.
• Loyalty: if the experience is satisfactory, the user will tend to entrust more transactions to the assistant.
• Data collection: merchants obtain richer information on preferences and behaviors, enabling them to fine-tune their offer.

Challenges and risks

Security and fraud

Transactional agents are a target for hackers. It is imperative to protect API keys, encrypt communications and use mechanisms such as card tokenization to limit exposure of sensitive data. Platforms must monitor suspicious transactions and detect fraudulent orders.

Privacy policy

Agents have access to personal data (purchasing preferences, banking information). Users must be informed of the data collected and its uses. The RGPD requires clear consent and the possibility of withdrawing one’s data.

Risk of errors and over-spending

The agent may misinterpret the request or order an unwanted product. To avoid this, platforms should require confirmations for large amounts and allow rapid cancellation.

Competition between agents

As assistants proliferate, merchants will need to adapt their interfaces to be compatible with different agents. Standardization of commerce APIs (product information, orders, payments) is essential.

Market situation and outlook

According to the Economic Times, the market for transactional agents is growing fast, driven by partnerships between Visa, Microsoft, OpenAI and other players. Consumers appreciate the convenience of these assistants, but demand transparency on security and data protection. Analysts estimate that within a few years, one in five customers could delegate the majority of their purchases to agents. Competition between platforms will lead to the emergence of marketplaces dedicated to agents, and interoperability standards will emerge.

Best implementation practices

1. Set limits: allow the user to set a spending limit and specify the categories accepted. Transactions above a threshold must be manually validated.
2. Reinforce security: use passkeys, double authentication and tokenization. Verify agent identity for each transaction.
3. Manage consent: provide clear information about the data collected, how long it will be kept and how it will be used. Facilitate the exercise of rights (access, rectification, deletion).
4. Provide human customer service: even if the agent manages the transaction, human support must be available in the event of a problem or dispute.
5. Test and audit: perform regular security and compliance audits. Check that the agent respects user instructions and is not being manipulated by malicious content (prompt injection).

Keyword table

Summary: A transactional AI assistant is an autonomous agent that manages the entire purchasing cycle: it searches, compares, negotiates, pays and tracks delivery. Visa and its partners are demonstrating that this model, called agentic commerce, replaces the old “search and buy” scheme. Users define spending limits and preferences, while the agent applies techniques such as tokenization and passkeys to secure payments and respect privacy. The market for transactional agents is growing fast (45% a year, according to the Economic Times). Benefits include time savings, expense optimization and a personalized experience, but challenges remain: security, privacy, possible errors and the need for interoperable standards. Companies deploying such assistants need to reinforce controls, inform users and maintain human support.