The European Union’s new transparency rules for artificial intelligence are a timely warning for Indian technology companies. Since August 2, providers and deployers covered by Article 50 of the EU AI Act must tell people when they are interacting with certain AI systems and meet new requirements for AI-generated content. Compliance matters, but a label alone will not build trust in products that can misunderstand a request, act on incomplete information or send an error through a connected workflow.
India Technology News has recently highlighted the scale of the opportunity. One report described AI-powered public services and emergency-response systems operating across India. Another covered a multilingual voice platform designed to support more than 216 languages and dialects. These systems can make digital services more accessible, especially for people who do not use English. They also make the cost of an unnoticed mistake much larger.
Indian AI companies selling into global markets should go beyond a disclosure badge. They should give users a correction receipt.
A correction receipt would appear after an AI system completes a consequential interaction or action. It would explain, in plain language, what the system understood, what it did, which information it relied on, who owns the outcome and how the user can challenge or correct it. The receipt should be short enough to read and specific enough to be useful.
Consider a voice assistant helping someone apply for a benefit, book a medical appointment or report a financial problem. A generic notice that “AI may be used” does little when the system mishears a name, confuses a dialect or places a request in the wrong category. The user needs a record that says which details were captured, which next step was triggered and how to reach a human before the mistake becomes final.
The same principle applies to enterprise products. India Technology News has also reported that enterprise AI projects are running into privacy and data-sovereignty barriers. A correction receipt would not solve every governance problem, but it would expose where responsibility sits. It would show whether an output was merely suggested, automatically executed or approved by an employee. That distinction becomes essential when AI agents interact with customer records, underwriting systems, tax filings or internal approvals.
A useful receipt would contain five elements.
First, it should state the task in the user’s language: “You asked to update your address,” not an internal system code.
Second, it should identify the action and its status: proposed, completed, rejected or waiting for human review.
Third, it should display the key facts used. People do not need a technical model trace, but they should be able to spot a wrong date, amount, location or category.
Fourth, it should name the accountable organisation and provide a direct correction route. “Contact support” is not enough when the support team cannot see what the AI did.
Fifth, it should record the resolution. If a human corrects the result, the connected records and the system’s future handling of similar cases should be updated where appropriate.
This approach is good product design, not merely defensive compliance. It reduces repeat contacts, makes support work faster and gives developers evidence about recurring failures. It also helps companies distinguish between impressive demonstrations and dependable services. A multilingual system should not be judged only by the number of languages listed on a product page. It should be judged by whether users in those languages can detect and repair errors without starting over.
India’s AI industry has a strong opportunity to compete on trust. Cost, speed and model performance will remain important. Yet global buyers increasingly need proof that an AI product can be governed after deployment. A correction receipt turns an abstract promise of human oversight into an ordinary part of the customer experience.
The companies that make mistakes visible and reversible will not look weaker. They will look ready for the markets where AI is becoming infrastructure rather than a novelty.
