Is this a consulting service?

No, this is a free, interactive software tool that calculates your potential liability under the DPDP Act 2023 in 30 seconds. It provides an instant risk score and automated action plan.

What are common DPDP violations in DPDP Audit for AI Model Training on User Data?

Common violations include: Training AI models on internal customer databases (CRM, support tickets) without obtaining specific consent for 'AI model training' as a purpose., Using publicly available data scraped from social media or websites for AI training without checking for personal data and ensuring a lawful basis., Lack of robust anonymization or pseudonymization techniques for personal data before it's used to train Generative AI or Machine Learning models..

The DPDP Audit Tool

Compliance for DPDP Audit for AI Model Training on User Data

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DPDP Audit for AI Model Training on User Data
Liability Check

Training your AI models on customer data, internal logs, or web-scraped information without explicit, purpose-specific consent is a direct violation of the DPDP Act. This exposes your business to massive penalties, potentially up to ₹250 Crore, for illegal data processing.

Why DPDP Audit for AI Model Training on User Data is at Risk

The DPDP Act doesn't just apply to how you collect data; it governs **every stage of processing**, including using it to train your cutting-edge AI. If your AI models, from predictive analytics at a major e-commerce player to chatbots deployed by a fintech startup in Bengaluru's tech parks, are fed **personal data** (names, emails, demographics) or **sensitive personal data** (biometrics, health records), you absolutely need a **valid legal basis**. Without it, you're not just building a smart AI, you're building a compliance time bomb. The Data Protection Board will demand proof of **informed consent** for each specific purpose, and simply having data in your database doesn't give you a free pass for AI training.

Common Violations

1.Training AI models on internal customer databases (CRM, support tickets) without obtaining specific consent for 'AI model training' as a purpose.
2.Using publicly available data scraped from social media or websites for AI training without checking for personal data and ensuring a lawful basis.
3.Lack of robust anonymization or pseudonymization techniques for personal data before it's used to train Generative AI or Machine Learning models.

The Immediate Fix

First, conduct an immediate **data inventory and audit** of all datasets currently used or planned for AI training. Identify all instances of **personal data**. Next, implement a process to obtain **explicit, purpose-specific consent** for AI training for any new data collection, and retroactively assess if existing data can be legally used, or requires full anonymization.