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Key Takeaways The standard 5-step AI privacy playbook is necessary and helps manage risk, but it has a major blind spot — it accepts that data will leave your environment at some point.
Client-side filtering — detecting and redacting sensitive data within the browser before anything transmits to any AI provider — is the sixth step that most founders miss.
If personally identifiable information never leaves the user’s device, no third party can misuse it, leak it or retain it improperly.
Meta fined €1.2 billion. Amazon hit for $812 million. Microsoft ordered to pay $20 million for retaining children’s data without parental consent. The headlines keep coming and the pattern is clear — regulators are no longer issuing warnings. They are issuing penalties.
For founders building AI-powered products and services, the privacy playbook has become essential reading. Most now follow the same five steps. But after building an EdTech platform for a UK university, I discovered these steps share one fundamental flaw — and fixing it changed everything.
The standard playbook
If you have spent any time researching AI and data protection, you have encountered these five steps in some form. They represent the consensus view on protecting client data when using AI tools.
Step 1: Classify your data
Before any data touches an AI system, know what you are working with. Public information, internal documents and sensitive client data require different handling. The founders who skip this step are the ones who end up in compliance nightmares later. A simple three-tier classification — public, internal and confidential — takes an afternoon to implement and prevents most accidental exposures. Start here before evaluating any AI tool.
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