Meta is preparing to automate a significant portion of its internal product risk evaluations using artificial intelligence.
According to internal documents reported by NPR, the company plans to delegate up to 90% of product-related privacy and risk assessments to AI systems—a role traditionally fulfilled by legal and privacy experts.
This shift aims to accelerate the rollout of updates across Meta’s major platforms, including Facebook, Instagram, and WhatsApp.
However, the move comes with potential regulatory and ethical implications, especially given Meta’s longstanding agreement with the U.S. Federal Trade Commission (FTC) requiring rigorous privacy oversight.
Instant Risk Decisions via Automation
Under the proposed system, Meta’s product teams will begin the evaluation process by completing a standardized questionnaire outlining the nature and scope of proposed changes.
The AI will then analyze the responses and issue an “instant decision,” flagging potential privacy or safety risks and suggesting compliance measures.
According to Meta, this new process is designed to streamline product development cycles without weakening internal compliance obligations.
The company claims the AI-based approach adds consistency and predictability to low-risk decisions, while still reserving complex or novel issues for human experts.
Regulatory Context
The proposed shift takes place within the framework of Meta’s 2012 consent agreement with the FTC, which mandates systematic privacy reviews prior to feature launches.
The automation of this process raises questions about whether AI can adequately identify and evaluate risks that may not be easily quantifiable or that require nuanced judgment.
Meta maintains that it remains committed to regulatory compliance and user safety, citing more than $8 billion in privacy-related investments.
In a statement, a company spokesperson said the new system supports a “maturing privacy program” and emphasized that human oversight will continue for cases that fall outside the scope of automated evaluation.
Speed Versus Safety
Despite the efficiency benefits, some internal stakeholders have expressed caution. A former Meta executive told NPR that the increased reliance on automation could result in a higher risk of negative externalities.
The concern is that subtle or emerging risks might slip through undetected when AI replaces human judgment in the initial evaluation stages.
Critics also note that AI systems can struggle with context and ambiguity—qualities often essential for assessing potential downstream effects of a new feature, particularly those involving user safety or platform integrity.
Beyond Privacy to Content and Safety
Meta’s AI system is designed to evaluate not only privacy-related issues but also risks associated with content integrity and user safety. This includes monitoring for potential implications around misinformation, exposure to harmful content, and the protection of minors.
The company asserts that its approach will improve governance by standardizing common evaluations while freeing up human experts to focus on more complex or sensitive issues.
AI as a Core Component of Governance
The move to automate product governance processes reflects a broader organizational shift at Meta. As part of its AI-driven operational strategy, the company is embedding machine learning tools into workflows across teams in an effort to improve scalability and efficiency.
Meta positions this hybrid model—AI triaging routine cases, with humans handling edge cases—as a way to evolve with increasing regulatory demands and user expectations. Still, the broader impact of such a system will likely depend on how carefully its limitations are managed.
Meta’s use of AI to govern internal risk management processes could signal a new trend among major tech companies seeking to reduce operational bottlenecks. Yet, with billions of users affected by decisions made within these systems, the stakes remain high.
