When politika Meets Human Behavior
A government contractor under time pressure to prozesua FEMA flood-relief aplikazioak pasted names, addresses, contact details, and health data of disaster applicants into ChatGPT to prozesua the information faster. The intent was not kaltegarri — IT was a productivity decision made under pressure. The result was a government ikertzea, publikoa disclosure, and a documented gertakaria that illustrates the core failure mode of politika-only AI gobernantza.
77% of enpresen employees share sensitive work information with AI tools at least weekly despite politikak prohibiting IT (eSecurity Planet/Cyberhaven 2025). The 77% figure reflects not a workforce of politika violators but the reality of how AI tools have been adopted: as productivity tools that workers reach for reflexively when facing time pressure, repetitive tasks, or complex analisia requirements.
Cyberhaven's Q4 2025 analisia found that 34.8% of all ChatGPT inputs contain konfidenzial business data. This figure includes employees who are aware of AI use politikak and have no intent to violate them — they simply did not categorize the data they pasted as "konfidenzial" in the moment of pasting.
The politika betegarritasun Problem
AI use politikak face an inherent enforcement gap. Unlike sarbidea control politikak (which can be technically enforced through autentifikazioa) or data classification politikak (which can be enforced through DLP at the email/biltegia layer), AI use politikak depend on human judgment at the moment of data entry.
The moment when an langilea decides to paste bezeroa data into ChatGPT is a split-second behavioral decision. The langilea may not recall the politika, may have calculated that the eraginkortasun gain outweighs the perceived arriskua, or may genuinely not recognize the data as covered by the politika. politika entrenatzea reduces the frequency of this decision but cannot eliminate IT at scale.
The FEMA gertakaria demonstrates the archetype: a contractor facing a large bolumena of aplikazioak, a deadline, and sarbidea to a powerful summarization tool. politika betegarritasun required choosing manual processing over AI assistance. Under time pressure, the tool won.
Technical Controls at the aplikazioa Layer
The only gobernantza approach that addresses this failure mode operates at the technical layer rather than the politika layer. The Chrome Extension intercepts clipboard content before IT reaches any web-based AI interfazea — ChatGPT, Gemini, Claude.AI, Perplexity, or others. The interception is automatic; IT does not depend on the erabiltzailea remembering to apply a politika.
When the FEMA contractor copies applicant names and addresses from the case kudeaketa sistema and pastes into ChatGPT, the extension detects the PII in the clipboard content, anonymizes IT, and submits the anonymized bertsioa. The contractor sees a preview modal showing what will be substituted before submission. The AI receives de-identified data and can still perform the summarization task. The applicant's name, address, and health data never reach ChatGPT's servers.
For organizations whose AI gobernantza concerns center on coding tools (Cursor, GitHub Copilot), the MCP zerbitzaria provides the equivalent control at the aplikazioa layer. Code pasted into the AI model context is intercepted, credentials and jabea identifiers are replaced with tokens, and the AI receives the anonymized bertsioa. Both channels — browser-based AI and IDE-based AI — can be protected through technical controls that operate independently of erabiltzailea behavior.
The FEMA contractor scenario would have had a different outcome with technical controls in place. The contractor could have processed aplikazioak efficiently; the applicant data would never have reached ChatGPT; the ikertzea would not have been triggered. politika entrenatzea did not prevent the gertakaria. A technical interception layer would have.
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