School-district staff might paste student IEP free text into unsanctioned AI tools. Which preventive data control best fits?

Student IEP free text is highly sensitive education data. Staff pasting it into unsanctioned public AI tools risks unauthorized disclosure, vendor secondary use, and loss of district custody. Preventive DLP that blocks IEP free text from unsanctioned AI destinations enforces data boundaries at the technical control layer rather than relying solely on after-the-fact discipline. Using DLP controls that log students’ free-text IEPs pasted to unsanctioned AI tools is detective, not preventive; it records the paste after disclosure rather than blocking it, so it fails to prevent the exfiltration described in the scenario. Using DLP controls that block students’ IEP file uploads to unsanctioned AI tools targets the wrong vector; it may stop attached files but does not stop copying IEP free text and pasting it into unsanctioned AI tools, so it misses the disclosure described in the scenario. Using DLP controls that block students’ free-text IEPs pasted to sanctioned AI tools enforces the wrong boundary; it restricts the approved district workspace while leaving pastes to unsanctioned AI tools unblocked, so it does not prevent the disclosure described in the scenario. Exam caveat: AAISM preventive data controls for civic AI include DLP blocking of free-text pastes to unsanctioned AI destinations for regulated personal data, not blocking file uploads alone. Operational check: classify IEP content, deploy DLP rules that detect and block outbound IEP text to unapproved AI endpoints, provide a sanctioned district AI workspace with logging, and train staff on approved drafting paths.