What companies should check first on AI services and personal data protection
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Both providers and enterprise adopters of AI systems must navigate the Act on the Protection of Personal Information (APPI) when the text, audio or images they handle include personal information. Compliance centers not on raw technological capabilities, but on whether an organization can articulate which data it handles, for what explicit purposes, and under whose responsibility.
The 2026 APPI amendment was enacted on July 10 and promulgated on July 17, 2026. The Personal Information Protection Commission's announcement states that, apart from some provisions, it will take effect on a date set by Cabinet Order within two years of promulgation. Legal teams should confirm the exact commencement date and implementing regulations for any specific rule before treating it as already in force.
Mapping the data flow
Prior to drafting policies, teams should map the entire data flow: entry points, local server storage, transfers to external AI APIs, logging durations, and model retraining workflows. Drafting a privacy policy without this factual foundation creates discrepancies with real operations. When integrating external generative AI APIs, user prompts leave company infrastructure, requiring scrutiny of vendor terms and data retention policies. Securing concrete architectural diagrams from engineering teams aids in distinguishing outsourcing from statutory third-party provision.
Explaining the purposes of use
A generic purpose such as "to provide the service" may leave readers unable to tell how their information will be used. Disclosures should describe specific use cases, such as summarizing user-submitted text, generating suggested responses, or analyzing usage logs. Because using personal information to train or refine models carries distinct legal risks, organizations must document whether data contributes to model training, whether it is treated as anonymised information under the applicable requirements, and how these choices are disclosed.
Distinguishing outsourcing, third-party provision, and cross-border transfers
Because AI products rely on third-party cloud platforms and model APIs, their classification under the APPI depends on the vendor's actual access to data, permitted uses, and contractual terms. If the arrangement involves a foreign third-party transfer under the APPI, check the applicable requirements, including any consent or information provision. Characterizing a relationship as outsourcing does not automatically satisfy cross-border transfer obligations. In B2B contexts, enterprise customers entering personal data may position the vendor as an entrusted processor, making re-entrustment provisions an additional compliance consideration.
Managing risks in AI outputs
When generative systems evaluate, classify, or profile individuals, downstream outputs can negatively impact affected persons. In hiring or credit assessment, the company should define human review before using an AI assessment to make a decision about a person. Furthermore, model hallucinations can generate false personal information, creating problems when the company stores or acts on inaccurate information.
Work beyond the privacy policy
Effective privacy governance for AI requires internal access controls, vendor contract reviews, and security incident readiness. Enterprise clients routinely issue detailed vendor questionnaires, and a startup's ability to explain data flow controls and deletion mechanisms can affect the customer's decision. LegalAgent views AI privacy compliance as a continuous discipline of service architecture and contractual practice, rather than isolated document drafting.