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PDPA & AIPDPA-Aware AI:
Data Minimization & Consent Flows
Build AI that stays useful without exposing more personal data than necessary. We help teams design data-minimizing models and consent flows that align with Thailand’s Personal Data Protection Act BE 2562 (2019) and prepare for intensified enforcement in 2025 — Book a Discovery Call to map your compliance gaps and a practical roadmap.
Book a Discovery Call.
What We Deliver
We produce a PDPA-aware governance checklist, consent-flow designs, and practical technical controls focused on limiting data collection to what’s strictly necessary. Deliverables include documented purpose limitation, consent templates, and an implementation plan for Privacy by Design so controls are applied from development onward. Request a Proposal if you need a scoped package or fixed-fee engagement.
How It Works
We start with a focused risk assessment of your AI use cases, identifying where personal data is processed and whether a Data Protection Impact Assessment (DPIA) is required for high-risk activities. We then map required legal bases — such as Consent, Contract, or Legitimate Interest — into operational consent flows, and recommend tooling (for example, CMPs mentioned in the research) and techniques to reduce excess collection. Implementation support covers developer controls, documentation for transparency, and handover templates for ongoing monitoring.
Why It Matters Now
Thailand’s PDPA (BE 2562, 2019) is the governing law for personal data; regulators and the Personal Data Protection Committee (PDPC) are increasing enforcement activity with particular scrutiny expected in 2025. That shift means gaps that were tolerated before will draw attention; starting compliance work now avoids disruption to AI projects and helps preserve user trust.
Proof & Results
Work products align with the research-backed elements identified for Thailand: legal-basis mapping, data minimization, transparent consent handling, and DPIA readiness. Engagements produce auditable documentation and an implementation plan you can act on immediately, reducing the likelihood of enforcement action as regulator attention grows in 2025. Book a Discovery Call to review a sample checklist and see how this applies to your AI pipeline.
Pricing & engagement
We offer modular engagements: a short advisory workshop to map risk and consent needs, a hands-on implementation sprint for controls and CMP integration, and a longer retainer for monitoring and remediation. Tell us your preferred scope in a Discovery Call and we’ll propose fixed-fee options or hourly estimates.
Compliance & risk —
what it means for you
Compliance requires clear legal bases for processing, demonstrable data accuracy, purpose limitation, and explicit consent where needed. We translate those obligations into operational controls: consent capture and revocation workflows, purpose-bound data stores, and retention limits. For high-risk AI uses we prepare DPIAs — a DPIA is a structured assessment that documents risks and mitigation for significant personal-data processing — and provide remediation steps to reduce regulatory exposure.
Technical implementation highlights
We embed Privacy by Design into the development lifecycle so data protections are considered from day one. That includes minimizing inputs to models, pseudonymization where feasible, and clear documentation of processing activities for transparency. Where relevant, we recommend monitoring and tooling approaches referenced in the research to reduce excess collection and track consent status across systems.
Book a Discovery Call
to get a scoped proposal for your business.
Related hub orientation
This page serves as the central PDPA-aware AI governance overview; related sub-pages cover the details of core principles, consent workflows, technical controls, and enforcement monitoring so you can dive deeper into each area.
If your AI processes personal data in Thailand, the time to act is now. Book a Discovery Call to get a tailored PDPA-AI gap analysis, or Request a Proposal for an implementation-ready plan.
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