PDPA-Aligned Agentic AI.

Short answer: the Malaysian Personal Data Protection Act 2010 (PDPA) was not written with agentic AI in mind, but its seven principles map cleanly onto specific architectural choices you can make at deployment time. Below is the checklist we run with every Malaysian enterprise client before an agent goes live.

Why a checklist, not a policy document

PDPA compliance is usually presented as a privacy-notice and consent exercise. For agentic AI that's necessary but nowhere near sufficient: the agent takes actions, retrieves records, and writes to downstream systems on behalf of a named identity. Each of those steps is a separate compliance surface. The checklist below operationalises the seven PDPA principles into concrete engineering decisions.

The 12-point checklist

1. Named identity propagation

Every agent action must carry the identity of a real human or service principal. No anonymous agent calls into systems holding personal data. This satisfies the General Principle requirement that processing be lawful.

2. Bounded data-subject scope

Define upfront which categories of data subjects the agent may touch (customers, employees, vendors, third-party referees). Configure tools to refuse calls outside that scope. Satisfies the Notice and Choice Principle.

3. Read/write separation

Read endpoints and write endpoints carry different audit rules. Write actions always require an explicit authorising decision logged with reason code. Failing this turns the agent into an unaccountable conduit.

4. Per-action provenance trail

Every output the agent produces must cite the source records it relied on, with timestamps. This is what makes the Access Principleworkable: when a data subject requests a copy of their data, you can show exactly what the agent saw and when.

5. Local inference, no third-party model training

Regulated payloads (personal data, financial records, health records) must not transit to third-party model training pipelines. Either run sovereign inference, or contract explicit exclusion. Satisfies Disclosureand Security Principles.

6. Retention boundaries by data category

Agent memory is not free storage. Set retention by data category — agent conversation logs typically 90 days, decision provenance 7 years (matching tax retention), summarised analytics indefinitely. Satisfies the Retention Principle.

7. Data integrity confirmation step

Before the agent writes to a system of record, it must confirm the source data is current. A stale read → fresh write loop creates integrity drift that the regulator will find first. Satisfies the Data Integrity Principle.

8. Right-to-correct path

Build a human-handoff route specifically for data-subject correction requests. AI must not be the only channel for "please fix my record". Failing this fails the Access Principle on its second leg.

9. Cross-border consent gate

If any agent dependency processes data outside Malaysia, that path requires explicit, recorded consent from the data subject (or one of the limited statutory exceptions). Configure tool-level checks; never rely on a privacy notice paragraph to cover this.

10. Sensitive-data detection

Agents see free-form text. Build PII/sensitive-personal-data classifiers into the agent's reasoning layer so payloads containing IC numbers, health data, or political affiliation are flagged before any tool call.

11. Documented data-flow diagram

For each agent persona, maintain a current data-flow diagram showing every system it reads from, every system it writes to, and every external dependency. Update on every deployment. This is the document a regulator will ask for first.

12. Per-action redaction policy

Agent transcripts and audit logs themselves contain personal data. Define redaction rules so transcripts can be shared with internal audit without re-exposing PII to staff who shouldn't see it.

How AITG builds this in

All twelve checks are baked into how we deploy the Teragrid Agent. The Platform's governance layer (L5) is specifically designed for PDPA-style obligations. If you're reading this because your CIO or DPO asked for an agentic AI compliance posture before a board review, get in touch — we'll walk through the checklist against your current deployment in 30 minutes.

This article is provided for informational purposes only and does not constitute legal advice. Consult Malaysian privacy counsel for specific compliance posture.