Indonesia - Ethical Guidelines for AI
Concept Draft of Ethical Guidelines for AI
Konsep Pedoman Etika Kecerdasan Artifisial (Concept Draft of Ethical Guidelines for AI)
Indonesia
RAI-ID-NA-KPEKAXX-2025Indonesia - Ethical Guidelines for AI is Draft in Indonesia as of 8 Sep 2026, according to portal.komdigi.go.id.
GuidelineGovernance and OversightRisk ManagementConformity Assessment and RegistrationThe 2025 Concept Draft of Ethical Guidelines for AI sets out a risk-based framework for AI developers, issued by Indonesia's Ministry of Communication and Digital (Komdigi). It guides high-risk classification, human oversight, and transparency measures, and remains a draft following public consultation on 8 August 2025.
Summary
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The Konsep Pedoman Etika Kecerdasan Artifisial is a concept draft published by the Ministry of Communication and Digital (Komdigi) in August 2025 for public consultation. It accompanies a national AI White Paper (‘Buku Putih Peta Jalan Kecerdasan Artifisial Nasional’) and is presented as a values-driven, risk-based framework intended to guide the development, deployment, and governance of AI across public and private sectors in Indonesia. The draft builds on the foundation set by Ministerial Circular/SE No.9 of 2023 on AI ethics and signals the Ministry’s intention to move from guidance toward a binding Presidential regulation. The public consultation opened on 8 August 2025 and was extended to 29 August 2025 to gather broader stakeholder input. Extension notice.
Definitions
The draft defines key concepts in alignment with existing Indonesian instruments: ‘Artificial Intelligence / Kecerdasan Artifisial’ (programming capable of data processing, ML, NLP, neural networks), ‘Penyelenggara Sistem Elektronik (PSE)’, ‘Pelaku Usaha’ (AI programming actors), ‘High-Risk AI’ (applications with elevated potential for harm), and related technical terms such as ‘model provenance’, ‘human-in-the-loop’, and ‘adversarial robustness’. These definitions are intended to interoperate with the statutory definitions in Law No. 27/2022 on Personal Data Protection and existing electronic systems law and guidance. The draft aims to align legal and ethical terminology to reduce ambiguity across implementing agencies.
Governance and Institutional Framework
The draft places primary stewardship with the Ministry of Communication and Digital but envisages a multi-agency governance architecture involving sectoral regulators (e.g., OJK for finance, Ministry of Health for healthcare), national cybersecurity authorities (e.g., BSSN), and consumer protection bodies. It proposes a national coordination mechanism to: (1) classify high-risk systems; (2) maintain registries or notification schemes for significant AI deployment; (3) coordinate conformity assessment and market surveillance; and (4) harmonize sectoral rules to avoid regulatory fragmentation. The model is consultative and iterative — Komdigi’s consultation document and the White Paper were produced by a broad taskforce of government, academics, industry and civil society representatives to ensure cross-sectoral buy-in. Komdigi announcement.
Key Focus Areas
The draft’s focus areas include: (a) Governance & oversight (clear institutional roles, registries and inter-agency coordination); (b) Risk management (mandatory risk assessments and classification of high-risk use-cases); (c) Safety testing & evaluation (pre-deployment testing, adversarial resilience and continuous monitoring); (d) Transparency & disclosure (model cards, user notices, provenance data and AI-generated content labelling); (e) Data protection & privacy (privacy-by-design, DPIA alignment with Law No.27/2022); (f) Fundamental rights (anti-discrimination, due process protections for automated decisions); (g) Cybersecurity & model security (requirements for integrity, access controls and incident reporting); (h) Conformity assessment & registration (third-party audit pathways and potential mandatory registration for certain categories); (i) Accountability & documentation (retention of logs, audit trails and explainability records); and (j) Liability, redress & enforcement (administrative sanctions and measures to ensure remediation). Many of these areas explicitly reference or harmonize with existing instruments such as SE No.9/2023 and the PDP Law. SE No.9/2023.
Implementation Framework
Implementation in the draft is phased and risk-based. Lower-risk AI retains voluntary compliance plus baseline transparency obligations; high-risk AI triggers mandatory pre-deployment risk assessments, documentation, registration/notification, third-party conformity or testing (as defined by implementing rules), and enhanced human oversight requirements. The draft anticipates sectoral implementing rules to operationalize thresholds, technical standards, and enforcement mechanisms. It also recommends capacity building for regulators, accredited testing laboratories, and guidance documents for SMEs to reduce compliance burden while protecting public interests.
Monitoring and Evaluation
The draft outlines monitoring mechanisms including market surveillance, periodic reporting by PSEs, incident notification requirements, and performance indicators tied to safety, fairness and privacy outcomes. It envisions a national AI registry or dashboard to track high-risk systems, a complaint-handling channel for affected persons, and regular public reporting by Komdigi and partner agencies on compliance trends. Independent evaluation — including audits and public transparency reporting — is recommended to measure policy effectiveness and to feed iterative updates to the framework.
Penalties, Liability, and Appeals
As a concept draft, detailed sanctions are deferred to implementing regulations, but it enumerates possible measures: administrative fines, remedial orders (model rollback, algorithmic adjustments), suspension or blocking of services, revocation of PSE registration, and referral for criminal investigation where statutory offences are implicated (e.g., violations of PDP Law or ITE provisions). The draft also describes redress pathways for individuals including complaint mechanisms and requirements for transparent appeals procedures. Enforcement is envisaged to be proportional, risk-based and accompanied by guidance to support compliance.
Relationship to Other Instruments
The draft explicitly connects to: the Ministerial Circular/SE No.9/2023 on AI ethics; Law No.27 of 2022 on Personal Data Protection (PDP Law); existing Electronic Information and Transactions (ITE) law and implementing PSE rules; and sectoral laws (health, finance) where additional safeguards apply. The draft is positioned as a normative bridge that informs future binding instruments (including a proposed Presidential Regulation) while respecting existing statutory obligations under the PDP Law and other sectoral regimes. SE No.9/2023; Law No.27/2022 (PDP Law).
International Alignment
The Concept Draft emphasizes alignment with international best practices and soft-law instruments (e.g., OECD AI Principles, EU AI Act concepts), while calibrating to Indonesia’s legal context. It encourages interoperability (data protection, cross-border cooperation on AI safety and incident response) and proposes participation in multilateral fora to harmonize standards and avoid fragmentation, particularly for cross-border AI services and global platforms operating in Indonesia. This international orientation is intended to facilitate trade, investment, and cooperative enforcement mechanisms.
Implementation Timeline
| Milestone | Date | Notes |
|---|---|---|
| Public consultation opened | 2025-08-08 | Komdigi announcement |
| Consultation extended (deadline) | 2025-08-29 | Extension notice |
| Submission of Perpres initiative | 2025-09-05 | ANTARA report |
| Expected harmonization & drafting | Q3–Q4 2025 (target) | Subject to inter-agency process and stakeholder input |
Sources and References
Requirements for a company
What an organisation has to do under Indonesia - Ethical Guidelines for AI, at a glance. Not legal advice — the table below gives the provision and deadline for each item.
Not yet in force (Draft). These requirements apply once the instrument takes effect and may change before then.
Must do
0Nothing in this category.
Must not do
0Nothing in this category.
Should do
8- Conduct pre-deployment risk assessments and risk classifications for high-risk AI system use cases.Providers and deployers of high-risk AI systems
- Label AI-generated content and publish model cards and user notices for transparency.Electronic system operators deploying AI systems
- Perform pre-deployment testing and continuous safety evaluations to ensure adversarial resilience.AI developers and electronic system operators in Indonesia
- Implement privacy-by-design and conduct data protection impact assessments aligned with personal data protection laws.Electronic system operators processing personal data using AI
- Retain system logs, audit trails, and explainability records for oversight and accountability.Providers and operators of AI systems
- Report cybersecurity and safety incidents promptly to national authorities.Electronic system operators deploying AI
- +2 more in the table below
Should not do
0Nothing in this category.
Who must do what
The obligations under Indonesia - Ethical Guidelines for AI, most serious first. Not legal advice — verify against the official text before relying on it.
| # | Who | Requirement | By when | Where | Severity |
|---|---|---|---|---|---|
| 1 | Providers and deployers of high-risk AI systems | Conduct pre-deployment risk assessments and risk classifications for high-risk AI system use cases. “mandatory risk assessments and classification of high-risk use-cases” | Before deployment | Key Focus Areas | Recommended |
| 2 | Electronic system operators deploying AI systems | Label AI-generated content and publish model cards and user notices for transparency. “model cards, user notices, provenance data and AI-generated content labelling” | — | Key Focus Areas | Recommended |
| 3 | AI developers and electronic system operators in Indonesia | Perform pre-deployment testing and continuous safety evaluations to ensure adversarial resilience. “pre-deployment testing, adversarial resilience and continuous monitoring” | Before deployment | Key Focus Areas | Recommended |
| 4 | Electronic system operators processing personal data using AI | Implement privacy-by-design and conduct data protection impact assessments aligned with personal data protection laws. “privacy-by-design, DPIA alignment with Law No.27/2022” | — | Key Focus Areas | Recommended |
| 5 | Providers and operators of AI systems | Retain system logs, audit trails, and explainability records for oversight and accountability. “retention of logs, audit trails and explainability records” | — | Key Focus Areas | Recommended |
| 6 | Electronic system operators deploying AI | Report cybersecurity and safety incidents promptly to national authorities. “requirements for integrity, access controls and incident reporting” | — | Key Focus Areas | Recommended |
| 7 | Deployers of high-risk AI systems | Maintain human oversight mechanisms, including human-in-the-loop controls, for high-risk AI systems. “enhanced human oversight requirements” | — | Implementation Framework | Recommended |
| 8 | Providers and deployers of high-risk AI systems | Register high-risk AI systems within national registries or notification schemes before deployment. “maintain registries or notification schemes for significant AI deployment” | Before deployment | Governance and Institutional Framework | Recommended |
Related Regulations
More AI regulation in Indonesia
© Regulations.AI · updated on 20 Sep 2026 · reviewed against official sources on 8 Sep 2026 using Gemini 3.6 Flash