AI Ethics Principles
This document establishes the 2025 AI Ethics Principles and framework issued by the Saudi Data and Artificial Intelligence Authority (SDAIA). It sets out guiding principles for artificial intelligence including fairness, privacy and security, humanity, social and environmental benefits, reliability and safety, transparency and explainability, and accountability. Furthermore, it outlines an AI System Lifecycle approach spanning preparation, planning, building, and deployment, alongside checklists and tools for compliance in the Kingdom of Saudi Arabia.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This document is for public and private sector entities, developers, deployers, and stakeholders involved in designing, developing, or using AI systems within the Kingdom of Saudi Arabia.
What the document contains
The document covers comprehensive ethical principles, risk management categories, a structured four-stage AI system lifecycle with associated controls for each phase, governance roles and responsibilities within adopting entities and nationally, and tools and checklists for compliance.
Not stated
- The framework establishes seven core AI ethics principles: Fairness, Privacy & Security, Humanity, Social & Environmental Benefits, Reliability & Safety, Transparency & Explainability, and Accountability & Responsibility.
- AI systems and associated risks are classified into four tiers: Little or no risk, Limited risk, High risk, and Unacceptable risk.
- The AI System Lifecycle is divided into four main phases: Prepare Input Data, Plan and Design, Build and Validate, and Deploy and Monitor.
- Adopting entities are required to designate specific roles such as a Chief Compliance Officer and a Responsible AI Officer to oversee AI ethics compliance.
- The framework provides annexures containing AI ethics tools, mappings, and detailed checklists for each phase of the AI system lifecycle.
· Introduction · Definitions · Scope · AI Ethics Principles and Controls · Roles and Responsibilities · Appendices
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
The accountability and responsibility principle holds designers, vendors, procurers, developers, owners and assessors of AI systems and the technology itself ethically responsible and liable for the decisions and actions
Principle 7 – Accountability & Responsibility
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
The fairness principle requires taking necessary actions to eliminate bias, discrimination or stigmatization of individuals, communities, or groups in the design, data, development, deployment and use of AI systems.
Principle 1 – Fairness
screening score · 2026-10-23
Human Dignity
4/5Respect for the inherent worth of persons
The humanity principle highlights that AI systems should be built using an ethical methodology to be just and ethically permissible, based on intrinsic and fundamental human rights and cultural values
Principle 3 – Humanity
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
The privacy and security principle represents overarching values that require AI systems; throughout the AI System Lifecycle; to be built in a safe way that respects the privacy of the data collected
Principle 2 – Privacy & Security
screening score · 2026-10-23
Enforcement
4/5Consequences and compliance mechanisms with real force
Measure compliance of Adopting Entities on a regular basis based on the defined compliance mechanism directly or through sector regulators
SDAIA National Level Roles and Responsibilities
screening score · 2026-10-23