Ethical AI for Leaders in Thailand

All training modules incorporate PDPA compliance frameworks, covering consent management, data minimisation, and breach notification obligations. With THB 21.5 million in fines already levied in 2025 — including against data processors — we ensure your team understands both controller and processor obligations when deploying AI systems that handle personal data.

We cover the full regulatory landscape: PDPA (fully enforced, THB 21.5M in 2025 fines), the draft AI Law with risk-based classifications, BOT AI Risk Management Guidelines (September 2025), the Emergency Decree on Technology Crimes (April 2025), NSTDA AI Ethics Guidelines, and MDES/ETDA Generative AI governance standards. Our framework maps your AI systems against each obligation.

The 2025 Draft Principles of Thailand's AI Law introduces 'Prohibited-risk' (social scoring, subliminal manipulation) and 'High-risk' categories with strict governance duties. Our masterclass builds governance structures that classify your AI applications against these risk tiers and implement the transparency, accountability, and oversight controls the law will require upon formalisation in 2026.

Yes. BOI investment promotion offers up to 13 years CIT exemption for AI and digital technology activities. The QRTC provides 30-50% refundable tax credits for R&D and advanced skills development. SMEs can also claim a 200% tax deduction on qualifying digital expenses through December 2027.

We deliver using a hybrid English-Thai approach with high-energy, interactive workshops that match Thai learner preferences. Content respects hierarchical management structures and the kreng jai norm of maintaining group harmony, using consensus-building exercises rather than confrontational case studies.

The 2025 Draft Principles of Thailand's AI Law introduces risk-based classifications including 'Prohibited-risk' and 'High-risk' AI categories. Our training builds governance frameworks that anticipate these requirements, so your organisation is prepared when the law is formalized in 2026.

AI ethics decisions directly affect your brand reputation, regulatory compliance, and stakeholder trust. Leaders who understand fairness, bias, and transparency can make AI decisions they can confidently defend to customers, regulators, and the public. This programme ensures your leadership team is equipped to guide responsible AI adoption that protects your organisation's reputation and values.

Your leaders will receive ethical decision-making frameworks, bias assessment checklists, stakeholder communication templates, and guidelines for establishing an AI ethics review process. These are practical, ready-to-use tools that help your team evaluate AI projects through an ethical lens and make responsible decisions quickly, not abstract philosophical discussions.

Organisations that deploy AI without ethical guardrails risk bias incidents, privacy violations, and public trust erosion that can take years to recover from. This programme equips your leadership team with frameworks to anticipate and prevent these issues before they arise. You will learn to establish AI ethics policies, create accountability structures, and communicate responsibly about your AI practices. Companies with strong ethical AI governance consistently outperform their peers in customer trust, employee confidence, and regulatory readiness.

Your leadership team receives a comprehensive ethical AI governance package that includes a responsible AI policy template aligned with international standards and regional regulatory expectations, a bias detection and mitigation checklist applicable to common AI applications, a transparency and explainability guide for communicating AI-assisted decisions to customers and employees, an ethical review board charter for establishing internal oversight, and a stakeholder communication framework for publicly reporting on your AI ethics commitments. Each document includes implementation guidance and real-world examples from organisations across Southeast Asia that have successfully operationalised ethical AI practices. These are not theoretical frameworks but working documents refined through practical deployment across multiple industries and regulatory environments.