AI Regulation and Global Governance Training Course

Course Overview

Artificial Intelligence (AI) Regulation and Global Governance have become strategic priorities for governments, regulatory authorities, international organizations, technology companies, financial institutions, healthcare providers, educational institutions, and development partners seeking to harness the transformative potential of artificial intelligence while ensuring ethical, transparent, secure, and accountable deployment. The rapid advancement of Artificial Intelligence (AI), AI Regulation, Global Governance, Responsible AI, AI Ethics, AI Policy, AI Risk Management, Machine Learning, Generative AI, Digital Governance, Algorithmic Accountability, AI Compliance, Data Governance, Cybersecurity, Privacy Protection, AI Safety, Digital Rights, AI Standards, Explainable AI (XAI), AI Auditing, AI Impact Assessment, Regulatory Technology (RegTech), Digital Transformation, International AI Governance, and Sustainable Development Goals (SDGs) is reshaping economies, public administration, healthcare, education, finance, justice, and international cooperation. This comprehensive training course equips participants with practical knowledge and advanced competencies to develop, implement, and oversee AI governance frameworks that foster innovation while safeguarding human rights, security, and public trust.

The course provides participants with a comprehensive understanding of international AI governance frameworks, national AI strategies, regulatory models, ethical principles, legal compliance, institutional governance, AI lifecycle management, algorithmic transparency, risk assessment, AI auditing, and accountability mechanisms. Participants will learn how to formulate AI policies, establish governance structures, conduct AI impact assessments, manage regulatory compliance, strengthen institutional oversight, develop responsible AI programmes, and promote trustworthy AI systems aligned with international standards. The programme incorporates internationally recognized principles and frameworks including the UNESCO Recommendation on the Ethics of Artificial Intelligence, OECD AI Principles, ISO/IEC AI Standards, NIST AI Risk Management Framework, European Union AI Act, G7 Hiroshima AI Process, African Union Digital Transformation Strategy, and the United Nations Sustainable Development Goals (SDGs).

Special emphasis is placed on emerging governance challenges including generative AI, foundation models, autonomous systems, algorithmic bias, fairness, explainability, transparency, privacy-enhancing technologies, AI cybersecurity, digital identity, cloud-based AI platforms, blockchain-enabled AI governance, AI procurement, AI in public services, AI for healthcare, financial technologies, smart cities, environmental sustainability, digital inclusion, cross-border AI regulation, international cooperation, regulatory sandboxes, AI assurance, and innovation governance. Participants will also explore legal, ethical, social, economic, and geopolitical implications of AI deployment while strengthening institutional capacity for responsible innovation and effective regulatory oversight.

Through practical policy development workshops, AI governance simulations, regulatory compliance exercises, risk assessment laboratories, collaborative group work, web-based tutorials, and relevant international case studies, participants will develop competencies required to govern AI systems responsibly across public and private sectors. Upon successful completion, participants will be equipped to strengthen AI governance frameworks, improve regulatory compliance, manage AI risks, protect fundamental rights, support ethical innovation, enhance institutional resilience, promote international cooperation, and contribute to secure, transparent, and human-centred artificial intelligence ecosystems.

Course Objectives

1.     Understand the principles and frameworks of AI regulation and global governance.

2.     Develop effective AI governance strategies aligned with international standards.

3.     Strengthen institutional capacity to regulate and oversee AI systems responsibly.

4.     Apply AI ethics, transparency, fairness, and accountability principles in organizational governance.

5.     Conduct AI risk assessments, impact assessments, and regulatory compliance reviews.

6.     Strengthen cybersecurity, privacy, and data governance for AI-enabled systems.

7.     Promote responsible innovation through regulatory sandboxes and AI assurance frameworks.

8.     Integrate AI governance into public policy, digital transformation, and organizational strategy.

9.     Strengthen monitoring, evaluation, and performance management of AI governance programmes.

10.  Build sustainable, secure, and trustworthy AI ecosystems that support inclusive economic and social development.

Organizational Benefits

1.     Improved governance and oversight of artificial intelligence systems.

2.     Enhanced compliance with international AI regulations, ethical principles, and standards.

3.     Reduced legal, operational, cybersecurity, and reputational risks associated with AI deployment.

4.     Strengthened public trust through transparent and accountable AI governance.

5.     Improved decision-making using ethical, explainable, and reliable AI systems.

6.     Enhanced institutional capacity for responsible AI innovation and digital transformation.

7.     Better protection of privacy, human rights, and sensitive organizational data.

8.     Increased collaboration among regulators, policymakers, academia, industry, and civil society.

9.     Improved organizational resilience through effective AI risk management and governance.

10.  Sustainable AI adoption supporting innovation, competitiveness, and long-term institutional growth.

Target Participants

This course is designed for policymakers, legislators, government officials, regulators, central bank officials, data protection authorities, ICT managers, chief information officers, chief technology officers, AI governance officers, compliance managers, legal advisors, judges, prosecutors, cybersecurity professionals, data governance specialists, digital transformation managers, risk managers, internal auditors, ethics committee members, researchers, academics, consultants, innovation managers, project managers, healthcare administrators, financial sector professionals, telecommunications regulators, development partners, and professionals responsible for AI governance, digital policy, regulatory compliance, and organizational transformation.

Course Outline

Module 1: Introduction to AI Regulation and Global Governance

·       Fundamentals of artificial intelligence

·       Evolution of AI governance

·       Global AI policy landscape

·       AI opportunities and risks

·       Responsible AI principles

·       International governance trends

Case Study: Developing a national framework for AI governance and regulation.

Module 2: International AI Governance Frameworks

·       UNESCO AI Recommendation

·       OECD AI Principles

·       NIST AI Risk Management Framework

·       ISO/IEC AI standards

·       Regional AI governance initiatives

·       International cooperation mechanisms

Case Study: Aligning organizational AI governance with international standards.

Module 3: AI Policy Development and Regulatory Frameworks

·       National AI strategies

·       Legislative and regulatory models

·       Institutional governance

·       Regulatory authorities

·       Policy implementation

·       Regulatory harmonization

Case Study: Drafting a national AI regulatory policy for emerging technologies.

Module 4: AI Ethics, Human Rights and Responsible Innovation

·       AI ethics principles

·       Human rights protection

·       Algorithmic fairness

·       Bias mitigation

·       Explainable AI (XAI)

·       Responsible innovation

Case Study: Addressing algorithmic bias in AI-assisted public service delivery.

Module 5: AI Risk Management and Impact Assessment

·       AI risk identification

·       AI impact assessments

·       Enterprise AI governance

·       Operational risk management

·       Compliance monitoring

·       Risk mitigation strategies

Case Study: Conducting an AI impact assessment before deploying an automated decision-making system.

Module 6: Data Governance, Privacy and Cybersecurity

·       Data governance frameworks

·       Privacy protection

·       AI cybersecurity

·       Digital identity management

·       Information security

·       Cross-border data governance

Case Study: Securing sensitive data within an AI-powered government platform.

Module 7: AI Assurance, Auditing and Compliance

·       AI auditing methodologies

·       Regulatory compliance

·       Internal controls

·       AI assurance frameworks

·       Transparency reporting

·       Continuous compliance monitoring

Case Study: Performing an independent audit of an AI-enabled financial service.

Module 8: Sectoral Applications of AI Governance

·       AI in healthcare

·       AI in financial services

·       AI in education

·       AI in public administration

·       AI in justice systems

·       AI in smart cities

Case Study: Establishing governance controls for AI-assisted healthcare diagnostics.

Module 9: AI Innovation, Procurement and Regulatory Sandboxes

·       AI procurement governance

·       Innovation management

·       Regulatory sandboxes

·       Public-private partnerships

·       AI investment strategies

·       Technology adoption

Case Study: Launching a regulatory sandbox for responsible AI innovation.

Module 10: Monitoring, Evaluation and Performance Management

·       AI governance indicators

·       Results-based management

·       Performance monitoring

·       Compliance reporting

·       Governance reviews

·       Continuous improvement

Case Study: Measuring the effectiveness of an organizational AI governance programme.

Module 11: Cross-Border AI Governance and International Cooperation

·       International regulatory cooperation

·       Cross-border AI governance

·       Digital trade implications

·       Global standards harmonization

·       International partnerships

·       Capacity building

Case Study: Coordinating multinational AI governance across regional economic communities.

Module 12: Emerging Trends in AI Regulation and Global Governance

·       Generative AI governance

·       Foundation model oversight

·       Autonomous systems regulation

·       AI and climate governance

·       Future AI policy developments

·       Strategic AI governance roadmaps

Case Study: Developing a long-term national roadmap for trustworthy and globally aligned AI governance.

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centres. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, flight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.