Governance of National AI Infrastructure Training Course

Course Overview

Governance of National AI Infrastructure has become a strategic priority for governments, regulatory authorities, national digital transformation agencies, public institutions, research organizations, telecommunications regulators, cloud service providers, and innovation ecosystems seeking to establish secure, resilient, ethical, and scalable artificial intelligence capabilities that drive economic growth and public sector modernization. The rapid advancement of National AI Infrastructure, Artificial Intelligence (AI), AI Governance, AI Policy, AI Strategy, AI Regulation, High-Performance Computing (HPC), Cloud Computing, Data Centres, National Data Infrastructure, AI Supercomputing, Machine Learning, Generative AI, Large Language Models (LLMs), Data Governance, Cybersecurity, Digital Sovereignty, AI Ethics, Responsible AI, Digital Public Infrastructure, AI Innovation, Big Data Analytics, Internet of Things (IoT), Edge Computing, AI Risk Management, Digital Economy, Smart Government, AI Standards, Digital Transformation, and Sustainable Development Goals (SDGs) is transforming public administration, healthcare, education, agriculture, finance, manufacturing, energy, transportation, and national security. This comprehensive training course equips participants with practical knowledge and advanced competencies to develop, govern, secure, and manage national AI infrastructure that supports innovation, competitiveness, and responsible digital transformation.

The course provides participants with a comprehensive understanding of national AI infrastructure frameworks, AI governance models, digital public infrastructure, cloud and high-performance computing ecosystems, AI data platforms, national AI strategies, regulatory frameworks, institutional governance, cybersecurity, AI ethics, data sovereignty, digital identity integration, procurement strategies, innovation ecosystems, and AI investment planning. Participants will learn how to formulate national AI infrastructure policies, establish governance structures, manage AI computing resources, strengthen institutional coordination, implement secure data governance systems, develop AI-ready digital infrastructure, and ensure compliance with national and international standards. The programme incorporates internationally recognized frameworks and best practices from the OECD AI Principles, UNESCO Recommendation on the Ethics of Artificial Intelligence, NIST AI Risk Management Framework, ISO/IEC AI Standards, International Telecommunication Union (ITU), World Bank Digital Development Framework, United Nations Digital Public Infrastructure initiatives, African Union Digital Transformation Strategy, and the Sustainable Development Goals (SDGs).

Special emphasis is placed on emerging technologies and strategic infrastructure including sovereign cloud platforms, AI-ready data centres, high-performance computing clusters, graphics processing unit (GPU) infrastructure, AI chips, edge computing, quantum computing readiness, AI model governance, digital twins, blockchain-enabled governance, interoperable digital public infrastructure, national data exchanges, cybersecurity operations centres, AI observability platforms, automated compliance systems, privacy-enhancing technologies, geospatial analytics, AI innovation hubs, open-source AI ecosystems, green computing, and sustainable AI infrastructure. Participants will also examine governance issues relating to responsible AI deployment, environmental sustainability, digital inclusion, procurement transparency, ethical AI, public-private partnerships, workforce development, investment governance, resilience, and international collaboration.

Through practical governance workshops, infrastructure planning exercises, AI strategy simulations, policy development sessions, collaborative group work, web-based tutorials, and relevant international case studies, participants will develop competencies required to govern national AI infrastructure programmes effectively. Upon successful completion, participants will be equipped to strengthen AI governance, modernize digital public infrastructure, improve cybersecurity and resilience, accelerate responsible AI innovation, optimize AI investments, enhance institutional coordination, protect national digital assets, and build secure, inclusive, and future-ready AI ecosystems that support sustainable national development.

Course Objectives

1.     Understand the principles and frameworks governing national AI infrastructure.

2.     Develop national AI infrastructure policies aligned with international governance standards.

3.     Strengthen institutional governance for AI infrastructure planning, implementation, and oversight.

4.     Apply responsible AI, ethical governance, and regulatory compliance in national AI initiatives.

5.     Enhance governance of cloud computing, high-performance computing, and AI data platforms.

6.     Strengthen cybersecurity, privacy, and digital sovereignty for national AI infrastructure.

7.     Promote AI innovation through strategic investment, partnerships, and digital transformation.

8.     Improve interoperability, data governance, and digital public infrastructure integration.

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

10.  Build resilient, secure, sustainable, and inclusive national AI ecosystems.

Organizational Benefits

1.     Strengthened governance of national AI infrastructure and digital public assets.

2.     Improved coordination across government institutions, academia, and industry.

3.     Enhanced cybersecurity, data protection, and resilience of AI infrastructure.

4.     Improved compliance with international AI governance principles and technical standards.

5.     Increased efficiency through integrated AI platforms and digital public infrastructure.

6.     Enhanced national innovation capacity and AI research capabilities.

7.     Improved evidence-based decision-making through advanced AI and analytics.

8.     Increased investment confidence through transparent AI governance and infrastructure planning.

9.     Strengthened institutional readiness for emerging AI technologies and digital transformation.

10.  Sustainable AI infrastructure supporting inclusive economic growth and national competitiveness.

Target Participants

This course is designed for government officials, national AI strategy teams, policymakers, ICT ministry officials, digital transformation managers, chief information officers, chief technology officers, AI governance officers, regulators, telecommunications authorities, cybersecurity professionals, cloud infrastructure managers, data governance specialists, national statistical office personnel, innovation agency officials, research institution leaders, university administrators, AI researchers, data scientists, enterprise architects, infrastructure planners, project managers, procurement officers, development partners, consultants, monitoring and evaluation specialists, and professionals responsible for AI governance, digital infrastructure, national technology policy, and innovation management.

Course Outline

Module 1: Introduction to National AI Infrastructure Governance

·       Principles of AI infrastructure governance

·       Components of national AI infrastructure

·       AI ecosystem development

·       Digital transformation strategies

·       Global AI governance trends

·       International best practices

Case Study: Developing a national AI infrastructure governance roadmap.

Module 2: National AI Policies, Strategies and Institutional Frameworks

·       National AI strategy development

·       AI policy formulation

·       Institutional governance

·       Regulatory frameworks

·       Stakeholder coordination

·       Public sector leadership

Case Study: Designing an institutional framework for national AI implementation.

Module 3: AI Computing Infrastructure and High-Performance Computing

·       High-performance computing (HPC)

·       GPU infrastructure

·       AI computing platforms

·       Data centre planning

·       Cloud computing

·       Infrastructure scalability

Case Study: Establishing a national AI supercomputing centre.

Module 4: Data Governance and National AI Data Infrastructure

·       National data governance

·       Data quality management

·       Metadata standards

·       Data interoperability

·       Open data ecosystems

·       Data sharing frameworks

Case Study: Building a secure national AI data exchange platform.

Module 5: Cybersecurity, Privacy and Digital Sovereignty

·       AI cybersecurity

·       Privacy-enhancing technologies

·       Digital sovereignty

·       Information security

·       Cyber resilience

·       Incident response planning

Case Study: Protecting national AI infrastructure against cyber threats.

Module 6: Artificial Intelligence Ethics and Responsible Governance

·       Responsible AI principles

·       Explainable AI

·       Algorithmic accountability

·       Bias mitigation

·       Human oversight

·       Ethical governance

Case Study: Implementing ethical governance for AI-enabled public services.

Module 7: AI Infrastructure Procurement and Investment Governance

·       Strategic procurement

·       Infrastructure financing

·       Public-private partnerships

·       Investment governance

·       Vendor management

·       Contract oversight

Case Study: Procuring national AI infrastructure through transparent governance processes.

Module 8: AI Innovation Ecosystems and Digital Public Infrastructure

·       Innovation ecosystems

·       Digital public infrastructure

·       AI research collaboration

·       Startup ecosystems

·       Technology transfer

·       Innovation policy

Case Study: Developing a national AI innovation hub supporting public sector transformation.

Module 9: Emerging Technologies Supporting AI Infrastructure

·       Edge computing

·       Internet of Things (IoT)

·       Quantum computing readiness

·       Blockchain integration

·       Digital twins

·       Green computing

Case Study: Integrating emerging technologies into national AI infrastructure planning.

Module 10: Monitoring, Evaluation and Performance Management

·       Results-based management

·       AI infrastructure performance indicators

·       Monitoring frameworks

·       Governance reporting

·       Compliance reviews

·       Continuous improvement

Case Study: Measuring the performance and maturity of national AI infrastructure programmes.

Module 11: Risk Management and Business Continuity

·       Enterprise risk management

·       AI infrastructure resilience

·       Disaster recovery

·       Business continuity planning

·       Operational governance

·       Crisis management

Case Study: Developing a resilience strategy for critical national AI infrastructure.

Module 12: Emerging Trends in National AI Infrastructure Governance

·       Generative AI ecosystems

·       Sovereign AI platforms

·       AI observability

·       Autonomous infrastructure management

·       International AI cooperation

·       Future AI governance strategies

Case Study: Developing a long-term national strategy for secure, resilient, and globally competitive AI infrastructure.

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) centers. 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.