After completing the course, participants will be able to:

• differentiate a coherent organisational AI strategy from a collection of stand-alone projects and tools;
• link candidate AI uses to strategic objectives and prioritise them using explicit decision criteria;
• assess data, technology, capability, cost, time, governance and human-oversight requirements;
• select an appropriate assisted, augmented or autonomous approach and identify suitable implementation options;
• define KPIs, value-realisation measures and decision gates for prototyping, production and scale; and
• prepare an initial Organisational AI Strategy Canvas and structure a 0-36-month transformation roadmap.

Module 1: From AI projects to organisational AI strategy (the project-strategy distinction, strategic urgency and introduction to the Organisational AI Strategy Canvas)

Module 2: Business needs, strategic objectives and the use-case portfolio (starting from business needs, short-, medium- and long-term objectives, use-case portfolio design, prioritisation criteria and initial KPI inputs)

Module 3: Implementation architecture – autonomy, data, technology and prototyping (assisted, augmented and autonomous AI; data strategy; build, buy, partner and AI-as-a-Service decisions; cost, time and prototyping as strategic learning)

Module 4: Organisation, culture, governance and AI literacy (operating model, role allocation, adoption, capability development, governance, NIST AI RMF, ISO/IEC 42001, regulation, privacy, risk controls and human oversight)

Module 5: KPIs, value realisation and the 0-36-month AI roadmap (success measures, value realisation, short-, medium- and long-term initiatives and conversion of the strategy canvas into an organisational AI strategy document)

Dr. Merve Ayyüce KIZRAK

Dr. Merve Ayyüce Kızrak is the Founder and CEO of HUX AI, specialising in AI governance, risk management and trustworthy AI. She has been working in AI since 2007, with experience across academia, government and industry. She previously served as an AI Specialist at the Digital Transformation Office of the Presidency of the Republic of Türkiye, where she was a core contributor to the National AI Strategy and led the Public Sector Data Space initiative. She has represented Türkiye in OECD AI governance work and contributed to international initiatives involving GPAI, CEIMIA, Oxford Insights, and the Council of Europe’s CDNET. She has also taught AI engineering and ethics at university level. She holds a PhD in Electronics and Communication Engineering and is an ISO/IEC 42001 Lead Auditor.

Organisations need more than isolated AI projects, generative-AI tools or short-term automation experiments. They need a strategy that connects AI with institutional vision, digital-transformation priorities, data assets, technology infrastructure, people, governance and ethics. This course guides managers through the decisions required to build that strategy. Participants distinguish a coherent organisational AI strategy from a collection of individual projects and create a portfolio of use cases linked to business needs and strategic objectives. They priorities opportunities using value, feasibility, data readiness, risk, scalability and KPI clarity. The course compares assisted, augmented and autonomous AI approaches and examines data ownership, quality, governance and privacy; build, buy, partner and AI-as-a-Service choices; prototyping and controlled pilots; and the decision gates required for production and scale. It also addresses organisational design, capability development, AI literacy, NIST AI RMF, ISO/IEC 42001, human oversight and value realisation. Participants conclude by structuring an Organisational AI Strategy Canvas and a 0-36-month roadmap. The course connects this roadmap with the BSC AI Factory ecosystem, including European computing capabilities available through EuroHPC JU and Türkiye’s national infrastructure and support services provided through Turkish Science e-Infrastructure (TRUBA).

Basic familiarity with everyday AI concepts and organisational decision-making is recommended. No coding, data-science or specialist technical background is required.

None required.

An internet-connected computer or tablet, a current web browser and audio-playback capability. No additional software or programming environment is required.