Programme Content
Pillar 1: Technology Strategy, Architecture, Data and AI Systems
CTO to CTAIO role evolution: tech, data and AI convergence
Data strategy, data platforms and modern AI infrastructure
AI systems overview: ML, GenAI and agentic architectures
Deploying AI systems: lifecycle, RAG architectures and production constraints
Platform engineering, APIs and distributed systems for scale
Compute strategy: cloud, GPUs, edge and infrastructure scaling
Automation strategy: RPA, APIs and agentic workflows
Technology decision frameworks: build vs buy vs partner
Pillar 2: Digital Platforms, Product Strategy and Innovation
Technology strategy for innovators in AI-driven markets
Platform strategy and ecosystem design: APIs, marketplaces and network effects
Business model innovation: pipeline vs platform economics and value capture
CTO-CPO partnership, digital product management and roadmap governance
Building internal ventures and new tech products
Technology adaptation, implementation excellence and renewal
Tech and AI sourcing, ecosystem building, and strategic alliances
Value chain digitalisation
Pillar 3: Technology Economics, FinOps and Value Creation
Financial statement analysis tools and framework for analysis, including profitability and other issues; advanced financial statement analysis from a capital market perspective, DuPont analysis, ROIC
Capital budgeting decision: NPV, IRR, capital allocation, measuring financial performance - residual income
Understanding cost for decision-making: cost behaviour, cost-volume-profit (CVP) analysis, target profit and volume, operating leverage analysis, sensitivity analysis
Cloud, compute and AI model costing; FinOps
Scaling strategies: organic, inorganic and ecosystem/GCC pathways
Innovation portfolio management and project finance
Vendor strategy, sourcing and interfirm collaboration models
Outsourcing strategy and build-partner-operate choices
Product operating model, agile execution and platform delivery governance
Technology economics for AI platforms, APIs and data monetisation
Pillar 4: Governance, Cybersecurity, Responsible AI and C-Suite Leadership
Shaping technology policy
IT, data and AI governance in the age of AI
Responsible AI: bias, hallucinations, safety, human-in-the-loop and compliance
Cybersecurity and AI risk governance
Sustainability and the imperative of ESG
Technology lifecycle, technical debt and risk controls
Corporate entrepreneurship and ecosystem partnerships
Strategic alliances, sourcing models and external innovation governance
Change management for AI-led transformation
Executive presence, board communication and stakeholder alignment
Crisis communication and thought leadership
Pillar 5: CTAIO Transformation (On-Campus Sessions)
Workshop style session: ecosystem strategy, platform play and alliance design
Workshop style session: AI for cybersecurity and responsible AI
Boardroom communication for CTAIOs: executive narrative, stakeholder influence and crisis messaging
AI opportunity mapping and prioritisation workshop
ROI and technology investment case workshop
Project presentations
