Programme overview
Technical depth: Conceptual · Practical mode: Case study
Introduction
Government entities face pressure to use AI to shorten service times, manage rising demand and improve decisions, yet many launch isolated pilots that never scale or that erode public trust. Without a roadmap linking use cases to readiness, governance and funding, investment scatters across disconnected experiments. This coreconcept course equips public sector executives to plan AI adoption across a portfolio of government services using international principles and standards. Participants test each step against cases from several service domains and leave with an AI Adoption Roadmap for their own entity.
Course Objectives
- Assess an entity's readiness for AI across governance, data, infrastructure, skills and public trust
- Apply international AI principles and standards, including the OECD framework, ISO/IEC 38507 and ISO/IEC 42001, to set governance for AI in public services
- Prioritise AI use cases across a service portfolio by public value, feasibility and risk
- Sequence pilots, scale-up and enabling investments into a phased roadmap with stage gates and benefits measures
- Evaluate fairness, transparency and procurement risks before AI is used in citizen-facing decisions
- Produce an AI Adoption Roadmap ready for submission to the entity's leadership for endorsement
Target Audience
- Executives accountable for the design and delivery of public services
- Digital government and transformation leaders setting technology direction for their entities
- Chief data and technology officers responsible for platforms, data and AI capability
- Strategy and planning leaders aligning initiatives with policy goals and budgets
- Senior policy leaders shaping how services and automated decisions are governed
- Executive committee members approving investment in digital and AI programmes
Course Outline
Day 1: AI in Public Services and Institutional Readiness
- Government AI Use Patterns Across Service Delivery, Enforcement and Back Office
- Public Value and Citizen Trust Drivers for AI in Services
- OECD Framework for Trustworthy AI in Government: Enablers, Guardrails and Engagement
- Institutional Readiness Diagnosis Using UNESCO Readiness Assessment Methodology Dimensions
- Digital Government Maturity Baseline with the GovTech Maturity Index
Day 2: Principles, Standards and Operating Models
- OECD AI Principles and the UNESCO Recommendation on the Ethics of AI
- ISO/IEC 38507 Governance Implications of AI for Governing Bodies
- ISO/IEC 42001 AI Management System Scope for a Public Entity
- ISO/IEC 42005 AI System Impact Assessment for Citizen-Facing Services
- AI Operating Model Options: Central Hub, Federated and Hub-and-Spoke
Day 3: Building the Roadmap
- Service Journey Mapping to Locate AI Opportunities
- Use Case Prioritisation Matrix: Public Value, Feasibility and Risk
- Three Horizons Model for Sequencing Pilots, Scale-Up and Transformation
- Data and Infrastructure Dependency Mapping per Use Case
- Benefits Dependency Network for Service Outcomes
Day 4: Risk, Procurement and Scaling Decisions
- Algorithmic Fairness Review for Eligibility and Enforcement Decisions
- AI Procurement Guardrails Using the AI Procurement in a Box Toolkit
- Pilot-to-Scale Stage Gates and Exit Criteria
- Public Transparency Artefacts: Algorithm Registers and Service Notices
- Roadmap Risk Register Aligned to ISO 31000
Day 5: Case Work and the AI Adoption Roadmap
- Benefits Administration Case Study: Automated Eligibility Screening
- Municipal Services Case Study: AI Triage of Citizen Requests
- Readiness and Prioritisation Scorecard for an Own Service Portfolio
- AI Adoption Roadmap Drafting
- Executive Panel Review and Roadmap Defence
Skills You Will Gain
- AI Readiness Assessment
- Public Value Analysis
- AI Portfolio Prioritisation
- Roadmap Sequencing
- Public Sector AI Governance
- Algorithmic Accountability
- Technology Investment Oversight
Why Attend This Course
- Return with an AI Adoption Roadmap for your own service portfolio, tested before a panel of fellow executives
- Challenge vendor and internal proposals with one consistent test of public value, feasibility and risk
- Anticipate the trust, fairness and transparency questions that citizens and oversight bodies will ask of AI services
- Compare roadmap choices with public sector leaders from other countries and service domains
Conclusion
AI improves public services only when its adoption is sequenced, governed and explained to the citizens it affects. This course moves from assessing an entity's readiness, through the principles, standards and operating models that govern public sector AI, to the prioritisation, procurement and risk decisions that determine whether pilots scale. The final day turns that material into an AI Adoption Roadmap reviewed by peers acting as an executive panel, giving participants a defensible plan to put before their leadership.