Chief AI Officer Diploma Programme: the original.

• You decide which initiatives create value, which burn budget, and which tasks an agent may take on.
• You turn the values of the people affected into testable requirements and set where humans approve, intervene and stay accountable (human gates).
• You make reasoned technology decisions, from a single agent to several agents working together, and make success measurable with KPI cards.
• You build governance under the EU AI Act and ISO/IEC 42001 into operations: roles, risk and impact assessment, an agent register, release before go-live, monitoring and audit.
• You present an AI Strategy 2030 and a decision-ready initiative to your leadership.

Modules

Five modules, 100 teaching units, one initiative: yours. The ADA Sprint moves through 12 Building Blocks in three phases (ACT, DESIGN, ALIGN), and each phase ends with a quality gate. Every module is one third input, one third case work and one third work on your own initiative. Agentic AI runs through every module.

1. 01

   Module 1 · Strategic Context & State of AI Agents20 units live · 1 Friday + 3 evenings

   What GenAI and agents can reliably do today, and where they fail. You find the tasks an agent should take on, and the ones it deliberately should not.

   Learning goals

   • Place language models, RAG and multi-agent systems in context, without the hype
   • Find agent value cases and set autonomy levels
   • Prioritise ideas by value: maximal valuable product instead of minimum viable product
   • Choose your initiative and frame it as a one-page proposal

   Result: Agent opportunity map and project proposal

2. 02

   Module 2 · ACT · Building Blocks 1–420 units live · 1 Friday + 3 evenings

   What your initiative is for, what value it creates, who it affects and what data it needs. Plus your agent's mandate, limits and access rights.

   Learning goals

   • Clarify purpose and context: system of interest, system environment, concept of operations
   • Set strategic value and core values, and surface goal conflicts
   • Involve stakeholders: roles (RACI), participation, the people affected by agent actions
   • Set up a data strategy: sources, lineage, data protection, least-privilege access

   Result: Project context in the Value Register, agent mandate, access matrix

   Quality Gate ACT

3. 03

   Module 3 · DESIGN · Building Blocks 5–820 units live · 1 Friday + 3 evenings

   This is where values become system design: requirements, threats, controls and clear limits for humans and agents.

   Learning goals

   • Apply AI Ethics by Design through three lenses: duties, consequences, character
   • Derive ethical value requirements with threats and controls
   • Detect and limit data-quality issues and bias
   • Set limits and human oversight: human-in-the-loop, human-on-the-loop, escalation, transparency
   • Handle agent-specific risks such as prompt injection, and specify your agent's behaviour
   • Prepare a fundamental rights impact assessment under the EU AI Act

   Result: Value Register with requirements, threats and controls, human-gate design, agent behaviour spec

   Quality Gate DESIGN

4. 04

   Module 4 · ALIGN · Building Blocks 9–1220 units live · 1 Friday + 3 evenings

   How your initiative goes live and stays there: technology, change, measuring success, and an AI management system under ISO/IEC 42001.

   Learning goals

   • Decide on technology: build, buy, partner or compose; orchestrate several agents
   • Shape change: adoption, enablement, communication
   • Measure success: business, technical, ethical and quality KPIs, plus evaluation and monitoring of agents
   • Set up governance: roles, policies, audits, continuous improvement
   • Apply ISO/IEC 42001: structure of the AI management system, risk and impact assessment, controls, a gap analysis for your own initiative

   Result: Architecture decision, KPI cards, governance corridor with agent register, ISO/IEC 42001 gap analysis

   Quality Gate ALIGN

5. 05

   Module 5 · AI Leadership & AI Strategy 203020 units live · 1 Friday + 3 evenings

   You lead human-and-agent teams, steer an AI portfolio and take your AI Strategy 2030 to your leadership.

   Learning goals

   • Take on the Chief AI Officer role: mandate, accountability, working with the board and business units
   • Steer an AI portfolio: prioritise, allocate resources, stop
   • Develop trends and 2030 scenarios for your industry
   • Draw up an AI action plan under the EU AI Act and ISO/IEC 42001, with milestones
   • Prepare your project presentation for the examination board

   Result: AI Strategy 2030 with an agent roadmap and a 12-month action plan, project presentation

What you leave with

• A decision-ready AI initiative of your own, worked through all 12 Building Blocks
• Your Value Register: from stakeholder values through requirements, threats and controls to KPIs
• An agent behaviour spec and a human-gate design
• KPI cards, a governance corridor and an ISO/IEC 42001 gap analysis for operations
• Your AI Strategy 2030 with an action plan
• Your project presentation and the diploma

Who leads you

Sabine Singer, MBA

Sabine created Austria's first executive programme for Chief AI Officers and the ADA AI Ethics by Design Framework™ this programme is built on. She is an ISO/IEC 42001 Lead Auditor and Lead Implementer, an IEEE 7000 CertifAIed Lead Assessor, and received the Constantinus Award 2025 (1st place, Ethics & CSR). She has trained more than 600 people. Her Valuebased AI Academy is Austria’s first Business Academy for AI Ethics by Design and valuebased business development.

You present your own initiative to the examination board of Sabine Singer and her co-trainers and answer their questions on the project and the content. You then receive the diploma of the Valuebased AI Academy (Sophisticated Simplicity GmbH) and a confirmation of attendance stating scope and period.