Responsible AI in Practice: How to Implement Your AI Governance Framework
Dr Georgiana Marsic
Pioneering Trustworthy & Responsible AI
Dr Paul Dongha
Pioneering Trustworthy & Responsible AI
Practical course showing how to make AI Governance operational
Learn how to implement your organisation’s AI Governance Framework in 2 weeks. Leave with practical knowledge, frameworks and ready-to-deploy templates, but more importantly with the clarity of knowing how to embed Responsible AI practices in your organisation to build trust with your stakeholders and prepare for compliance with the EU AI Act and other AI regulations.
What you’ll learn
In 2 weeks, you'll learn how to implement an AI Governance Framework in practice and gain the confidence to make AI Governance operational.
Recognise using real case studies how AI systems can fail legally, operationally, reputationally, and strategically.
Understand how AI Governance builds trust with stakeholders and embeds regulatory compliance/standard alignment (EU AI Act, ISO42001, NIST)
Define the core elements of your AI Governance Framework.
Articulate your AI Governance purpose: why AI Governance is needed in your organisation. Draft your Ethical AI Principles.
Define your AI Governance scope by clarifying what qualifies as AI, your organisation's role in the AI value chain and its obligations.
Set strategic trajectory and success criteria: where you are going with AI Governance (between minimum compliance and trustworthy AI).
Outline decision rights, and the RACI / accountability for AI Governance decisions.
Build your AI Governance body(ies) (AI Governance Council/AI Steering Committee/AI Ethics Board), establish accountability, decision rights.
Centralised vs federated governance models: trade-offs and when each works.
Outline your Risk Management Framework (risks, mitigations, controls), and risk classification (low / medium / high) mapped to EU AI Act.
Define the AI Policy(ies) you need, and create your AI Policy(ies) using templates.
Define your AI inventory, AI intake, AI impact and risk assessment and vendor / third-party AI Governance process(es).
Operationalise the AI inventory and intake process. Establish AI impact and risk assessment across the AI Solution Lifecycle.
Set AI Solution Design, Development & Deployment Governance, also from an Agentic AI perspective, artefacts (e.g., model cards, datasheets).
Establish Post-Deployment Governance: Monitoring, Incident Management and Retirement.
Define People & Culture enablement plan: AI Literacy, Comms, Change Management.
Specify the required Digital Capabilities: reference architecture, tooling, guardrails (e.g., PII redaction), data & digital assets.
Connect it all in Operations: operating model, performance management & mechanisms for adaptive evolution=>AI Governance as a living system.
Learn directly from Georgiana & Paul
Dr Georgiana Marsic
Experienced Data & AI Governance Leader. ISO 42001 Lead Implementer.
Dr Paul Dongha
Paul is the Head of Responsible AI and AI Strategy at one of UKs largest banks.
Who this course is for
Anyone interested to learn about how AI Governance is implemented in an organisation
Leaders / practitioners who directly oversee or contribute to establishing Responsible AI practices
Compliance guardians (e.g., Legal Counsel, Privacy Officer, Chief Risk Officer) or AI product leaders (e.g., Head of AI, Product Managers)
What's included
Live sessions
Learn directly from Dr Georgiana Marsic & Dr Paul Dongha in a real-time, interactive format.
Access to recordings and templates
Lifetime access to course resources. Refresh your learning whenever you need to.
Like-minded peers
Learn with and from fellow practitioners struggling with similar challenges.
Hands-on practice
The course provides practical knowledge and the opportunity to complete hands-on activities.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Community
Becoming part of a community and building connections.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
Week 1
Jun
24
Session 1: AI Governance Foundations & Motivations
Jun
25
Session 2: Authority, Accountability and Governance Structures. Risk, Control Environment and Assurance.
Jun
26
Week 1 Office Hours
Week 2
Jul
1
Session 3: Establish AI Lifecycle Governance to govern AI solutions including Agentic AI
Jul
2
Session 4: Capability, implementation and adaptive evolution: making AI Governance operational and keeping the system alive
Jul
3
Week 2 Office Hours
Schedule
Live sessions
4 hrs / week
Wed, Jun 24
5:00 PM—6:30 PM (UTC)
Thu, Jun 25
5:00 PM—6:30 PM (UTC)
Fri, Jun 26
3:00 PM—4:00 PM (UTC)
Frequently asked questions
£695
GBP