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AI Governance Practitioner Certification Lead Level
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AI Governance Practitioner Certification Lead Level

Design, lead and sustain enterprise AI governance programs across regulation, boards and organisational change
Last updated 7/2026
English

What you'll learn

  • Design a complete AI governance architecture for an organisation with none, from inventory to deployment gate
  • Apply the PROVE framework and GRADE evidence stack to prove any single system is governed, not just certified
  • Structure a governance function that serves multiple sectors under one architecture, without false uniformity
  • Run the centralise-or-localise analysis to decide what belongs at the centre and what belongs with sector leads
  • Translate one governance position honestly for a board and a regulator in the same sitting
  • Lead a governance programme through team turnover, new regulation, and portfolio growth without it collapsing
  • Apply the no-partial-credit principle and hold a deployment gate even under real organisational pressure
  • Prioritise governance work honestly under genuine capacity constraint, managing degradation rather than hiding it

Course content

6 sections6 lectures1h 42m total length
  • Introduction1:12

    Welcome to the AGPC™ Lead Level The Lead Level is the highest tier of the AI Governance Practitioner Certification programme. Where the Practitioner level teaches you to govern one AI system, Lead teaches you to design, lead, and sustain AI governance across an entire organisation. How the five modules connect The five modules form a single arc, not five separate topics: L-M1 teaches you to design a governance architecture for an organisation that has none. L-M2 teaches you to translate that governance for a board and a regulator at the same time. L-M3 introduces the PROVE framework, the organising logic behind every module that follows. L-M4 takes that framework to enterprise scale, across multiple sectors under one governance function. L-M5 tests everything against change: what makes a governance programme survive disruption rather than collapse under it. Each module follows the same shape: a real organisational challenge, the analytical thinking a Lead-level practitioner applies to it, a design decision and what it cannot guarantee, and practice questions with full reasoning, not just correct answers. Prerequisite AGPC™ Practitioner certification, or equivalent hands-on experience governing individual AI systems, is recommended before starting this course. This is not an introductory course. Every module operates at the application and analysis level. A note on certification Completing this course confirms that you have covered the AGPC™ Lead Level body of knowledge and are prepared for the official AGPC™ Lead Level examination. It does not itself certify you. The official examination is a separate, independently administered assessment. To follow announcements on the AGPC™ examination as they're finalised, connect with Balamurali Boggu on LinkedIn. The Study Guide is attached to this lecture as a downloadable resource. Read each module in full before attempting its practice questions.

Requirements

  • No coding or technical AI/ML background required
  • Familiarity with basic AI governance terminology (covered in Foundation and Practitioner levels) is assumed
  • AGPC™ Practitioner certification, or equivalent hands-on experience governing individual AI systems, is recommended before starting this course

Description

AI governance stops being a checklist exercise the moment you're the person a board, a regulator, or a Chief Risk Officer turns to and asks: is this actually governed? This course is built for that moment.


The AGPC™ Lead Level is the highest tier of the AI Governance Practitioner Certification programme. It moves beyond governing a single AI system, which is what the Practitioner level teaches, into designing, leading, and sustaining AI governance across an entire organisation. If Practitioner asks "is this system governed?", Lead asks "how do I build, defend, and keep alive the governance that answers that question for every system, every audience, and every kind of change an organisation will face?"


You'll follow one consultant, Divyansh Mehta, through five real-world engagements, each one built around a different organisational challenge under the EU AI Act, GDPR, and ISO/IEC 42001:


Module 1: Governance by Design. An airport operator with six AI systems and no governance programme at all, twelve weeks from a board presentation. You'll learn to build a system inventory that finds what governance missed, classify systems deliberately, name accountability to a person rather than a role, and design a deployment gate that holds for every system going forward.


Module 2: Board and Regulator Engagement. A financial services bank facing a board presentation and a regulator's information request twelve days apart, from the same evidence base. You'll learn the five-pairing translation check that catches the gap between what a leader says and what a regulator hears, how to triage a regulator notification by exposure rather than ease, and the single consistency test that keeps two very different communications honest with each other.


Module 3: The PROVE Framework. A healthcare technology company that already holds ISO 42001 certification and employs certified governance staff, and still can't produce complete evidence that one clinical system is governed. This is the module where PROVE, the five-principle framework at the centre of the whole programme, and the GRADE evidence stack get applied in full, including the no-partial-credit principle that a four-of-five evidence stack is not eighty percent governed.


Module 4: Organisational Governance Architecture. A financial group that has just acquired a healthcare business, now holding two high-risk AI systems in two sectors with genuinely different regulatory obligations. You'll learn to hold one governance framework constant while letting its application vary by sector, and to run the centralise-or-localise analysis that decides, element by element, what belongs at the centre for consistency and what belongs with sector specialists for correctness.


Module 5: Leading Governance Across Change. A telecoms group whose governance programme worked for eighteen months, until a restructuring halved the team, three of five governance leads left within two months, new regulation changed obligations for one system type, and two new systems needed deployment, all in the same quarter. This closing module teaches you what actually makes a governance programme survive disruption: the handover protocol, the Cadence review practice, and honest prioritisation under real capacity constraint.


Who this course is for


This course is built for professionals who are, or expect to become, responsible for AI governance at organisational scale: heads of AI governance, risk and compliance leaders, AI governance consultants who design programmes rather than operate within them, and senior practitioners moving from executing governance to owning it. The AGPC™ Practitioner level, or equivalent hands-on experience governing individual AI systems, is the recommended foundation. This is not an introductory course. Every module operates at the application and analysis level: you'll be asked to apply frameworks to real scenarios and analyse trade-offs, not recall definitions.


**What makes this different from a knowledge-based AI governance certification**


Most AI governance training teaches what the regulations say. This course teaches how to apply that knowledge as a leader: how to design governance architecture from nothing, how to hold two audiences honest with the same evidence, how to advocate for a framework without disparaging the certifications and qualified people an organisation has already invested in, how to structure governance across sectors that genuinely differ, and how to keep a programme alive when the people, the regulation, and the organisation around it all change at once. The five modules build on each other deliberately: the architecture from Module 1 is what makes the translation in Module 2 possible; the PROVE framework from Module 3 is the spine that runs through Module 4's enterprise-scale design; and Module 5 tests whether everything built in the first four modules can actually survive contact with organisational reality.


Every practice question in this course includes full reasoning, not just a correct answer: why the right answer is right, and specifically why each other option fails. That reasoning is the actual skill being taught.


A note on certification


Completing this course confirms that you have covered the AGPC™ Lead Level body of knowledge and are prepared for the official AGPC™ Lead Level examination. It does not itself certify you. The official examination is a separate, independently administered assessment. To follow announcements on the AGPC™ examination as they're finalised, connect with Balamurali Boggu on LinkedIn.

If you're ready to move from governing a system to being answerable for the governance itself, this course is where that starts.


Who this course is for:

  • This course is built for professionals who are, or expect to become, responsible for AI governance at organisational scale
  • heads of AI governance, risk and compliance leaders, AI governance consultants who design programmes rather than operate within them, and senior practitioners moving from executing governance to owning it
  • The AGPC™ Practitioner level, or equivalent hands-on experience governing individual AI systems, is the recommended foundation.
  • This is not an introductory course. Every module operates at the application and analysis level
  • you'll be asked to apply frameworks to real scenarios and analyse trade-offs, not recall definitions