Requirements, design, coding, testing, deployment — agents are in all five, and most of what they produce ships without a named owner. Through AI governance training, your leadership leaves with policy, oversight and a rollout plan for the whole lifecycle.
For leaders responsible for how AI gets adopted across an engineering organisation — setting policy, owning risk and proving governance works, rather than reviewing code line by line.
The people who carry the answer when a board, a customer or a regulator asks how AI is governed here.
Whoever has to turn a policy into something teams actually follow, without stopping delivery to do it.
The owners of the controls, the audit trail and the escalation path when agent-written code causes an incident.
AI is already in every stage of the lifecycle, and the EU AI Act puts deadlines on it. The AI governance training works through your own organisation module by module, so the capstone presents a plan you can actually run.
Requirements, design, coding, testing and deployment — every stage AI has already entered, named.
Learning objectiveKnow your real AI exposureA true picture of AI use across engineering, including the tools nobody approved.
Certify Your TeamFinding the highest-risk points across the lifecycle before an incident finds them for you.
Learning objectiveRank the risks worth acting on firstOversight effort spent where a failure would cost the most.
Certify Your TeamWho decides, who approves and who answers, written down for each stage rather than assumed.
Learning objectiveMake policy teams actually followRules clear enough to apply without a meeting to interpret them.
Certify Your TeamDesigning the record that shows what a model wrote, who reviewed it, and on what basis.
Learning objectiveBe ready before the auditor asksEvidence already on file, so an audit is a request rather than a scramble.
Certify Your TeamDraft the first version of a policy for your own organisation, with ownership filled in.
Learning objectiveTake a working draft back to the officeReady for legal and engineering to review the week the training ends.
Certify Your TeamThe categories specific to generated code, in plain language rather than in vendor terms.
Learning objectiveSet the security bar for agent-written codeReview rules that catch what agents get wrong before it reaches production.
Certify Your TeamReal incidents, and exactly what oversight would have caught each one before release.
Learning objectiveAvoid the mistakes other teams already madeControls picked from failures that happened, not from a vendor's checklist.
Certify Your TeamThe patterns that put ownership of your own codebase in question, and how they appear.
Learning objectiveKeep your IP cleanLicence problems caught while they are cheap to fix, not during due diligence.
Certify Your TeamWhat leaves the building inside a prompt or through the tools an agent is connected to, and the controls that stop it.
Learning objectiveProtect confidential dataCustomer and company information safe, without banning the tools people rely on.
Certify Your TeamDraft the reporting and oversight checklist your teams will actually be measured against.
Learning objectiveAsk your teams the right questionsUpdates that show what is really happening, at a rhythm leaders can sustain.
Certify Your TeamThe stages and the indicators that tell you honestly where the organisation stands.
Learning objectivePlace the organisation on a scaleA starting point everyone agrees on, so progress is shown rather than claimed.
Certify Your TeamMeasures of governance working, not of tools adopted.
Learning objectiveReport progress the board trustsFigures that show risk going down, not activity going up.
Certify Your TeamPilot, early adopters, organisation-wide, in an order that survives the first failure.
Learning objectiveRoll out without stalling deliveryTeams keep shipping while the new rules arrive, one group at a time.
Certify Your TeamThe structure that says who is called, when, and what authority they hold.
Learning objectiveEscalate fast when agents get it wrongIncidents reach a decision-maker quickly instead of waiting in a queue.
Certify Your TeamFinalise and present the governance rollout plan with its maturity assessment and metrics.
Learning objectiveEarn leadership backingThe mandate to take governance across every engineering team.
Certify Your TeamEvery module of the AI governance training ends in a document the leadership team drafted, not in a summary of somebody else's policy.
Policy, oversight and rollout build on each other across the AI governance training, so the final plan is one the organisation can actually run.
AI governance training with no coding required. The security and licensing material is in plain language, aimed at the people who set policy.
The EU AI Act and its neighbours are treated as dates with owners rather than as a slide at the end of a deck.
Two checkpoints with quizzes on risk mapping and on licensing scenarios, then a capstone presentation and a written escalation exercise.
An SDL Enterprise and Governance Certification per participant, issued at the end of the AI governance training for the checkpoints passed and the plan defended.
AI governance training covers where AI already sits in the lifecycle, who owns each stage, what the audit trail has to show, and how the rollout is sequenced, for the people who answer for it.
21 hours in total across three modules, instructor-led on site or live online, scheduled around your team and workshop-based throughout.
CTOs, VPs of engineering and product, and heads of platform, security or AI, rather than the engineers reviewing code line by line.
Yes. The AI governance training treats it as dates with owners rather than as a summary slide, and as a deadline the rollout plan has to meet.
A policy skeleton for its own organisation, an oversight checklist, a rollout plan with a maturity assessment, and the SDL Enterprise and Governance Certification for each leader.
The AI governance training is built for the group and priced on team size, level and timeline.
Strategy, workforce design and the economics of an AI-native organisation — for the people who set direction.
Learn More →Building production multi-agent systems — anatomy, orchestration, guardrails and a launch review.
Learn More →Design agentic systems that survive production — hybrid retrieval, knowledge graphs, multimodal pipelines and agents that coordinate.
Learn More →Redesigning how a team works — specs, documents, meetings, and a workflow proposal with its impact estimate.
Learn More →Agents are writing code in your organisation today. This AI governance training is where you decide who signs it off, and how to prove it to an auditor.