Leadership and strategy
AI project and product management course
Take an AI project from idea to production without it becoming an endless pilot.
Many AI projects start with a brilliant demo and stay in “pilot” forever. It is rarely a technology problem; it is a management problem: requirements that cannot be checked, data nobody maintains, risks that surface too late or users who do not trust the result.
This course gives project managers and product owners a method for taking AI to production: how to define what “good enough” means, how to evaluate a system that does not always answer the same way, how to plan human oversight and how to keep quality up once it is in use.
No coding, but enough understanding of the technology to make good decisions and talk on equal terms with the technical team and with vendors.
What you will learn
- Understand how an AI project differs from a classic software project
- Define requirements and quality criteria for non-deterministic systems
- Plan data, evaluation and human oversight from the start
- Manage technical, legal and adoption risks
- Organise the team and the improvement cycle once in production
Syllabus
8 modules, from the fundamentals to the final project.
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What changes with AI
- Probabilistic and "good enough" results
- The role of data and business knowledge
- Lifecycle of an AI product
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Discovery and fit
- Problem, user and process before technology
- Quick proof of concept with existing tools
- Criteria for continuing or dropping it
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Requirements you can verify
- Test cases and an evaluation set
- Quality, cost and latency as requirements
- What to do when the AI does not know the answer
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Data and knowledge
- Sources, permissions and information quality
- Personal and confidential data
- Who keeps the content up to date
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Common architectures for non-technical people
- Assistants, RAG, data extraction, agents and automations
- What each one means for timeline, cost and risk
- Off-the-shelf tool, platform or custom development
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Evaluation and launch
- Testing with real users and human review
- Gradual roll-out and communication plan
- Usage, quality and business metrics
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Risk and compliance
- Risk register for an AI project
- Transparency, oversight and AI Act obligations
- Security and misuse of the system
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Operate and improve
- Monitoring quality in production
- User feedback loop
- Model changes, costs and versions
Tools you will practise with
- AI project canvas
- Evaluation set template
- Risk register
- Jira, Trello or the team's project management tool
Hands-on project
You plan an AI project in your organisation from start to finish, with the project canvas, the set of evaluation cases, the risk register and the phased launch plan.
Requirements
- Experience in project or product management.
- No coding required.
Other courses
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AI business case and ROI course
Turn an AI idea into a business case with numbers you can defend.
- Duration: 8 hours
- Level: Intermediate
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AI change management and adoption course
Get AI used for real, with judgement and without fear, across the organisation.
- Duration: 6 hours
- Level: Beginner
-
AI course for executives and managers
Decide with judgement where to apply AI, how much to invest and how to lead the change.
- Duration: 6–8 hours
- Level: Beginner
Want this course for your team?
We adapt the content, length and format to your company.