Managing AI Projects

Managing AI Projects

The workshop emphasizes what project managers need to do differently when managing AI initiatives, rather than teaching AI technology or repeating conventional project management principles.

Takeaways and Benefits

  • Learn why AI benefits must connect to measurable business outcomes, not just AI adoption for its own sake
  • Understand how to capture data requirements alongside functional ones and why data quality decides project viability
  • Identify the non-obvious stakeholders AI projects bring in: data owners, compliance officers, model end-users
  • Build scope and schedules that stay flexible under data uncertainty and iterative validation
  • Plan for the specialist people and non-human resources, compute, storage, licensed data that AI projects demand
  • Extend quality, risk, and monitoring practices to cover model performance, bias, explainability, and adoption
  • Close projects the right way: safe operationalization, model-monitoring ownership, and hypercare for users

Workshop Agenda

Day 1 – Understanding and Planning AI Projects

  • AI Projects vs. Traditional Projects: What Makes Them Different?
  • Types of AI Projects: Predictive AI, Generative AI, and Agentic AI
  • The AI Project Lifecycle: From Experimentation to Production
  • Identifying AI Opportunities and Assessing Project Feasibility
  • Defining Project Scope, Objectives, and Success Criteria for AI
  • Data Readiness, Quality, Availability, and Ownership
  • Managing Uncertainty and Experimentation in AI Projects
  • Selecting the Right Delivery Approach: Agile, Predictive, or Hybrid
  • Estimating AI Project Costs, Resources, and Timelines
  • AI Project Roles, Skills, and Stakeholder Expectations

    Day 2 – Delivering, Governing, and Scaling AI Projects
  • Managing AI-Specific Risks: Bias, Hallucinations, and Unpredictability
  • AI Governance, Ethics, Privacy, and Regulatory Compliance
  • Managing AI Vendors, Models, and Technology Dependencies
  • Validating AI Outputs: Testing, Accuracy, and Performance
  • Human Oversight, Accountability, and Decision-Making
  • Managing Scope Changes and Evolving AI Capabilities
  • Integrating AI Solutions into Existing Business Processes
  • Change Management, Trust, and User Adoption
  • Deploying, Monitoring, and Maintaining AI Solutions
  • Measuring Business Value and ROI in AI Projects
  • Managing Model Drift, Continuous Improvement, and AI Project Closure

Trainer

Florian Ivan is the ideal trainer for “AI in Project Management,” thanks to a rare dual specialisation that perfectly mirrors the course itself.

With over 20 years of project management expertise his command of project management methodologies is second to none. Equally impressive is his technology pedigree: a data analysis degree from Oxford, formative years at a data analytics startup, and a senior Programme Manager role at Microsoft give him deep, firsthand fluency in the tech landscape that underpins modern AI tools.

Florian doesn’t just understand both worlds, he lives them, making him uniquely positioned to show professionals exactly how AI can transform the way projects are managed.

Languages

  • This course in available in English and French

Duration

  • 1-2 days in classroom
  • Also available as online or virtual delivery

Ready to bring your team on the AI journey?

This training has already helped many professionals take the leap — with confidence and a clear method. Whether you want to organise a session for your team or simply find out more about the course content, we’d love to hear from you.

👉 Get in touch to discuss your needs and find the format that works best for you.

© ROLF