AI Manager: From AI Pilot Project to AI Strategy

Course overview

An AI Manager leads AI initiatives from the first AI pilot project to a viable AI strategy for the entire company. The focus is on evaluating pilot results, prioritizing use cases, and deriving target images, roadmaps, and governance structures. The training addresses the path from individual attempts to a coordinated direction, rather than the technical setup of individual solutions. Evaluating and Deciding on Pilot Projects A pilot provides insights, not proof - the evaluation determines the next step. - Establish success criteria for pilot projects and measure results against them - Systematically capture learning experiences regarding data, tools, acceptance, and effort - Create decision templates for continuation, adjustment, or termination - Recognize typical pilot pitfalls: individual solutions, lack of responsible parties, unclear data basis Organizing Use Cases into the Portfolio - Collect and uniformly describe use cases from specialist departments - Evaluate benefits, effort, data availability, and risk for each use case - Determine order and dependencies within the portfolio - Prepare make-or-buy decisions between standard services and in-house development From Experience to AI Strategy A strategy answers what the company uses AI for and what it consciously does not. - Derive target images and action fields from business strategy and pilot results - Develop a roadmap with milestones, budget framework, and measurable interim results - Formulate principles for the use of AI in the company - Prepare the strategy for management and committees in a decision-ready format Organization, Roles, and Competencies - Define responsibilities between specialist departments, IT, data protection, and management - Plan competency building and training needs along the roadmap - Design collaboration with external partners and providers Governance and Framework Conditions Without rules, every AI strategy remains a statement of intent. - Translate requirements from the EU AI Act and data protection into guidelines and approval processes - Regulate handling of risks, transparency, and accountability - Build documentation and evidence for decisions Managing and Reporting Progress - Establish key figures for the use, impact, and cost-effectiveness of AI initiatives - Organize regular reviews of the strategy and adjustments to new opportunities - Report results understandably for management and employees This training conveys how a coordinated AI strategy with clear responsibilities emerges from individual AI pilot projects.

Upcoming dates

• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Aachen · Hybrid Learning
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Augsburg, Bayern · Hybrid Learning
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Berlin · Hybrid Learning
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Bielefeld · Hybrid Learning

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