AI Transformation Manager for AI Implementations

Course overview

Individual AI projects do not constitute a transformation. This training prepares participants for the role of AI Transformation Manager, who does not view AI implementations as isolated initiatives but instead manages the transition to AI-supported work as a whole: across multiple projects, areas, and over an extended period. From Individual Project to Transformation Program Only by looking at the big picture can we prevent many good individual projects from running parallel to each other. - Capture and relate ongoing and planned AI initiatives within the company - Consciously plan sequences and dependencies between initiatives instead of starting them in parallel - Utilize synergies between areas and avoid duplicate work - Maintain and update a common vision across individual projects Establish Structures and Responsibilities for AI To ensure that AI is not just a project issue, it needs a fixed place within the organization. - Anchor permanent responsibilities for AI topics within the company - Establish internal points of contact and clear decision-making paths - Organize collaboration between departments, IT, and data protection - Keep committees lean: decide instead of manage Lead Areas into Change Sequentially Not every area can and should start simultaneously. - Determine the order of areas based on benefit and capacity to absorb change - Realistically balance the burden of daily business with change - Structure the transfer of experiences from early areas to later ones - Take the specifics of individual areas seriously instead of imposing blueprints Measure and Report Progress of the Transformation A multi-year change requires verifiable interim results instead of perceived progress. - Assess the maturity level and breadth of AI usage across areas - Prepare the value contribution of the transformation for management in a comprehensible manner - Identify misdevelopments early and initiate course corrections before they become costly Develop a Learning Organization in Dealing with AI - Establish exchange formats between areas that make experiences usable - Network internal contacts from different areas - Secure experiences made so that knowledge does not depend on individuals - Regularly review and adjust the transformation approach Upon completion, participants will be able to structure AI transformations as comprehensive initiatives, manage them across areas, and reliably present their progress to management.

Upcoming dates

• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Herzogenrath · Hybrid Learning
• 2026-10-20T22:00:00.000Z · 2026-12-22T23:00:00.000Z · Leinfelden-Echterdingen · Hybrid Learning
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Virtuelles Klassenzimmer