AI Operations Manager

Course overview

This training course covers the responsibilities of an AI Operations Manager: organizing the ongoing operation of productive AI applications, monitoring their quality, and structuring their further development. The focus is on responsibilities, review routines, and maintenance processes for AI solutions in everyday work. Organizing ongoing operations Responsibility for AI does not end with the launch; it begins there. - Clarify and document responsibilities for support, maintenance, and further development - Establish and publicize points of contact for user questions and issues - Regulate collaboration between departments, IT, and data protection in operations Monitoring quality and usage Without measurement points, any statement about quality is just a gut feeling. - Define and regularly report key figures for usage, benefits, and outcome quality - Establish sampling and review routines for AI outputs - Early detection of deviations, error accumulations, and quality loss - Systematically collect and evaluate feedback from everyday use instead of reacting to requests Maintaining prompts, workflows, and knowledge bases AI applications gradually become outdated if no one keeps them current. - Regularly review and adjust prompt templates and workflows - Keep stored documents and knowledge sources current and consistent - Document and communicate changes in a traceable manner Managing disruptions and risks - Establish procedures for dealing with faulty or unexpected AI outputs, including corrections and informing affected parties - Define and practice escalation paths for critical cases - Implement requirements from the EU AI Act and GDPR in ongoing operations Organizing further development - Prioritize improvement ideas from usage and feedback and translate them into a realistic roadmap - Introduce adjustments in a controlled manner and verify their impact Supporting users in operations Satisfied users are the best indicator of a healthy operation. - Structure the onboarding of new users and accompany it with short learning offerings - Keep quick guides and answers to frequently asked questions up to date - Establish regular Q&A sessions and exchange formats to make problems visible early - Involve experienced users as everyday supporters This course teaches how to operate, monitor, and structure the further development of productive AI applications after their launch.

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
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-11-03T23:00:00.000Z · 2027-07-03T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-11-17T23:00:00.000Z · 2027-01-19T23:00:00.000Z · Virtuelles Klassenzimmer