Chief AI Officer

Online live seminar (4 teaching units) + self-study (2 teaching units)

Role and mandate of the Chief AI Officer

• Tasks, decision-making rights, and responsibilities of the Chief AI Officer.
• Collaboration with management, IT, business units, legal, and data protection.
• Connection to the operational role as an AI Officer.
• AI Maturity: Data, Processes, Competencies, and Initial Situation.

AI basics, agents, and fields of application

• Analytical and generative AI, language models and their limitations.
• Assistants, AI agents, and automation in the enterprise context.
• Practical examples of data quality, errors, and human oversight.
• Identify suitable areas of application and initial action requirements.

Learning outcome: You can describe the CAIO mandate and realistically assess AI potentials.

Online live seminar (4 teaching units) + self-study (2 teaching units)

AI Strategy and Use Cases

• Derive AI target vision from corporate strategy and customer needs.
• Identify use cases along the value chain.
• Prioritize utility, feasibility, data availability, and risks.
• Develop a manageable portfolio with clear responsibilities.

Business cases and investments

• Evaluate benefit assumptions, total costs, and uncertainties.
• Classify in-house development, acquisition, and vendor dependencies.
• Define budget, resources, and success criteria.
• Prepare decision papers for piloting, continuation, or termination.

Learning outcome: You can justify AI investments and set strategic priorities.

Online live seminar (4 teaching units) + self-study (2 teaching units)

EU AI Act and legal classification

• Scope of application, roles of providers and operators, and risk classification.
• Prohibited practices, high-risk applications, and transparency requirements.
• Relevant duties, documentation, and human supervision based on case studies.
• Interfaces with data protection, copyright, confidentiality and employment law.
• Recognize the need for legal review and involve the relevant departments.

AI Governance and AI Officer(s)

• AI inventory, internal policies, and comprehensible release processes.
• Tasks, responsibilities, and escalation paths for AI officers.
• Organizing AI expertise in the company and identifying training needs.
• Collaboration with data protection, information security and legal advice.
• Review provider information and document relevant evidence.

Learning outcome: They can systematically align with legal requirements and shape operational AI governance.

Online live seminar (4 teaching units) + self-study (2 teaching units)

Risk analysis and risk assessment

• Identify fault scenarios, affected persons, and possible damage.
• Evaluate the probability of entry and the extent of damage in a comprehensible manner.
• Legal risk classification and operational risk assessment are different.
• Consider data protection, security, discrimination and quality risks.
• Document protection measures, human controls, residual risks, and approval criteria.

Implementation and sustainable control

• From pilot project to operation: tests, responsibilities, and ongoing monitoring.
• Employees are involved, communicate changes, and build competencies.
• Organize incidents, escalations, and changes to AI systems.
• Develop an implementation roadmap with milestones and resources.
• Review benefits, usage, quality, and risks using appropriate metrics.

Learning outcome: You can accompany AI projects with a sense of risk and control their implementation in a measurable way.

Homework: Your AI strategy for practice

Independent study (15 ECTS), in addition to self-study.

They develop a business-oriented AI strategy with a concrete use case. The project combines strategic decisions with the operational tasks as an AI practitioner.

• Background, target image and prioritized use cases.
• Business case with benefits, costs, and success criteria.
• Classification of the EU AI Act and relevant legal issues.
• Documented risk analysis and assessment, including protective measures and residual risks.
• Governance, responsibilities, competence building and implementation roadmap.

The written work summarizes the results from the four course modules. Requirements, submission, and assessment are explained at the beginning of the course.

Diploma and Certificate

In the additional final term, you reflect on the key findings and next steps for practice. Subsequently, the certificate will be awarded. A presentation of the assignment is not planned.

Certificate: Chief AI Officer

University course in cooperation with the Whitecliffe University of Applied Sciences in Berlin, including qualification as an AI officer.

Sie erhalten das Hochschulzertifikat „Chief AI Officer“ einschließlich der Qualifizierung als KI-Beauftragte:r in Kooperation mit der Whitecliffe University of Applied Sciences in Berlin.

Die eigenständige Hausarbeit umfasst 15 UE. Im zusätzlichen Abschlusstermin reflektieren Sie Erkenntnisse und nächste Schritte. Eine Präsentation der Hausarbeit ist nicht vorgesehen.

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