Managing AI in the Organization

The course covers the use of AI in an organisational context, which includes identifying and addressing challenges when implementing AI in an organisation.

The course covers topics such as:

  • Responsible use of AI, AI ethics and alignment of AI (such as large language models) with human values and preferences.
  • Ways of identifying and dealing with bias in data and algorithms.
  • Privacy and data security issues related to collecting, processing and training AI models using large amounts of data, both from a legal perspective (GDPR, AI Act) and a technical perspective (privacy-preserving techniques, encryption methods).
  • Machine learning operations (MLOps) as a framework for operationalising machine learning models in organisations, focusing on key software engineering principles and the construction of machine learning pipelines to streamline the development and deployment of AI solutions.
  • Best practices through design patterns for building sustainable machine learning solutions to support long-term AI integration in organisations.



Teaching Format

  • The teaching activities consist of lectures, practical exercises/lessons and supervision.
  • The language of instruction is English.


Assessment

The course is examined through an on-campus written exam and assignments.

Examiner


The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.


Note that the course literature can be changed up to two months before the start of the course.


Course reports are displayed for the three most recent course instances.









Study counsellors

Margrét Håkansson and Mitra Wijkman

Visiting hoursPlease contact us via email if you want to book a meeting. We are available on Campus in Kista and via Zoom.

Phone hoursThursday 12.30–2 pm

Irregular office hoursFirst phone hours for spring 2026: Thursday 15 January