AI and the future of work: what changes for your company?

Selected by Dr. Sven Jungmann

Four steps through the question

1. AI makes the task easier. How should collaboration change?

   Start with a specific task. The article helps you examine individual performance and collaboration separately before turning a successful result into a staffing decision.

2. AI and early careers: how leaders can read conflicting employment evidence

   Then examine what the research can establish. Employment records, technical exposure and actual use answer different questions. Evidence from other countries needs interpretation for your own organisation.

3. AI saves ten minutes. What happens next?

   Account for the whole path to a usable result. The worked example includes review, rework and abandoned attempts. Decide explicitly what any released time should be used for.

4. Who reviews the extra work that AI prepares?

   Finally, look for the next constraint. More prepared work can create more questions and approvals. The article identifies review effort and outstanding cases that belong in the evaluation.

For your next working session

• Which specific service should improve for its recipient?
• Where do effort, waiting and rework arise before the result becomes usable?
• Which observation would contradict our assumption about the benefit?

How to use this evidence

I selected these articles as a reading route. Building aiomics brings me into daily contact with questions about reliability, working practices and purchasing decisions. The individual articles identify research, personal experience and worked examples, with links to their sources. This collection is a selection rather than a systematic review of all studies. When applying an argument, check the task, setting and outcome that were examined.