AI is great for speeding up and assisting with many of your work tasks.
However, AI cannot help with the changes around that work: how customers react, how their behaviour shifts and the new questions they ask, or how colleagues might require different knowledge or data from you.
With all the coverage of AI, you can hardly see the wood for the trees any more. With my experience I have by now developed a Fingerspitzengefühl for seeing what is relevant and what is distraction, and I can not only provide clarity, I can also develop it. The goal is to deploy AI in the organisation and among its employees in such a way that everyone comes into their own more, taking privacy and sustainability into account.
AI was developed on a foundation of surveillance. When integrating AI into existing business software, it is crucial to ensure that organisational data does not leak externally; “Shadow AI” is a well-known example of this risk. Various privacy-preserving techniques have since been developed.
AI is inherently highly inefficient, which is why it consumes so much energy. When is it actually necessary to deploy an AI agent within a workflow? Often, the task can be accomplished just as well using a standard script (even one generated by AI).
Read about the AI Footprint Meter