And not just because one needs to constantly learn new things, but because it is incredibly useful to periodically validate what you already know…
Many thanks to KSE for the excellent course on AI transformation. It was insightful and engaging, leaving plenty of food for thought. I particularly valued the structured approach and the ready-to-use materials—briefs, canvases, and assessment methodologies. There were many insights, but I’ll share the three I identified as central:
1. We saved thousands of hours using AI. So what?
I really liked this question. Because saved time doesn’t automatically translate into money. People simply gained an extra resource. It is then up to the business to decide what to do with that resource: increase sales, work faster, avoid hiring additional staff, improve quality, or actually cut costs. Until that happens, there is no tangible economic impact from AI.
2. Middle managers are pivotal to AI transformation.
Top executives might say, “Let’s adopt AI.” IT can provide the tools. Staff can be trained to use them. But someone has to reshape the work itself: What does the human do now versus the AI? What tasks do we stop doing altogether? What does the process look like now? What is the manager responsible for? This is where the role of the functional manager becomes critical.
3. Which leads to the next question: organizational structure.
If AI truly transforms a significant portion of the work, why should roles, functions, headcount, KPIs, and areas of responsibility remain unchanged? I’ve concluded that we talk a lot about how to integrate AI into an existing business. But we should be asking: what does the business itself need to become now that AI is part of it?
We have a lot of work ahead of us… how did you go about the AI transformation in your company?