{"id":23571,"date":"2026-09-05T18:55:51","date_gmt":"2026-09-05T16:55:51","guid":{"rendered":"https:\/\/www.flow.de\/?p=23571"},"modified":"2026-09-05T18:55:51","modified_gmt":"2026-09-05T16:55:51","slug":"flow-podcast-ai-leadership-change-management","status":"publish","type":"post","link":"https:\/\/www.flow.de\/en\/flow-podcast-ai-leadership-change-management\/","title":{"rendered":"flow podcast: AI, leadership, change management"},"content":{"rendered":"

Artificial intelligence is currently the dominant topic in businesses. Expectations are huge, as is the uncertainty. What does AI mean for leadership? Which tasks will remain the preserve of humans? And why do so many AI projects fail despite enormous investment?<\/p>\n

<\/p>\n

I discussed this (in our latest podcast, in German language) with the sociologist of work, Prof. Dr Tobias K\u00e4mpf, who has been researching the digitalisation of the world of work for almost twenty years.<\/p>\n

Surprisingly, our conversation focused very little on technology \u2013 and almost entirely on people. That is probably the most important insight.<\/p>\n

AI is not an IT project<\/h2>\n

When asked what managers should be doing now when it comes to AI, Tobias replied without hesitation: \u201cThe most important factor for success is the involvement and empowerment of ordinary employees.\u201d This is because, in many companies, the introduction of AI is still a top-down process: senior management decides, IT implements, and employees only find out late in the process what will change for them. The problem is that AI doesn\u2019t just change software; it changes work.<\/p>\n

Why so much knowledge is lost<\/h3>\n

Drawing on his interviews \u2013 for example, with call centre staff \u2013 Tobias K\u00e4mpf reported: \u201cHow can anyone come up with the idea of building a chatbot without having spoken to the people who have been on the phone with customers every day for the past ten years?\u201d This is precisely where the fallacy lies: anyone who speaks to customers or manages processes on a daily basis knows where processes break down, what exceptions arise and why some \u2018perfect\u2019 solutions never work in practice. This knowledge often determines whether a solution is accepted. That is why Tobias K\u00e4mpf does not view the introduction of AI as an IT project, but as a collaborative development process.<\/p>\n

Case study: A bank wanted to automate its mortgage lending process. Land registry extracts, notarial deeds and building plans were to be processed using AI. Simple in theory, but complex in practice: every land registry office and every notary worked differently. The solution: IT and specialist departments worked together in interdisciplinary teams. Initially, things were rather bumpy, as both sides first had to learn each other\u2019s language. Yet it was precisely this mutual learning that ultimately led to a successful outcome.<\/p>\n

The ChatGPT moment \u2013 a guerrilla innovation<\/h2>\n

The success of generative AI often seems as though it was strategically planned. But it wasn\u2019t. \u201cEmployees realised in their private lives: \u2018Wow, these tools are so useful,\u2019 and brought them into the company on their personal devices,\u201d says Tobias K\u00e4mpf. Not management, not IT \u2013 the employees themselves, often long before any official policy was in place. Tobias calls this \u2018grassroots or guerrilla innovation\u2019. Innovation doesn\u2019t arise where it\u2019s planned, but where people have the freedom to experiment. This fundamentally changes the role of leadership: away from providing answers, towards asking questions and listening. Because nobody \u2013 not even management \u2013 can know all the answers anymore.<\/p>\n

AI projects rarely fail because of the technology<\/h2>\n

\u201cWe think we can introduce the technology as if it were a plug-and-play tool, and that it will solve all our problems. That is the fatal mistake,\u201d says Tobias K\u00e4mpf. New AI does not replace poor processes, nor does it create collaboration on its own. The traditional interplay between people, technology and organisation remains crucial. Anyone who merely changes the technology will fail because of the other two factors.<\/p>\n

Change management begins much earlier<\/h3>\n

Rather than starting with training only after software development has been completed, K\u00e4mpf believes that change begins the moment people are \u2013 or are not \u2013 involved in the design process. To achieve this, managers need to provide fewer answers and create more space in which people can experiment and learn. They need a basic understanding of the technology in order to realistically assess its opportunities and limitations. More importantly, however, they must enable change rather than control it. \u201cIt\u2019s about creating spaces where people can experiment,\u201d says Tobias K\u00e4mpf. After all, nobody knows today which applications will become established. Experimentation and collaborative learning are becoming central leadership tasks.<\/p>\n

The change primarily affects the managers themselves<\/h3>\n

When it comes to change management, we usually think first of all of the employees. Yet the work of managers is also undergoing fundamental change. Decisions are prepared on the basis of data, whilst routine tasks are disappearing. Tobias K\u00e4mpf spoke of experienced engineers in the automotive industry who were suddenly expected to develop software: \u201cProfessional identities have to be redefined.\u201d This applies just as much to managers, who in future will need to focus more on facilitating, networking and providing guidance rather than simply drawing on their specialist knowledge.<\/p>\n

AI can make work more human<\/h2>\n

Instead of asking, \u201cWhich AI should we buy?\u201d, we should be asking: Where do employees waste time unnecessarily every day? Tobias K\u00e4mpf himself was sitting over his travel expense claim after a train journey and thought: \u201cIt\u2019s a shame I don\u2019t have an agent for this yet.\u201d His recommendation: \u201cYou should ask employees: \u2018Where are your pain points?\u2019\u201d Because the focus isn\u2019t on the technology, but on day-to-day work.<\/p>\n

Productivity isn\u2019t automatically a bad thing<\/h3>\n

In many companies, productivity has negative connotations, evoking images of staff cuts and pressure. Tobias K\u00e4mpf sees it differently: what matters is who benefits from productivity gains. If they merely lead to cost reductions, they won\u2019t generate any enthusiasm. If, however, they reduce routine work and create space for customers and more creative tasks, AI becomes a genuine asset. But: \u201cIt\u2019s not enough to build acceptance. We need to generate enthusiasm,\u201d says Tobias K\u00e4mpf. Acceptance means \u201call right then, so be it\u2026\u201d. Enthusiasm means \u201cGreat, that really does help us!\u201d. People get involved when they recognise a clear benefit for their own work from that involvement.<\/p>\n

We now have the opportunity to reshape work<\/h2>\n

Tobias K\u00e4mpf drew a historical parallel: the \u2018Humanisation of Work\u2019 programme of the 1970s sought to improve both production and working conditions \u2013 an idea that is more relevant today than ever. He concluded by saying: \u201cWe are in the midst of a profound transformation of work and the economy.\u201d This is comparable to industrialisation, but this time it concerns knowledge work. The difference: \u201cBecause many structures are currently in flux, they can now be changed.\u201d If companies fail to seize this opportunity, there is a risk of uncertainty and social tensions: \u201cWe must shape this positively; otherwise, social cohesion and unity in the world of work will be seriously at risk.\u201d<\/p>\n

Conclusion<\/h2>\n

The real challenge of AI is not the technology \u2013 it is leadership. Companies need fewer people who believe they know all the answers, and more leaders who ask good questions and create space for learning and active participation. The success of AI is rarely decided in the server room, but rather in the meeting room \u2013 specifically, when leaders ask: \u201cWhat would really make your work better?\u201d<\/p>\n

Best regards,<\/p>\n

Anneli Gabriel<\/strong><\/a><\/p>\n

You can also find our podcast on Spotify<\/a><\/strong> and Apple Podcasts<\/a><\/strong>.<\/p>\n

You can subscribe to our newsletter<\/a><\/strong> here.<\/p>\n

graphic: flow consulting<\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

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