{"id":23692,"date":"2026-10-11T09:20:02","date_gmt":"2026-10-11T07:20:02","guid":{"rendered":"https:\/\/www.flow.de\/?p=23692"},"modified":"2026-10-26T09:22:45","modified_gmt":"2026-10-26T08:22:45","slug":"ai-hr-and-leadership","status":"publish","type":"post","link":"https:\/\/www.flow.de\/en\/ai-hr-and-leadership\/","title":{"rendered":"AI, HR and Leadership"},"content":{"rendered":"
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Automated, but Not Transformed?<\/strong><\/h2>\n

What We Learned in Halle About AI, HR and Leadership<\/strong><\/h3>\n

Once a year, we at flow make a conscious decision to take some time out for ourselves. No client meetings, no seminars to run \u2013 just a few days when we consultants get to be the learners for a change.<\/p>\n

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This summer, our annual workshop took us to Halle (Saale), a city that has more to offer than you might expect: a rich history, plenty of green spaces and a lively university scene. Just the right place to reflect on the future of work.<\/p>\n

At the heart of our discussions was a question that comes up in almost every client project: what is AI changing in HR, and what does it mean for leadership? To explore this, we invited two guests who have been researching and working with these questions for years: Dr Christian Ho\u00dfbach and Christopher M\u00fcllner, MSc, from the Chair of Human Resource Management and Business Governance at Martin Luther University Halle-Wittenberg and the AI-HR-Lab<\/a><\/strong>. Their session was entitled \u201cAutomated, but Not Transformed? Three Years of AI in HR Under the Microscope\u201d<\/em>. It gave us plenty to think about long after the workshop had ended.<\/p>\n

The key insight: automation is not transformation<\/h2>\n

The AI-HR-Lab has been exploring how AI is changing HR since 2018. The session was therefore firmly rooted in practical experience. One finding stood out: many AI tools in HR simply automate existing processes. They digitise the old ways of working without changing how people think. Genuine transformation only happens when organisations look beyond the technology to consider culture and roles as well.<\/p>\n

We also worked with specially designed personas and discussed practical examples. One concerned meeting recordings: when employees know that meetings are being recorded, they tend to think more carefully about what they say. At the same time, recordings make it easier to produce meeting minutes. Whether AI tools are accepted and prove effective depends to a large extent on the level of psychological safety within the team.<\/p>\n

Technology alone, then, is rarely the deciding factor. This was the point at which we at flow took the discussion a step further.<\/p>\n

Our perspective: leadership shapes the connections<\/h2>\n

In our work with leaders, we use an established framework built around three elements: people, technology and organisation. The MTO approach has its roots in the socio-technical systems research of Emery and Trist and was further developed by Strohm and Ulich at ETH Zurich.<\/p>\n

Our perspective is a little different, though. Rather than focusing on the three elements themselves, we pay particular attention to the connections between them. After all, it is where people, technology and organisation meet that determines whether AI works in practice.<\/p>\n

The people\u2013technology interface.<\/strong> This is about how people work directly with AI tools. The key is to ensure that theydo not outsource their thinking to AI. Instead, as most of our clients prefer, they should use it as a sparring partner \u2013 a way to test ideas, challenge assumptions and explore different perspectives. Otherwise, it is all too easy to end up with results that look convincing but lack substance. This is not an argument against AI, but a case for developing thoughtful, deliberate ways of using it.<\/p>\n

The technology\u2013organisation interface.<\/strong> This is where processes, structures and responsibilities come into play. A feeling of being in control is no substitute for proper checks. There is also an important regulatory consideration: as of 2 August 2026, most provisions of the EU AI Act have become applicable, including obligations relating to high-risk AI systems. These can include AI applications used in recruitment and selection.<\/p>\n

The organisation\u2013people interface.<\/strong> This is about involvement, culture and trust. The key question is not, \u201cWhere can we introduce AI?\u201d but rather, \u201cWhat role should AI actually play in the way we work together?\u201d Teams that take the time toagree on this are better placed to shape how AI is used \u2013 and where it should not be used.<\/p>\n

One team, three interfaces: what this looks like in practice<\/h2>\n

Imagine an eight-person sales support team. This is a fictional example, but one that may sound familiar. Several team members have started using AI on their own initiative to prepare quotations and draft correspondence with customers. The quotations are ready more quickly, but they need more revisions: the wording is polished, yet the content often feels generic.<\/p>\n

Looking at the situation through the three interfaces turns a vague sense of unease into something tangible. At the people\u2013technology interface, the team lacks a shared understanding of what the tool is actually good for. At the technology\u2013organisation interface, it is unclear who should check the content before it goes out. And at the organisation\u2013people interface, what is needed is genuine involvement rather than instructions handed down from above.<\/p>\n

The result is three small, targeted measures rather than one major programme. We will show you what they are in our webinar.<\/p>\n

Leadership shapes the impact<\/h2>\n

During our summer workshop in Halle, we spent a long time discussing what is genuinely new about leadership in the age of AI. Our answer? Surprisingly little.<\/p>\n

Long before the current AI hype, Frankiewicz and Chamorro-Premuzic made the point succinctly in Harvard Business Review: \u201cDigital Transformation Is About Talent, Not Technology.\u201d Or, as we would put it: technology changes the tools. Leadership shapes the impact.<\/p>\n

The fundamentals still apply:<\/p>\n