As the Founder and Managing Partner of Mindgroup, I specialize in guiding private equity-backed companies through complex operational transformations. My approach transcends traditional consulting; I immerse myself in an organization’s core, aligning strategy with culture to cultivate an environment where leadership and innovation coalesce and thrive.

Throughout my career, I have had the privilege of driving operational success across various portfolios, including those within Bregal and Partners Group. I have led transformations that resulted in tangible outcomes such as 38% EBITDA savings and 67% reduction in resolution times at Compart. While these numbers are significant, it’s the lasting changes in mindset and culture that resonate most deeply with me.

During the global pause of COVID, I found the space to reassess how I lead. It became clear that sustainable transformation doesn’t come from strategy alone, it comes from understanding how deeply it’s tied to culture and human potential. Since then, this perspective has shaped my work: focused not just on delivering results, but on creating change that lasts and makes sense for the people inside the system.

I believe in the transformative power of human potential. My leadership philosophy is rooted in empathy, intentional growth, and a nuanced understanding of organizational dynamics through the lens of neuroscience. This foundation led to the creation of Mindgroup’s proprietary frameworks, including the Resistance Framework and Flow Cycle, which help organizations navigate complexity, reduce friction, and optimize decision-making. These tools are designed to align people, processes, and culture, unlocking higher levels of performance and fostering a unified force for change.

As a humanitarian, I am committed to the belief that business can drive both financial success and positive social impact. Just as nature restores the mind, I aim to create environments where transformation is both human and enduring, aligning with how we naturally think, work, and grow.

There’s a pattern I’ve seen many times inside private equity-backed software companies, and I keep thinking about it while watching the current repricing unfold.

For years, value creation in software followed a disciplined rhythm. 
Acquire recurring revenue. 
Tighten operating discipline. 
Expand margins. 
Apply leverage. 
Prepare for exit. 

The entire architecture worked because one assumption held steady: human cognitive effort inside the product and inside the organization was scarce, measurable, and defensible. Seat licenses reflected that scarcity. Billable hours reflected that scarcity. Even EBITDA improvements ultimately reflected that scarcity.

But now AI is beginning to disturb that foundation.

What interests me isn’t the volatility. Markets fluctuate all the time. What interests me is this question: if parts of cognition become cheaper, where exactly does defensibility migrate?

When Goldman Sachs estimates that 44% of legal and professional service tasks are automatable, & McKinsey & Company projects up to 30% of consulting work hours may compress over this decade, this is not a productivity headline. It is a margin headline. And in leveraged structures, margin assumptions are oxygen.

In 2025, software deal volume by financial sponsors declined around 20%, according to S&P Global Market Intelligence. Public markets erased roughly $285 billion in software valuations following incremental AI capability upgrades. Incremental. That detail matters. 

I have worked inside transformations where six people spent full time producing dashboards for ownership reporting. When AI enters that system, it compresses it. The first layer affected is volume. The second is pricing logic. The third is leverage tolerance.

This is why I find the divergence in capital behavior fascinating. 

While parts of the public market reduced exposure to perceived AI vulnerability, Blackstone reportedly increased its stake in Anthropic by roughly $1 billion. That tells you the conversation inside capital allocation committees has already moved beyond fear. It has shifted toward where margin gravity will settle next.

Private equity thrives when operating models are predictable. AI introduces variability into the cost of cognition itself. That's not an existential crisis. Consider it a structural migration. Value begins to move away from businesses monetising human effort at scale and toward those redesigning systems around cheaper cognition.

The graph below depicts this map of migration I'm trying to explain.

Portfolios built for one cost structure are being evaluated under another. The adjustment will surface through extended hold periods, tighter underwriting, credit sensitivity, and selective multiple compression.

This is early.

And in my experience, when the underlying economics of how thinking gets priced begin to shift, the surface of the market eventually follows with discipline.

The questions is... are we ready for this?

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Global Transformation Executive | B2B SaaS & Tech | AI-integrated Target Operating Model & EBITDA Delivery | PE-Backed Environments | Neuroscience-driven Leadership Advisory | Managing Partner, Mindgroup

When I was young, my mother had a simple way of helping me understand the world.

I would take all my questions to her, and she’d answer in a tone and expression I could understand. Problems were simplified. I never had to search very far or think too hard. Someone I trusted had already interpreted things for me.

As an adult, I sometimes feel AI is beginning to play a similar role.
Instead of searching through sources and forming our own interpretation, we increasingly ask a system to explain the world to us. The answer arrives instantly — clear, confident, and written in a tone that feels reassuring enough that we rarely dig much further.

Even better: we train these systems according to our preferences. The system learns how we ask questions, what tone we respond to, and what explanations feel convincing. In other words, the interpretation slowly adapts to us.

Pretty elegant.

Maybe it isn’t AI making things easier. Maybe it’s just that we were trained very early to enjoy convenient explanations. Thanks, mom. lol

The only small complication is this: every AI system reflects something behind it — training data, incentives, regulation, platform design. The response sounds authoritative, but the lens shaping it stays mostly invisible.
Which is why I notice many people now experimenting with multiple models. And I find myself doing the same — testing different “narrators” to interpret the world and deciding where to place my trust.

So I’m genuinely curious... which AI model have you found better than the rest and why? 
#Grok #Claude #CHATGPT #Gemini

There is a particular kind of pressure that comes with stepping into a transformation that is already under strain. 

I have walked into those environments more than once, and I can say honestly — it is never comfortable. There are long nights. There are difficult conversations. There are moments when you carry decisions that will not make everyone happy but are necessary for the business to stabilise. What keeps me there is not adrenaline. It is responsibility.

The words from André Holhozinskyj at Cloudflight mean a great deal to me because they reflect that invisible part of the work — the part where you fight through complexity, align stakeholders who see the world differently, rebuild operating rhythm, and create reporting discipline that leadership can actually rely on. 

Transformation sounds strategic from the outside. From the inside, it is emotional endurance, structured thinking under stress, and staying steady when programmes wobble. You simplify without cutting corners. You protect governance when shortcuts are tempting. You stay until the organisation can run independently and confidently.

The reward is never noise. It is stability. It is predictability across countries. It is a leadership team that can make decisions with clarity instead of instinct. It is walking away knowing the model holds even when you are no longer in the room.

I am currently open to complex mandates where execution ownership truly matters — restructurings, operating model redesign, ERP stabilisation, multi-entity governance environments. If you are carrying pressure inside your organisation that feels heavier than it should, I am always willing to have a direct conversation.

We are grateful for the trust expressed by André Holhozinskyj, CEO of Cloudflight, who highlights the core of our work: senior operating judgement combined with hands-on execution ownership across governance, operating model design, reporting discipline, and programme stabilisation.

In complex, multi-country environments, execution clarity protects enterprise value.

Proud to have supported Cloudflight’s leadership team in building structure, predictability, and a model that can run independently.

Germany is entering a moment of real economic pressure.

After years of political debate around energy policy, regulation, and the future of the country’s industrial base, the question of competitiveness has returned to the center of the discussion. Businesses, especially the german growth machine, Mittelstand, feel that parts of Europe’s largest economy have slowly been drifting toward de-industrialisation, and the new government is under immense pressure to implement long-overdue reforms aimed at restoring confidence and fostering growth across Europe, particularly within the German economy.

But Germany’s situation is not unfolding in isolation.

Wars are reshaping geopolitical alliances. Trade relationships are fragmenting. Across Europe and the US, debates around sovereignty, technological leadership, and economic resilience are becoming more intense. And in parallel, artificial intelligence is quietly moving from experimentation into the operating infrastructure of entire industries.

Technology accelerates.
Politics recalibrates.
Organisations try to maintain coherence somewhere in between.

In many boardrooms the question is no longer whether AI will change how companies operate. That debate has largely ended. The more interesting question now is how institutions adapt when the world around them begins to move faster than the systems inside them were designed to handle.

This is one of the reasons why gatherings like Unternehmertag feel particularly relevant right now.

Its a true privilege to attend this format as I’m keen of hearing perspectives such as Karl Nehammer speaking about “Capital, Power and Stability: Financing the Next Global Order,” as well as insights from entrepreneurs like Nikolas Bullwinkel who are building AI-driven automation businesses.

Equally curious to hear voices such as Christian Underwood discussing how AI is compressing the distance between strategy and execution, and Benjamin Bargetzi exploring the intersection between artificial intelligence and the human brain — something that will likely become central to leadership in the years ahead.

And I'm particularly interested in hearing what Bayer CEO Bill Anderson has to say on "Leading Through Change: Building Resilient Teams." This topic is highly relevant to my daily work, making it a "sweet spot" for me. His insights on transforming an industry icon with such a significant post-war history are reason enough to attend.

So I’m curious to learn how leaders think about execution and resilience when geopolitics, technology, and economic pressure are all accelerating at the same time?

After years working inside transformation programmes across complex organisations, one pattern keeps repeating. The bottleneck is hardly ever the technology. It is the human system around it.

#Unternehmertag2026 #TheGreatReShuffle #Innovation #Leadership #TechTrends #Entrepreneurship

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