Finding Ground: Identity and Values in 2025

Posted on by Patrick Sauerwein

2025 was another year of intense learning. It challenged how I view collaboration, my European and German identity, and the fragile foundation upon which our digital society is built.

The Culture Map Moment

It happened during our Commerce offsite. We sat together as a team, filling out the Culture Map framework, plotting our communication styles, decision-making approaches, and feedback preferences across Erin Meyer’s eight dimensions. Then we shared our results.

That’s when it clicked.

Generated with Claude AI

I finally understood why I felt this deep need to involve the team in every decision, to provide as much context as possible, to ensure everyone understood the “why” behind our choices. And I understood why my Greek counterpart looked at me with a mixture of confusion and polite bewilderment when I asked for his input, for him, it was crystal clear that decisions came from him and me, not from the collective.

We received The Culture Map as a gift that day. I’ll admit, I haven’t finished reading it yet. For anyone working in international contexts, this book is highly recommended. It is a true survival guide for navigating cultural unspoken rules that shape how we work together.

But the Culture Map did more than help me understand my colleagues. It made me realize how much I value where I come from.

Identity in a Fracturing World

My identity became more important to me this year. The international political tensions, the behavior of tech billionaires and their growing influence, the way algorithms shape public discourse especially on social media, all of it made me realize that Europe and Germany can no longer afford to look away.

We can’t keep depending on partners who pursue their own interests first, sometimes at our expense. We’ve seen how technology no longer serves the common good but increasingly serves specific countries and interest groups whose goals run counter to ours. Democracy itself is under pressure as media algorithms distort perceptions and thoughts dramatically. The very tools we use daily (social platforms, search engines, recommendation systems) are actively shaping political outcomes in ways we’re only beginning to understand.

„Whoever controls the media, controls the mind.“ – Jim Morrison

The parallels to security policy are impossible to ignore. Just as NATO has depended on others especially the US for military defense, we’ve built our entire digital infrastructure on foundations controlled by others. And the numbers tell a stark story.

The Digital Sovereignty Gap

When you look at AI computing capacity globally, the distribution is sobering:

  • USA: 74-75% of global AI supercomputing power
  • Europe: 4.8-6%
  • That’s a 15:1 disadvantage

For traditional data centers, the gap is somewhat smaller but still dramatic:

  • USA: 40-44% of global capacity
  • Asia-Pacific: 26-30%
  • Europe: 11-12%
  • Germany: 2-3%, despite leading Europe with 529 data centers

But here’s where it gets truly concerning, when you examine the complete technology stack, Europe’s dependency becomes existential:

Hardware Manufacturing: Europe produces less than 1% of global smartphones, PCs, and servers. China and Asia control 65%+ of manufacturing. We import virtually all our computing hardware.

Operating Systems: Europe’s market share for operating systems is 0%. Zero. Every desktop runs Windows (72%) or macOS (15%), both American. Every smartphone runs Android or iOS, both American, although Android is open source but inhouse development at Google increasing. A complete duopoly with no European alternative.

Software and Applications: North America holds 41-45% of the software market, Europe 20-25%. While we have some presence with companies like SAP, the platform layer (the infrastructure on which everything else runs) is overwhelmingly American.

This isn’t just about technology. Data sovereignty without compute sovereignty is an illusion. Digital independence without control over the full stack, from hardware to operating systems to cloud infrastructure, is impossible. We’ve built our entire digital society on a foundation we don’t control, in a geopolitical environment that’s increasingly unstable.

The problems this creates are as fundamental as those in security policy. We’re completely dependent on others and well-intentioned trading relationships. When those relationships become strained, our vulnerabilities are exposed. That’s why digital independence isn’t just nice to have, it’s strategically essential.

Big Tech

A podcast dialogue between media scientist Martin Andree and sustainability expert Maja Göpel deepened my understanding of this crisis. Martin’s research reveals an alarming concentration:

Germany’s web traffic has a Gini coefficient of 0.98, indicating near total monopoly.

Think about that. A handful of platforms control virtually all digital discourse.

These platforms operate under what Martin calls a “privilege of non liability.” They monetize polarizing and illegal content without facing the legal consequences traditional media outlets do. Meanwhile, they’re not just business interests, they’re ideological projects.

Many tech leaders are influenced by radical libertarian thinking, particularly “The Sovereign Individual,” a 1997 manifesto championed by figures like Peter Thiel and Elon Musk. This book envisions a post democratic era where a “cognitive elite” uses technology to escape democratic oversight entirely. Democratic states aren’t partners in this vision, they’re obstacles to be overcome.

Martin proposes a structural response, a “re opening” of digital markets through four key interventions:

  • Interoperability: Users must freely move data and followers between platforms, just like email works across providers.
  • Outlink Freedom: Platforms can’t trap users in walled gardens. Creators need the right to direct traffic to independent domains.
  • End Self Preferencing: Search engines and app stores must stop prioritizing their own services over competitors.
  • Democratic Oversight: Algorithm governance and content moderation should be handled by user led boards, not individual billionaires.

The bottom line, as Martin argues: Big Tech’s dominance isn’t the result of superior innovation only. Legal privileges granted by society play a vivid role.

Who Controls AI? The Economics of Power

But there’s another dimension to this sovereignty question that often gets overlooked: the economics of AI itself. Who pays for it? Who profits from it? And critically, who decides how it’s used?

The economic debate centers on two competing uses of AI: cost reduction versus revenue growth. McKinsey’s 2025 research shows that roughly 80% of organizations initially focus on efficiency, automating existing processes to cut costs. It’s the easier path. But high performing companies use AI for innovation and new revenue streams. The data tells the story: while 40% of AI gains come from cost savings, 35% come from new revenue and 25% from faster innovation cycles.

Goldman Sachs projects that widespread AI adoption could raise global GDP by 7% over the next decade, roughly $7 trillion in additional economic output. US labor productivity could increase by 1.5 percentage points annually. These aren’t marginal gains, they’re transformative. But here’s the critical question: transformative for whom?

The current trajectory suggests AI will primarily benefit those who control the infrastructure. The USA, with 74-75% of AI computing capacity, is positioned to capture the lion’s share of this economic value.

Europe, with just 4.8-6% of capacity, is becoming a consumer market for AI services rather than a producer.

Consider what this means for Germany and Europe specifically. We’re not just behind in infrastructure, we’re behind in the entire value chain. We don’t manufacture the hardware. We don’t control the operating systems. We have minimal cloud capacity. And now we’re watching AI, the next platform shift, being built on foundations we don’t own.

The investment numbers make this stark. The USA invested $109 billion in private AI funding in 2025. Europe invested $8 billion, a 14:1 disadvantage. This isn’t just about current capability, it’s about who shapes the future. Every dollar invested today determines who builds the models, who trains them, who decides what they optimize for, and who captures the economic returns.

Stanford’s 2025 AI Index reports that 83% of businesses now prioritize AI programs. But McKinsey found that only 26% have built the skills to scale AI beyond pilots. There’s a massive competency gap, and it’s not just technical. It’s strategic, organizational, and cultural.

For Europe and Germany, this creates both a challenge and an opportunity.
The challenge: we’re structurally disadvantaged in the AI race by nearly every measure.
The opportunity: AI adoption is still in its early stages, and the real economic impact won’t materialize until 2027-2030 according to Goldman Sachs. We have a narrow window to build capacity, develop skills, and establish sovereignty.

And that window is closing. Every year of underinvestment compounds. Every data center not built in Europe is another dependency on foreign infrastructure. Every AI model trained on US servers is another decision made without European input. Every use case deployed by American platforms is another economic opportunity captured elsewhere.

The question isn’t whether AI will transform the economy. The question is whether we’ll be active participants shaping that transformation or passive consumers of technologies and business models built by others, for others’ priorities.

Thinking Global, Acting Local

So what can I do? Meeting people, where they are. Locally. Meaningfully.

That’s one of the reasons I decided to engage as a co-organizer at ProductTank Frankfurt. Working alongside Steffen and Marisa to organize our local product management community has been one of the most meaningful things I’ve done this year. I’m deeply grateful to both of them for the opportunity to contribute. Read more about it here: ProductTank Frankfurt Rhein-Main: 2025 Year in Review

It’s a small contribution in the larger scheme of things. And it’s something tangible: bringing together product people in my region, sharing knowledge, building competence, strengthening our local tech ecosystem one meetup at a time. Having skilled people who shape, learn from each other, connect and understand product management, technology strategy, and how to build things that matter.

It is a form of competence that grows in local communities like ours and it is my form of individual contribution.

Language, Identity, and Authenticity

I’ve also been thinking a lot about my language this year, specifically, about writing more in German. My identity matters to me. My roots matter. And language is a fundamental part of that identity.

There’s always been this tension: write in English to reach a global audience, or write in German to speak authentically to a German speaking community. For years, I defaulted to English. The international reach felt more important.

But is this still true after 2025? Is there a tipping point where authenticity becomes more valuable and language becomes more important to raise awareness within my community?

I’m still struggling to find the right balance. I sense the urge to write more in German. Not to exclude others, but to include my voice in the place and culture I come from.

What This Means Going Forward

2025 was another year of intense learning. The Culture Map showed me how I work and why. The geopolitical shifts showed me what’s at stake. The data showed me how far behind we are. And my work with ProductTank Frankfurt showed me that local action still matters and I’m able to contribute, where I live and am.

The challenge ahead is massive. Europe needs to build digital sovereignty across the entire stack, hardware, operating systems, cloud infrastructure, AI computing power. That’s a generational project requiring investments, political will, and strategic thinking we haven’t shown yet.

And it starts with awareness. With not looking away. With understanding what we’ve built on and what we’ve given up.

And it continues with action, even small, local actions. Building competence. Strengthening communities. Writing authentically. Contributing where you are.

Because it’s about people who understand what’s happening, who have the skills to build alternatives, and who care enough to try.

That’s what 2025 taught me. That’s what I’m taking into 2026.

What’s your take on this post? Different views? What are your learnings in 2025? I’d love to hear your thoughts.

Sources & References

The data and statistics in this article are drawn from the following sources:

AI Computing Capacity & Supercomputers:

Data Center Infrastructure & Energy:

  • International Energy Agency (IEA, April 2025): “Energy and AI” Report – Comprehensive analysis of global data center energy consumption
  • IEA (2025): “Energy Demand from AI” – Detailed demand projections through 2030
  • Visual Capitalist (2025): Data center capacity mapping
  • CBRE & Bain & Company (2025): Market analysis and growth forecasts

Hardware & Operating Systems:

Software, Cloud Computing & Investment:

AI Economics & Productivity Research:

Germany’s Digital Monopoly Data:

  • Gini coefficient of 0.98 for web traffic concentration (Martin Andree research, University of Cologne)

Note: The data landscape is constantly evolving. These figures represent the best available estimates as of late 2025. Epoch AI’s dataset covers approximately 10-20% of global AI computing capacity, with actual capacity (particularly in China and classified US systems) likely higher than publicly reported.

The sources and data in this article were researched and compiled with the assistance of AI based on my research prompts and questions.

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