Disclaimer: The content of this article is based on the author's own independent reflections and thoughts and is not in any way associated with any company or organisation and has no commercial intent.
Looking Back to See Forward
2025 was a year of extraordinary acceleration. AI capabilities advanced faster than most organizations could absorb them. The pace of change compressed what used to take years into months, months into weeks. Everyone felt it. Everyone scrambled to keep up.
For me personally, 2025 brought recognition I didn't seek but am deeply grateful for - the Asana Work Innovation Award for Most Transformational Leader. But more than any award, this year brought clarity about something I've been building toward for two decades without fully realizing it.
This reflection isn't about celebrating achievements. It's about connecting dots that only become visible when you look back across twenty years of what seemed, at times, like a zig-zag career path that nobody - including me - fully understood.
The Twenty-Year Arc: Building Broad Line of Sight
I've spent twenty years at Danone, moving through Finance, Operations, Procurement, Project Management, Transformation, Quality, and R&I. At the time, these moves didn't follow conventional career logic. Ten years ago, even I couldn't have articulated where this path was leading.
But now, standing in 2025 at the intersection of Global Business Services and Generative AI, I understand what was actually being built: broad line of sight across multiple domains.
Finance taught me how value flows through organizations. Operations showed me how work actually gets done versus how we think it gets done. Procurement revealed the complexity of supplier ecosystems and interdependencies. Project management exposed the gap between plans and reality. Transformation taught me the human dynamics of change. Quality instilled systems thinking. R&I brought innovation methodology and the discipline of structured experimentation.
Most professionals specialize deeply in one domain. I collected lenses across six or seven.
And here's what I've come to understand: this wasn't accidental preparation - it was essential preparation. Because the future of Global Business Services - what I've been calling Generative Business Services - requires leaders who can orchestrate across all these domains simultaneously.
You can't optimize the Intelligence Triad (Human + Process + Artificial Intelligence = Amplified Intelligence) if you only understand technology. You can't implement the Virtuoso Dynamic Model (harmonizing data quality, process excellence, and technological capability) if you only understand process. You need the synthesis.
The skill I've built over these twenty years isn't expertise in any single domain. It's the ability to see patterns across domains and help others see them too. To connect the dots.
I'm profoundly grateful to have worked for a company that gave me room to shape this unconventional path. Danone allowed me to learn broadly rather than narrowly, to experiment rather than specialize, to follow curiosity across functional boundaries. That freedom created something I couldn't have designed intentionally but which turns out to be exactly what this moment requires.
Partnerships: Expanding Beyond Organizational Boundaries
The Asana award recognized something important: transformation doesn't happen in isolation. It happens through partnerships that expand your line of sight beyond your own organizational boundaries.
I've been fortunate to work with partners who didn't just provide capabilities - they provided different perspectives, different organizational contexts, different ways of seeing problems. These partnerships taught me as much as my internal Danone experience. They showed me how frameworks translate (or don't translate) across different industries, scales, and cultures.
The most valuable innovations emerge from collision of perspectives. When you bring together different domains, different organizations, different ways of thinking, you create the conditions for breakthrough insights that none of the participants could have reached alone.
This is why I'm such a strong advocate for collaborative models like GBS Condominiums - because the future belongs to organizations that can mutually amplify their collective intelligence, not those trying to build everything in isolation.
The Newsletter: Continuing the Conversation
This year I started "Connecting the Dots," a bi-weekly newsletter that's become one of my most rewarding professional activities.
The inspiration came from my own team during an event literally themed "connecting the dots." We were solving puzzles, seeing how individual pieces fit into larger systems. That experience crystallized something I'd been feeling for years: there's always more that needs to be said and discussed beyond the 20 minutes you get on a conference stage.
Conferences are valuable, but they're snapshots. The newsletter gives me space to show how one insight leads to another, how frameworks build on each other, how thinking evolves as you encounter new data. It's become my laboratory for testing ideas, seeing what resonates, understanding what questions people are actually wrestling with.
It's also been a way of walking the talk about dialogue and learning. The more paths of conversation we unlock, the faster we learn together, the faster we co-build, and the conversation naturally gravitates toward the right topics - including failures, mistakes, and lessons learned. Because success is nothing more than the lucky coincidence that a bunch of failures finally connect and work.
What 2025 Actually Taught Me
Despite all the technological acceleration, this year reinforced something fundamental: transformation is not about the technology. It's about people. And at its core, it's about trust.
During the ABSL Summit in Krakow, we surveyed GBS executives about their biggest transformation challenges. 41% identified trust - specifically stakeholder buy-in and confidence. Not technology. Not budget. Not capability. Trust.
This shouldn't surprise us, but it often does. In our rush to implement AI, optimize processes, and demonstrate ROI, we sometimes forget that transformation requires people to be vulnerable to change. And vulnerability requires the deepest kind of human assurance that won't be exploited.
Trust can't be engineered. It can't be procured. It can't be mandated. It emerges through countless micro-interactions, small promises kept, consistency over time. It's built in moments of transparency when things go wrong, not just when they go right.
I also learned that the more paths of dialogue we create, the faster we learn collectively. When we create space for honest conversation - including about failures and mistakes - we accelerate genuine understanding. This is the opposite of what most organizations do, where failure is hidden and mistakes are minimized.
The teams and organizations that thrive are those that recognize failure as essential data, not something to be ashamed of.
Looking Ahead: My Convictions for 2026 and Beyond
As we move into 2026, I'm more convinced than ever about several things:
First: Amplified Intelligence is the only sustainable path forward. Despite the hype suggesting AI will replace human work, I believe the opposite. We can already see what we can get from AI alone, and it's extraordinary. But it cannot compare to what we get from each other as humans.
The magic happens when we orchestrate Human Intelligence (wisdom, judgment, creativity) + Process Intelligence (domain knowledge, operational reality) + Artificial Intelligence (speed, scale, pattern recognition). This combination achieves outcomes impossible with any single form of intelligence alone.
The organizations trying to eliminate the human element will learn an expensive lesson. Those amplifying human capabilities through intelligent orchestration will build lasting competitive advantage.
Second: You cannot accelerate AI without data foundations. The question isn't whether data readiness matters - we already know the answer. The real question is how to accelerate data foundations at the pace this moment requires.
The traditional approach to data governance, master data management, and data quality - that took years or decades - simply won't work. We need to reimagine data readiness itself, probably using the very AI capabilities that depend on it. This seems paradoxical, but it's the only path forward.
Organizations chasing AI competitive advantage without fixing foundational data issues are about to get a very expensive, very visible lesson in what's actually broken. Because AI doesn't hide problems - it amplifies them.
Third: The current model of AI embedded in every software tool is great for providers but terrible for customers. Each vendor adds AI capabilities to their platform. Each tool becomes "intelligent." But from a customer perspective, this creates fragmented intelligence across disconnected systems.
We need to start thinking end-to-end about operations and processes. The Virtuoso Dynamic Model only works when data, process, and technology are orchestrated as an integrated system, not optimized in isolation.
Fourth: Siloes - like hedges - remain one of our biggest challenges. And here's what concerns me most: AI will make this worse before it makes it better.
As AI increasingly personalizes our preferences, experiences, and propositions, we risk becoming siloed by design. Hyper-personalization could fragment organizations and societies even more than current algorithms already do. The hedges won't just need trimming - they'll be growing algorithmically, faster than ever.
We must be extremely intentional about maintaining line of sight across boundaries while respecting the legitimate need for some separation. This is one of the most difficult leadership challenges ahead.
Fifth: We need to be ready to fail, relearn, redesign. The next year will require skills we haven't needed before - or at least not at this intensity. We'll need to forget some of what we thought we knew. We'll need to embrace uncertainty and experimentation at organizational scale.
For current professionals, this is challenging but manageable. We have mental models and frameworks to adapt.
The Father's Perspective: Worrying About What We're Building
But as a father, I find myself reflecting deeply on what all of this means for the next generation.
My children will enter a workforce where an MBA's worth of knowledge is "at the tips of our fingers" through AI. So what does education even mean in that context? What skills actually matter when information access is commoditized?
I believe the only true skill we cannot compromise in the next generation is agility - the capacity to learn, relearn, teach, forget, create, design, adapt. Not knowledge retention. Not credential accumulation. But intellectual and creative agility.
The academic pathways we've built for decades are predicated on knowledge as scarce and valuable. That world is ending. We need to reimagine education entirely - and we need to do it now, not in ten years when an entire generation has been prepared for a world that no longer exists.
This keeps me up at night more than any business transformation challenge.
The Citizen's Disappointment: What We're Still Not Solving
And then there's the broader perspective - the one that's hardest to write about but most important to acknowledge.
Despite all the technological acceleration, all the AI capabilities, all the transformation potential, we still face the same problems humanity has faced for centuries: war, poverty, famine, pollution, climate degradation. Our one and only planet still isn't in the top ten of our global priorities.
That's disappointing. That's more than disappointing - it's devastating.
And here's the hard truth: AI will only amplify our existing behaviors. If we're not solving these fundamental human challenges without AI, we're certainly not going to magically solve them with AI. In fact, we might accelerate in exactly the wrong directions.
The same technology that could help us model climate solutions could accelerate resource consumption. The same AI that could optimize food distribution could deepen inequality. The same tools that could foster human connection could fragment us further.
Technology is neutral. It amplifies what we choose to amplify.
So the question isn't "What can AI do?" The question is "What are we choosing to do with AI?"
The Hope: AI for Good
Which brings me to the one conviction that sustains my optimism: I believe we'll see more and more organizations focusing on AI for Good.
Not as PR. Not as corporate social responsibility theater. But as genuine commitment to using these extraordinary capabilities to address the challenges that actually matter.
I'm seeing it already in partnerships focused on sustainability, in applications targeting healthcare access, in projects addressing educational inequality. It's early, it's fragmented, but it's real.
The organizations that thrive in the coming decade won't just be those that optimize operational efficiency or maximize shareholder returns. They'll be those that recognize their fundamental responsibility to use transformative technology for human flourishing, not just economic growth.
This isn't naive idealism. It's strategic reality. Because the talent this era requires - the creative, agile, synthesizing minds that will actually drive innovation - those people want to work on problems that matter. They want to build something meaningful.
The companies that offer that will attract and retain the people who'll define competitive advantage in the age of Amplified Intelligence.
What I'm Taking Into 2026
So what am I carrying forward from 2025?
Gratitude for twenty years of learning across domains, for partnerships that expanded my perspective, for a company that gave me room to grow unconventionally, for a team that taught me what connecting dots actually means.
Conviction that Amplified Intelligence - the orchestration of Human, Process, and Artificial Intelligence - is the only sustainable path forward. That data readiness is the foundational work that can't be skipped. That trust remains the unmeasurable foundation of all transformation.
Concern about the world we're building - the fragmentation risks, the next generation's preparedness, humanity's continued failure to prioritize what actually matters.
Hope that enough organizations, enough leaders, enough parents, enough citizens will choose to aim AI toward what makes us more human, not less. Toward solving real problems, not just optimizing existing systems. Toward amplifying our best capabilities, not our worst tendencies.
Commitment to keep connecting the dots - to keep showing how seemingly separate insights relate to each other, how professional frameworks connect to human questions, how today's choices shape tomorrow's possibilities.
The Invitation
If you've made it this far, thank you. This reflection is longer and more personal than most of what I write professionally.
But 2025 was that kind of year - the kind that makes you step back and ask bigger questions. About your career arc. About what you're building. About what actually matters.
I'd genuinely value your perspective:
What are you carrying forward from 2025? What concerns you most about what's ahead? What gives you hope?
The conversation continues.
Because that's what connecting dots really means - recognizing that none of us has the complete picture alone. We build understanding together, one connection at a time.