The Growth Map is Being Redrawn

For decades, the growth journey of a company was predictable. You started with an idea, you survived the chaos of early traction, and then you scaled. The path had names, names we still use: the Startup phase, the Rollercoaster, the Management phase, Scale-Up, Flow.

More employees meant more capacity. More revenue meant more stability. Going international meant you had made it. Growth was a ladder, and the rungs were clear.

The map was imperfect. But it existed.

We built our methodology around that map. We helped hundreds of entrepreneurs understand which phase they were in and what it would take to move to the next one. And it worked, because the rules of the game, while hard, were at least legible.

“Growth used to be predictable. You knew where you stood. You knew what came next.”

Something changed.

We see it across every market we operate in: Italy, Turkey, Bulgaria, Denmark, the Netherlands. And what we hear, consistently, from the founders and leadership teams in our ScaleUp Sessions is no longer “how do we grow?”

It is: “Where do we still fit?”

Companies that spent years building a clear value proposition (in IT services, marketing, legal, finance, consultancy) are finding that the ground beneath them has shifted. Their clients are more self-sufficient than ever. The tools that used to require a specialist now require a prompt. The junior workforce that executed delivery is being replaced not by cheaper humans, but by software that doesn’t sleep.

Take a company that built its business around HubSpot or Salesforce implementation. On one side, those platforms are rebuilding their own service models, reducing the need for external partners. On the other side, the end clients are deploying agents to handle what implementation firms used to do. The business is being compressed from both ends simultaneously.

This is not a technology story unique to software. It is happening in legal services, in marketing, in finance. The compression is everywhere. The question of relevance is universal.

According to the 2025 Wharton Human-AI Research and GBK Collective AI Adoption Report (co-authored by Stefano Puntoni, Faculty Co-Director of Wharton Human-AI Research), 82% of enterprise leaders now use generative AI at least weekly, with 46% using it daily. That is a 17 percentage point jump in a single year. This is not a future trend. It is the present reality of your clients’ clients.

Relevance is the new growth.

Here is where it gets interesting, and where we see the companies that are thriving diverge sharply from those that are struggling.

Most businesses today are asking a reasonable question: “How can we use AI to do what we already do, faster, cheaper, better?” It is a sensible starting point. It yields marginal improvements. Teams work more efficiently, documents get drafted faster, reporting becomes cleaner.

Stefano Puntoni, in his broader body of work on AI and business strategy, draws a distinction that we find essential. The companies that will define the next decade are not asking how to apply technology to existing models for incremental gain. They are asking something fundamentally different: “What can we now do that we could not do before?”

Not optimisation. Reimagination.

The Wharton report supports this. Among the most forward-leaning enterprises surveyed, roughly one-third of their AI technology budgets are being allocated to internal R&D, building custom capabilities that did not exist before, not just licensing tools to accelerate what they were already doing.

The difference is not about budget. It is about the question being asked in the boardroom.

Are you asking: “How do we fit this technology into our business?” Or are you asking: “What kind of business could we build now that this technology exists?”

The first question produces a better version of what you had. The second question produces something new.

“Don’t fit the technology to the business. Fit the business to what the technology now makes possible.”

Our growth methodology (the phases, the frameworks, the structure) is not obsolete. If anything, it is more critical now than it was when the path was predictable.

But we have had to confront something honest: the phases no longer move in one direction. Instead, they move in cycles.

A company in the Management phase (structured, with a leadership team in place, clear KPIs, a functioning heartbeat) can find its entire value proposition disrupted overnight by a shift in how clients use AI. Suddenly, that company does not need a management mindset. It needs a founder’s mindset. It needs to question everything, start fresh in parts, and rebuild its reason for existing.

The warrior mode and the architect mode (the scrappy, instinct-driven builder and the disciplined, systems-driven operator) are no longer sequential stages in a career. They are modes a leadership team must be able to move between, sometimes in the same quarter.

Some of our clients are in what looks like a Scale-Up phase by the numbers. Revenue is there. Team is in place. But the product or service they built that business on is being challenged at its core. They need startup thinking inside a scaled organisation. That is a deeply uncomfortable combination. And it requires a very specific kind of support.

What we offer is not a ladder anymore. It is a framework that lets companies move at the speed this world demands, without losing their footing.

It would be incomplete to write about the AI-driven transformation of business without acknowledging what the data and our own experience make clear: this is genuinely hard.

The 2025 Wharton report is striking in its honesty on this point. Despite nearly half of organisations reporting critical technical skill gaps, investment in training has actually softened, and confidence in training as the path to building AI fluency is down 14 percentage points year over year.

There is a paradox at the heart of this moment: 89% of business leaders surveyed believe generative AI enhances their employees’ skills. And yet, 43% of those same leaders warn of skill atrophy from over-reliance. Organisations are gaining capability and losing depth at the same time.

The report identifies the real bottleneck clearly: it is not the technology. It is the people, the culture, and the leadership alignment. Morale. Change management. Cross-functional coordination. These are the persistent barriers. And they are exactly the terrain where companies without structure, clarity, and accountability frameworks break down.

Beyond the human side, the practical challenges are real: the reliability of AI systems, quality control, cost, and data privacy, especially for companies operating across multiple countries and regulatory environments. None of these are reasons to slow down. But they are reasons to build the right scaffolding before you sprint.

“Technology is the easy part. People, culture, and leadership alignment are where companies stall.”

We used to open every engagement with the same question: “What phase of growth are you in?”

It was the right question for a predictable world. Today, we ask something harder.

“Is your business designed for the world that exists right now, or for the world you built it for?”

The goal has not changed. We still work with entrepreneurs who want to build companies that outlast them, teams that run without them, and value that compounds over time. The BHAG is still the BHAG.

But the path to get there is no longer straight. It requires the ability to move between phases with intention, to have the structure of the architect and the fire of the warrior available at the same time. It requires asking not just how to grow, but what growth even means now that the rules have changed.

The map is being redrawn. The question is who’s drawing it, and whether your business is ready to navigate it.

“Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise.” Wharton Human-AI Research & GBK Collective, October 2025. Authors: Jeremy Korst, Stefano Puntoni (Sebastian S. Kresge Professor of Marketing, The Wharton School), Prasanna Tambe.

Stefano Puntoni, Faculty Co-Director of Wharton Human-AI Research, research and public commentary on AI strategy and business transformation.