Horizontal AI is a foundation, but only vertical, industry-specific AI creates sustainable competitive advantage. Combining the two is key.
AI in business today operates at two distinct levels. Horizontal AI addresses common business processes in a broad way: it is useful, scalable and increasingly standardized. Vertical AI goes further. It resolves complex issues specific to a sector of activity by integrating business expertise, proprietary data and key processes. It’s understanding the distinction between the two that makes the difference between marginal efficiency gains and true competitive advantage.
For years, executives have viewed AI as a silver bullet. Deploy a digital assistant here, a co-pilot there, and the magic will happen. Except that magic doesn’t happen, at least not on the scale that businesses need. Horizontal solutions are easy to implement, which is precisely why they are quickly becoming a commodity. And when everyone has the same tools, no one benefits from a sustainable competitive advantage!
Here’s what I’m seeing from our customers: Companies that are getting ahead of the curve today aren’t abandoning horizontal AI. They build on top of it. They stopped considering widespread deployment as an end goal and began to design vertical AI systems capable of profoundly transforming the way they operate. The horizontal constitutes the foundation. The vertical is where competitive advantage is created.
The paradox of complexity
There is a paradox here that many organizations have not yet fully understood. Horizontal AI is simple to deploy, but its value remains limited when used alone. Vertical AI is more complex to implement, but it truly transforms business bottom lines. And most organizations get stuck at the first level without ever getting past the second.
Let’s take an example. A generic digital assistant can save a customer service team a few hours per week. It’s useful, real, and a necessary starting point. But it does not, in itself, constitute a transformation. Compare this to an AI system specifically designed for your industry, integrated into your critical processes and powered by your proprietary data and business expertise. It’s no longer an assistant: it’s real business process re-engineering! These two approaches are not opposed; they reinforce each other.
The difference is not theoretical. In our workshops across Europe, I’ve seen organizations that have added vertical AI capabilities to their horizontal foundations achieve productivity gains of 15-20% or more, not on an isolated function but on entire processes! The horizontal layer created the common base; the vertical layer generated the change in scale.
Why vertical AI changes everything
Vertical AI multiplies the value of what horizontal AI has already implemented. It provides something that general solutions cannot offer alone: understanding your business. She knows your processes, your constraints, your regulatory requirements and your growth drivers. It does not seek to meet all the needs of all businesses; it is designed specifically for your issues, drawing on the platforms and tools that your teams already use.
This is where the ecosystem model comes into play. The cloud infrastructure sector followed the same evolution: hyperscalers provided the foundations, specialist players developed value-added solutions, and integrators orchestrated it all. Enterprise AI today follows exactly the same logic. Rather than spending months evaluating generic solutions, organizations can now identify, test and deploy specialized agents tailored to their industry, working on top of existing systems, in just days.
The most significant recent development is that enterprise platforms themselves now offer coordinated teams of specialized agents, designed to achieve specific objectives such as debt collection, workforce planning or supplier sourcing, rather than letting organizations add AI at the edge of their existing systems.
It is no longer a vision of the future: it is an operational reality. We are already seeing integrators and independent software vendors (ISVs) offering proven vertical AI solutions in the areas of finance, human resources, supply chain and even customer experience. These are not generic tools replacing existing functionalities, but intelligent agents designed to respond to specific sectoral and business challenges, while reinforcing the value of the platforms already deployed.
The real risk: stopping at the first level
What worries me more than anything else are organizations that are complacent with their horizontal AI deployments and view them as an end in themselves. They have checked the “AI” box by deploying it and can talk about it during their financial presentations; but they have not understood the real turning point in which we find ourselves.
It used to be that having a competitive advantage in AI meant having access to the best talent or the biggest budgets. Today, that is no longer enough. The advantage lies in the ability to move beyond standardized solutions and the discipline necessary to invest in vertical capabilities that generate concrete business impact. Organizations that act now are building a truly defensible structural advantage.
Conversely, those who consider horizontal deployment as an end goal are already starting to see that the benefits remain limited. They then question the reasons why certain competitors display radically different economic performances even though they started from the same starting point.
The way forward
The message is not to abandon horizontal AI; it is to sequence investments correctly!
Start by leveraging the AI capabilities already built into your systems. Use them to improve efficiency, build trust, and build the data foundations you’ll need.
Then quickly follow up with vertical AI projects targeting your most strategic and complex business processes.
Precisely identify the processes that have the most impact on your financial performance. Develop, or partner with partners who can, AI systems specifically designed for these processes. Measure results rigorously. Then scale up what works.
The companies that are taking a head start today are not those that are launching the most AI projects. These are the ones that take the more disciplined approach to the two levels of AI; and those who are aware that horizontal AI opens the door, while vertical AI determines what we build once we go through it.
Complexity is no longer an obstacle to deployment. On the contrary, it has become the path to follow to obtain a real competitive advantage.
