It’s hard to find a senior business leader today who hasn’t at least considered the potential of Generative AI (GenAI). Conversations about automation, efficiency, and innovation pop up in boardrooms and leadership meetings for all industries across the globe. The widespread agreement is that GenAI can fundamentally change the way organizations operate.
And yet, despite the excitement and the growing number of proof-of-concept projects underway, many businesses are struggling to deliver anything more than interesting experiments. The majority of GenAI initiatives remain in the pilot stage, with few having crossed the threshold into production. In Vertesia’s recent survey of 400 enterprise IT leaders, 85% of organizations shared that they are working on custom GenAI solutions, but only 30% currently have those solutions in production. The rest are either still exploring possibilities or facing significant barriers to deployment.
This disconnect between desire and delivery warrants a closer look, because the issue is not a technical problem, but something else. The technology is here, the capabilities are proven, and use cases are emerging daily. So, what is the real issue?
The challenge isn’t technological. It’s organizational.
One of the most common misconceptions is that GenAI is an initiative for the IT or AI team to figure out while the business waits to benefit from the results. In reality, successful GenAI deployment is only possible when business and technical teams work in partnership, with shared goals, clear accountability, and aligned priorities.
Too often, we see business leaders enthusiastic about the potential of GenAI but hesitant to engage in the realities and activity of deployment. There’s a tendency to treat GenAI as a “technology project” and let the IT team deal with it, rather than realizing an opportunity to fundamentally improve core business processes. The result is predictable: innovation stalls, pilots fail to scale, and any momentum is lost.
This scenario is spectacularly ironic given that the most compelling GenAI use cases are driven by business needs. These might involve enhancing customer communication, streamlining internal workflows, or surfacing insights from large volumes of unstructured data. None of these are abstract ideas; they’re tangible outcomes that business leaders care about. However, solutions to these challenges only happen when business leaders take ownership of the problem and drive the change.
From experimentation to strategic execution
To understand what’s holding many organizations back, it helps to look at how GenAI projects begin. Most cases start with curiosity. Perhaps a new AI model is released, the IT team runs some internal tests, or a vendor offers to demonstrate what’s possible. From there, a proof of concept gets developed—usually targeting a non-critical task—to demonstrate the model’s potential.
While these early experiments can be helpful to build internal awareness, they rarely create meaningful value on their own. Without a clear path to production, well-defined success criteria, or long-term ownership, the experiments end up as shelfware and a wasted effort. Worse, they can lead to disillusionment within the wider business when the initial excitement fails to translate into results.
Contrast this with what we see in organizations that are seeing returns from GenAI. These companies don’t just experiment, they execute. They identify high-value opportunities where GenAI can address a clear business challenge, and quickly move to close collaboration with their technical teams to define requirements, evaluate options, and deploy solutions. Most importantly, they build with scale in mind. This mindset means choosing architectures, platforms, and processes that allow them to expand their efforts over time, rather than delivering a single app in isolation.
The role of business in GenAI success
If you’re a business leader reading this, and your organization is still stuck in pilot mode, ask what it would take to move faster. Not just to play with GenAI, but to operationalize it and get genuine business benefits.
The answer isn’t another proof of concept. Instead, you should consider a mindset shift, from passive supporter to active sponsor.
Business leaders have a unique ability to unlock progress. They understand which outcomes matter, where inefficiencies lie, and which processes could benefit most from augmentation or automation. They’re also best positioned to set priorities, allocate resources, and build the cross-functional alignment required to deliver real change.
That doesn’t mean business leaders need to become AI experts. But it does mean they need to engage more deeply in the conversation, not just to approve budgets but to shape the agenda. That might involve identifying where GenAI can support strategic goals, working with data owners to ensure information is accessible, or, more likely, challenging internal teams to focus less on technical perfection and more on business impact.
Start with use cases
Not every GenAI idea will deliver transformational results. Some will generate nothing more than the technical high that IT gets from solving a problem with new technology. However, there is no shortage of high-value business use cases that can provide quick wins while building the foundation for broader adoption.
For example, many organizations use GenAI to enable more intuitive access to internal knowledge, transforming how employees interact with policies, procedures, or research by surfacing relevant answers through natural language queries. Others are automating parts of document review and risk analysis, particularly in legal, compliance, or finance teams. Some are focusing on content generation, using GenAI to support the creation of personalized communications or structured reports at scale.
These kinds of applications are not only beneficial, but they’re also highly visible. That makes them ideal for demonstrating a return on investment and generating internal momentum. They also benefit most from business ownership, measuring success by improved outcomes rather than technical prowess.
Business and IT: stronger together
Ultimately, the most successful GenAI initiatives see business and technical teams operate as true partners. Business defines the problem, the IT team brings the tools, and together they deliver a solution that works.
But this kind of collaboration doesn’t happen by accident. It requires shared language, mutual respect, and a willingness to align around outcomes rather than roles. Again, it requires the business to take responsibility, not for the technical details, but for ensuring that GenAI investments are focused, funded, and followed through.
At Vertesia, we believe that GenAI is most powerful when treated not as a one-off project, but as an enterprise capability. That’s why we’ve developed a step-by-step guide to help business and technology leaders move from experimentation to execution. It covers areas such as identifying the ideal use cases, preparing your data, selecting the best delivery model, and building a repeatable framework for success.
If you’re ready to stop experimenting and start scaling, the guide is a great place to begin.
What’s really holding GenAI back?
Most organizations don’t lack ambition around their GenAI goals. They don’t even see a lack of investment in the area either. What is missing is a clear path from business intent to scalable execution, and the misconception that GenAI success rests solely with the IT team.
GenAI should be a business capability with business leaders shaping direction, setting priorities, and partnering with IT to drive outcomes that matter.
The technology is ready. The use cases are proven. The opportunity is wide open.
What’s holding GenAI back isn’t what’s possible. It’s who takes responsibility for making it real.