Overcoming AI Paralysis: Why Starting Is the Only Way Forward

By Richard Pugh , Gavin Jackson , Seth Clifford and Dr. Radu Orghidan, EMBA

Content creation process: This article was based on a discussion between our experts, the Endava AI Pod, and then generated with the help of ChatGPT and the Endava content team, using only insights based on the discussion, as part of an experiment to better understand ways of working with AI in authentic content generation.  

AI isn’t slowing down – in fact, the treadmill is only getting faster. In our roles, we speak to clients, teams and peers across industries who are all facing the same challenge: how to keep up with the speed of AI. The pace is unrelenting – new tools, models and frameworks seem to emerge every week. For many leaders, it’s less about fear of AI and more about the paralysis caused by too many choices and too little certainty. 

We’ve come to call this the ‘state of AI dizziness’, and it’s holding organisations back. The instinct in this environment is to wait. To observe. To analyse every option before acting. But we’ve learned that clarity doesn’t come from thinking harder – it comes from doing. 

It’s like trying to study a blurry photo of a NASCAR race. You can’t tell which car is in the lead because everything is moving too fast. And even if you could, that picture would change a moment later. That’s the nature of AI today. So how do we move forward? 

Our answer is simple: you start.  

You don’t need a perfect plan or the latest model. You need the ability to experiment, iterate and learn – in real environments, with real teams. 

Some of the most powerful AI insights we’ve seen emerge only after teams begin working hands-on. That’s when the right questions start to surface: Where do we want control? What data do we have? What makes our approach distinct? 

These are questions that won’t appear in a strategy document. They emerge from engagement. And that’s why experimentation is essential. 

Inside most organisations, AI initiatives don’t fail because of lack of interest, but because of inaction. We’ve seen too many great ideas get stuck in a backlog – never tested or explored – because teams feel like they don’t know enough to begin their journey.  

Every learning process begins with a start point 

But the truth is, you learn by starting. Think back to how companies first adopted computers. No one had the perfect use case. They bought one, gave it to a team and learned. That small step led to the transformation of every industry. 

We believe AI follows the same pattern. Starting is the catalyst; it’s what builds momentum and helps organisations bridge the gap between strategy and delivery. 

Inevitably, the landscape will continue to shift. There will always be a faster model or a newer tool on the horizon. But waiting for the dust to settle will only find you left behind.  

Start small. Start focused. But above all – start, because the only way to understand AI is to engage with it. 

If you enjoyed this article as our first piece in our AI content series, then watch this space, there will be more to come!