As we push through 2025, the chatter around Generative AI has shifted. It’s no longer just a concept or a hype cycle; it’s a real-world business challenge.
That shouldn’t be a surprise, but for many it still is. In my chats with leaders from Waracle’s core sectors, I’m seeing a clear pattern that aligns with recent global studies. The question isn’t whether companies should or could use AI anymore, it’s switched to overcoming the fear factor and achieving deliverable results.
So, what’s happening out there? Companies are falling into one of three camps…
Let’s explore the three camps and think about how we’ll navigate past our current predicament and into the opportunity that lies beyond!
Let’s be honest: most people I talk to are in this first group. They’re experimenting, which is excellent, but many find it hard to progress beyond small-scale, isolated tests.
This reflects what market-wide research is saying: nearly everyone is dabbling in AI, but very few companies would say they’ve truly mastered it. As a result, there’s a broken link in the chain, where the isolated team hasn’t always shared the knowledge with other parts of the business. The experiment hasn’t been in growing GenAI capability, but instead in trying to find a shiny use case.
The interesting thing is what they’re asking for now. It isn’t a massive, complex AI build. The most significant demand I see is for guidance – for board-level presentations, “art of the possible” workshops, and solid strategic advice, which makes perfect sense.
One statistic shows that having a formal AI strategy sponsored by the C-suite can increase project success rates from a measly 37% to over 80%. Without that clear vision from the top, organisations just stay stuck in the maze of exploration, something our CEO, David, impressed upon the audience of a recent Unlearn podcast episode.
This is where things start to get exciting. This second group of companies is moving past the “what if” and getting down to the “what now.” They are driven by practical goals, and my client conversations line up perfectly with research showing that the top drivers for AI adoption are boosting business efficiency by at least 46% and improving productivity by a similar margin.
The projects themselves are incredibly diverse. For example, in the heavily regulated world of financial services, I’m seeing firms build tools to check various complex documents automatically. This saves considerable time and reduces the risk of expensive mistakes. These pioneers are doing more than just buying tech; they’re building a “compliance moat” with strong governance, giving them a competitive edge that others will find difficult to copy.
Over in healthcare, there’s a significant focus on tackling clinician burnout by using AI to automate the mountain of administrative work—a direct and much-needed response to one of the industry’s biggest crises.
Finally, there’s a smaller but growing group of true innovators who are already pushing the boundaries of what GenAI can do. These organisations deliberately avoid the “trap of incremental gains,” where focusing only on improving business-as-usual can stifle breakthrough ideas.
They’re looking past immediate productivity and are using AI to change how they develop their core products. I’ve had some fascinating discussions with product teams wanting to use AI for complex tasks in user experience and product governance, with all the benefits of explainable AI, so it’s not just a “black box”.
This is a massive leap towards maturity; using AI not just to improve a process, but to change how a business innovates fundamentally.
Here’s the bit that I think is most critical, and it’s not about the technology. It’s the human element. Recent studies have highlighted a massive perception gap: 75% of C-suite executives might feel their company has nailed GenAI adoption, but only 45% of their employees see it the same way.
This disconnect is a recipe for internal friction and can lead to what’s known as “shadow AI.” This is where staff, feeling unsupported, start using their personal AI tools to get work done. One study found that over 70% of healthcare workers do this, opening up enormous security and compliance risks. Fixing this requires a human-first approach focusing on teamwork, open communication, and real investment in upskilling people.
Again, in the Unlearn podcast, Barry O’Reilly summed it up:
“AI didn’t kill human connection. It made it matter more. Tech evolves. Tools improve. But trust, curiosity, and empathy still drive great work.”
From all these conversations, a few key things are crystal clear.
The AI journey is a marathon, not a sprint. The companies that will win are those that build a solid strategic foundation before they even consider building a house.
Where is your organisation on this journey? I’d like to hear your thoughts, so drop us a message and let’s carry on the conversation.