It's a scenario that's being played out in boardrooms across the world. The budget has been passed, the buzz of excitement fills the air, and the message has been received loud and clear: "We need AI, and we need it yesterday."
The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it.
But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed.
There's a disconnect between what leaders want and what their technical infrastructure can handle. We often hear that culture or fear holds technology back. The data tells us that the problem is much more boring: it's about plumbing.
The Myth of the Resistant Worker
There's a common story in tech that employees are the blockers. We assume they're worried about robots taking their jobs, so they quietly sabotage new tools.
But that story is (mostly) false.
The enthusiasm is there. The problem is that 78% of enterprises struggle to connect these new AI tools with the systems they already use.
Think about your own stack for a moment. You likely have a CRM for sales, a different tool for support tickets, and another for internal chat. You buy a flashy new AI tool to help write emails or analyze data. But if that new tool can't talk to your old database, it's just a toy sitting in a silo.
This is why 53% of leaders rate integration as moderately to extremely difficult. It's not a lack of will; it's a lack of wires.
The IT Paradox
The survey revealed something interesting about who's driving this change. You might expect Marketing or Sales to push the flashy new tech. But IT departments are actually over 10 times more likely to lead the charge on AI than other departments.
Here's the paradox: IT is leading the charge, but it's also the most likely to slow things down.
This isn't because they want to be difficult. It's because they're the ones who have to clean up the mess. While the business screams for speed, IT has to ensure security, manage governance, and deal with infrastructure that was never built for this.
They're trying to build a skyscraper on a foundation made for a residential house.
On top of that, 29% of respondents point to bad data as a key issue. AI needs good fuel. If your internal records are messy or scattered, the best model in the world can't help you.
So, how do we fix this? Start regarding AI as a building challenge rather than a magic wand.
1. Think about the pipes rather than the faucet
Before you license the next tool, you should ask: "How does this tool integrate with the things you already own?" If it doesn't work with your database or doesn't let you send messages to Slack, it's adding friction. What you want are tools that work together.
2. Let data flow
Workflows are more important than models. You want to be able to transmit information from point A to point B without having to copy and paste through a human. That's where the magic happens. By integrating your email account, database, and AI, you can see real results.
3. Include the whole team.
IT has to be in charge of security, but they can't be the bottleneck for every little thing. You should be able to empower non-tech teams to create their own simple workflows. The reason you want to let the people closest to the work decide the workflows is that it lets you move quickly.
The industry doesn't require additional hype. What it needs are improved connections. The firms that will succeed ultimately won't be those acquiring the "best" AI. They'll be the ones who learn to make it work.