You might want to try new AI tools, but the IT team keeps getting in the way – because they (rightly) don’t want unauthorised tech in your system. But there’s a simple way you can keep experimenting and evolving with AI, while still keeping your IT team happy. It’s a practical way to keep innovation moving while still staying on the right side of the IT team.
As a leader, where are you getting stuck with using AI in your team?
I was running a presentation recently about AI at work, and a participant raised a challenge she’s facing (and it’s not uncommon).
She and her team are already using AI, and are keen to keep trying new AI software and platforms. But whenever they want to sample some products or trial some new AI software, the IT team puts their foot down and stops them.
That’s for a good reason. IT professionals have the unenviable task of supporting increasing demands for enabling digital infrastructure while also protecting the organisation from AI-powered cybersecurity attacks, AI-powered rogue agents, and naïve staff using powerful technology without knowing the risks. So, of course, that’s why they might instinctively block your AI plans.
The IT department often gets a bad rap for being overly cautious, but most IT professionals love new technology and are keen to use it. But you need to do it on their terms, after they carefully assess, test, and integrate it with their existing systems.
On the other hand, you and your team might be keen to try out some new software.
The best way to manage this conflict is with AI projects.
Start with a small pilot project or prototype (with the approval of the IT team), keeping it separate from your main tech setup and with dummy data (so you don’t accidentally leak private or confidential information). Use this to test the concept and figure out if it’s worth pursuing.
Then, if it works, take it to the IT team and build the full working version – with their help.
You will probably have to discard everything from the prototype and build it again from scratch using approved software and infrastructure. But that’s exactly what you want. Treat the prototype as a clunky, messy, scrappy experiment designed to prove the value of your idea, and fully expect to throw it away.
In my next public online presentation, I’ll be talking about how to take AI to the next level – from individual use to team use. I’ll share a five-step process for running AI projects this way. Please join me, and invite others in your team and network as well.
Register for the virtual masterclass: