AI Implementation Warning: 3 Critical Questions You Can’t Afford to Ignore

AI adoption is accelerating across industries, even in historically risk-averse segments like healthcare. With a growing body of evidence demonstrating that AI can enhance efficiency and spur innovation, medical device manufacturers and distributors are actively exploring AI implementation in their daily operations. The [obvious] goal: save time, improve performance, and reduce human error.

So, should you do it too?

Definitely … maybe.

That’s not a very satisfying answer. But just because something is easy (or relatively easy) to do, and just because it seems like everyone else is doing it, doesn’t mean it is the right (or even best) option. As with any novel solution, if you are considering AI implementation, your first step should be thoughtful reflection on the why, the when, and the how.

Why are we doing this?

There are great reasons to pursue AI implementation, in its many flavors. But that doesn’t mean they’re great reasons for you and your specific environment. Before making that determination, you should ask yourself and your team:

• Why are we considering AI implementation now?
• What outcomes do we expect to see?
• What do we hope to see?
• Why is this better than the other options?
• What will this do to our overall operations?
• How will it impact our position in the market?
• What are the risks, and is our “why” big enough to outweigh them?

This is the first hurdle. If you can’t clear this bar with your team and leadership, the timing isn’t right, even if the technology is. Sometimes, this is as much about creating the right narrative as it is about having the right solution. Actively engaging these questions with your team will help you define the story that shows the alignment between the goals you have, the opportunities you see, and the AI implementation you’re proposing. And if it doesn’t, you need to go back to the drawing board.

When should we do this?

Assuming your “why” passes muster, the next critical question is, When should we move forward with AI implementation?

• Can this be done with our current resources, or do we need outside help?
• Are there times of the year when our AI implementation risk is lower (or higher)?
• If we wait, how will that impact our position in the market?
• If competitors implement AI first, does that give them an unfair advantage?
• If we do it first, how will we benefit?

Even if you determine AI is a meaningful tool for your operations, that doesn’t mean AI implementation needs to happen immediately, as soon as possible, or (as many like to say) “yesterday.” Timing can be more important than tuning. Even if you have the right solution and your AI implementation plan is flawless, poor timing can be disastrous—and that type of failure can be the hardest to bounce back from.

How do we make this successful?

Once you get through the “why” and the “when,” your team needs clarity on how you will actually make this work. More to the point, you need to know:

• How do we define success for our AI implementation?
• What are the metrics and KPIs that will prove it?
• Do we all agree on those KPIs, and do they align to the “why” that’s driving this initiative?
• Who needs to be involved, and how do we get them on board?
• What happens if we can’t get them on board—is that enough to stop the effort?

If you can’t nail the “how,” you should pause your AI implementation efforts until you get those questions figured out. That doesn’t mean abandoning the project; it means you have gaps that should be addressed before moving forward.

Some of those gaps can be resolved “in flight,” but the most important part is knowing which questions need answers before you launch. After all, the “how” isn’t just about nuts-and-bolts execution; it’s about ensuring that AI implementation maximizes the value of your “why” in the first place.

Final Thoughts on AI Implementation

In the end, AI (and other novel technologies) hold significant promise for every industry, including medical devices and healthcare more broadly. But the process you use to evaluate AI implementation is just as important as the technology itself.

If you don’t have a process designed to support your success, there’s a high likelihood you’ll end up throwing time, money, and effort out the window. That’s not good for any business. Done thoughtfully, however, AI implementation can enhance efficiency, reduce risk, and create a durable competitive edge for any business.