5 Common AI Pitfalls that Trick Unsuspecting CIOs

If there’s one thing CIOs are good at, it’s ignoring the hype and extracting the value out of technology. Except, however, when it comes to artificial intelligence. Whether it’s all the pomp and circumstance that clouds their reason or the lofty promises that tend to distract them, for some reason, a surprising number of IT leaders seem to fall into similar traps. It can be a costly lesson filled with delays and missteps. To avoid heading down this path in your organization, here are five risks to watch for.

Forgetting the importance of data.

We’ve said it time and time again, but an artificial intelligence solution is only as good as the data it has to work with. It’s sort of like having a Lamborghini and using subpar fuel. If you haven’t given adequate attention to ensuring that your AI platform is being fed data that is both accurate as well as relevant, then you will not realize much of any return on your investment (and you’ll probably end up holding the bag for it at the end of the day). A good strategy is to first identify which datasets are needed for each desired outcome and then building from there.

Being too quick to choose a solution.

A lot of CIOs get so amped up over the promises of what AI can deliver to their organization that they fail to perform due diligence when selecting a platform. Not only are solutions different in quality and potential benefits, but vendors themselves can vary widely on the spectrum of trustworthy vs. fly-by-night operations. Don’t fall for lofty promises. They may be legit, but it’s up to you to verify that by asking to see tangible results before signing on the dotted line.

Solving for the wrong problems.

Just because an AI solution works, doesn’t mean it’s delivering value. Ultimately, the goal isn’t to simply deploy artificial intelligence technology for the sake of doing so, but to generate actual return on your investment. To do this, you must define realistic, achievable objectives and outcomes that can be effectively tracked and measured. Otherwise, you’ll just end up with a fancy automation tool that does nothing more than cost you money.

Being lured by bells and whistles.

There are some pretty amazing artificial intelligence solutions out there. Unfortunately, many of them are so complicated, they’re actually not worth the investment to begin with. In fact, when a system is too complex, not only does it become detrimental, but it can lead to ancillary problems, like a lack of experienced personnel to manage the technology. Again, the goal is to deliver value, not get the fanciest tool on the market. Instead, you want a solution that’s advanced but also intuitive and as easy to use as possible.

Equating price with worth.

The fanciest tool on the market may have far more features than your organization even needs. And, as mentioned, the more bells and whistles, the more complicated and challenging it will be to deploy. Don’t be fooled into thinking that a hefty price tag means you’re getting the best possible solution. To the contrary, the platform that most closely matches your business needs may not only save you money upfront, but may also be more valuable in the long run as well.

Artificial intelligence has the potential to bring your organization to the next level. But only if it’s implemented the right way. If you’re just starting out on your AI journey, be cognizant of the above pitfalls so you can avoid them for yourself. If you’ve already fallen into one or more of these traps, the good news is, it’s never too late to right the ship.

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