Don’t be a victim of “AI washing”

Caution

As enterprise interest in artificial intelligence (AI) and machine learning increases, software vendors are rushing to meet market demand for AI-based solutions. So much so that by 2020, “AI technologies will be virtually pervasive in almost every new software product and service,” according to research and consulting firm Gartner.

This might actually be causing problems for enterprise decision-makers. “As AI accelerates up the Hype Cycle, many software providers are looking to stake their claim in the biggest gold rush in recent years,” said Jim Hare, research vice president at Gartner. “AI offers exciting possibilities, but unfortunately, most vendors are focused on the goal of simply building and marketing an AI-based product rather than first identifying needs, potential uses and the business value to customers.”

In other words, some software vendors are merely jumping on a bandwagon just to make a few bucks! (What’s next, gluten-free software?) Here’s how Gartner explains it:

Similar to greenwashing, in which companies exaggerate the environmental-friendliness of their products or practices for business benefit, many technology vendors are now “AI washing” by applying the AI label a little too indiscriminately.

Gartner goes on to offer vendors advice on how to stand out from the crowd, but these tips can be adapted for enterprise customers. For example, to “build trust with end-user organisations,” Gartner advises, “vendors should focus on building a collection of case studies with quantifiable results achieved using AI.”

That means use cases of actual customers using the vendor’s actual solution. As a technology writer, one huge red warning flag to me is when a vendor can’t point to a customer that has enjoyed tangible benefits using their product or services. I understand every company has to start somewhere — that’s why they call them start-ups! — but seriously, show me some proof before you start bragging about your “solutions.”

I’d suggest the same to enterprise customers: Don’t invest in software touting the benefits of AI without first seeing proof that it’s working as the vendor claims.

Gartner also urges vendors not to get too fancy. “Advancements in AI, such as deep learning, are getting a lot of buzz but are obfuscating the value of more straightforward, proven approaches,” Gartner says, going on to recommend “that vendors use the simplest approach that can do the job over cutting-edge AI techniques.”

Similarly, enterprise customers should look first for simple needs that can be addressed by AI. This provides an immediate return on investment and valuable experience with AI, which can set the stage for more ambitious use cases down the road. Pilot projects helped set the stage for many more ambitious cloud deployments and big data roll-outs; using the same approach for AI will serve many enterprises well.

Finally, lack of the right skills internally is the biggest barrier to enterprise AI adoption. Thus, Gartner advises, vendors should highlight how their “AI solution helps address the skills shortage and how it can deliver value faster than trying to build a custom AI solution in-house.”

For enterprises, that means a couple of things: 1) Packaged AI solutions may make the most sense for now, and 2) It would behoove you to go out and get some AI talent before your competitors do.

It’s hard to ignore the AI hype, but if enterprise decision-makers can first determine what they want to get out of AI, they’ll automatically eliminate a lot of market noise. That alone will make their decision easier.

Next week: Cutting through the hype around gluten-free software.

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Comments

  1. AI will fail if businessmen and entrepreneurs only talk about business, possess poor attitudes, and don’t want to learn and know what AI is and how it works.

    Like

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