Look right, look left, you’ll see a fellow CIO contemplating their artificial intelligence move. Failing to act is not an option in most organizations. However, as enterprises are kicking off their AI pilots or seeing early results, the honeymoon is over as enterprises that naively celebrated the cure-all promises of artificial intelligence (AI) technologies is over.
Enterprises needed better data foundations. They underestimated the level of business expertise needed. They didn’t anticipate the resources it takes. And enterprises needed to rethink their business models. The truth is, AI is hard!
Forrester predicts that 2018 will be the year when a majority of enterprises start dealing with the hard facts: AI and all other new technologies like big data and cloud computing still require hard work. Our 2017 predictions for data and analytics pointed to AI as the spark to the insights revolution. This came true: Survey respondents who told us their firm was investing in AI rose from 40% in 2016 to 51% in 2017. But success isn’t easy — 55% of firms have not yet achieved any tangible business outcomes from AI, and 43% say it’s too soon to tell.
The wrinkle? AI is not a plug-and-play proposition. Unless firms plan, deploy, and govern it correctly, new AI tech will provide meager benefits at best or, at worst, result in unexpected and undesired outcomes. If CIOs and chief data officers (CDOs) are serious about becoming insights driven, 2018 is the year they must realize that simplistic lift-and-shift approaches will only scratch the surface of possibilities that new tech offers.
In Forrester’s 2018 AI predictions released today, we provide CIOs working on data and analytic initiatives with pragmatic and tangible recommendations on how to act now with their AI initiatives. Here are just a few ways we predict AI will shape enterprises in 2018:
2018 will be the year that CIOs will realize that new technologies like AI require hard work. Forward-looking organizations will create new roles and processes to take full advantage of them – not by simply shifting away from old architectures, but by redesigning their whole operating models to suit the new wave of technology.
(This post originally appeared on the Forrester Research blog, which can be viewed here).
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