A.I. is unstoppable. And A.I. is struggling.

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Not only is A.I. coming for your job, but there’s probably nothing you can do to stay ahead of the automation wave.

That’s the takeaway from a recent report from Gartner, the technology research firm, forecasting that 69% of the tasks managers currently perform will be automated within the next four years, “requiring a complete overhaul of the role of the manager.”
The same report also predicted big trouble ahead for companies’ attempts to retool and reskill their workforces to face this newly-automated future. It forecast that 47% of learning and development budgets will wind up wasted as A.I. eliminates about two-thirds of what Gartner calls “on-the-job, task-based learning opportunities.”

But for every report such as this about the vast potential of artificial intelligence to radically reshape the nature of work there seems to be another one that points to a yawning gap between that potential and what most companies are finding they can actually achieve with the technology today. 
In the here and now, automation’s march does not seem to be quite so smooth. Another report out last week from Plutoshift, a Silicon Valley startup that provides software to help industrial companies collect data and implement predictive analytics, found that many manufacturing firms were struggling to use A.I.
Of the 250 industrial firms Plutoshift surveyed,

• over 72% found that they had taken far more time than anticipated to implement the necessary data collection processes for applying machine learning.

• and perhaps as a result, only 17% of those surveyed said they were actually at the full implementation stage of using A.I.,

• while about 70% said they were still studying what resources they’d need, assessing possible business use cases, or conducting small pilot projects only.

“Companies in the middle of this transformation usually lack the proper technology and data infrastructure,” Prateek Joshi, Plutoshift’s founder and chief executive officer, says. “In the end, these implementations can fail to meet expectations.”
Worryingly, almost 20% of companies cited “peer pressure” as the reason they had embarked on A.I. projects.

These dueling surveys, along with some other bits of A.I. news (see below) about companies using misleading marketing to sell their software, raise the looming spectre of disillusionment with the technology. Are businesses entering a new era of snake (or sn-A.I.-ke) oil salesmanship?

Jeremy Kahn
@jeremyakahn
[email protected]

This story was originally featured on Fortune.com