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By 2022, One in Five Workers Engaged in Mostly Nonroutine Tasks Will Rely on AI to Do Their Jobs

By Craig Roth | December 05, 2017 | 0 Comments

RobotsInformation workDigital WorkplaceAI

Artificial intelligence (AI) is hitting its stride.  Articles and conference presentations expound on how AI can transform smart cities, your shopping experience, and medical diagnosis.  Not to mention self-driving vehicles, drone targeting, and, when you finally decide to relax at home, beating you at whatever games you decide to play.  But overlooked in all these use cases are the assistance AI will provide future information workers going about their daily jobs.

By 2022, one in five workers engaged in mostly nonroutine tasks will rely on AI to do their jobs.

The current figure is probably more like one in eighty if you take into account all the parameters built into my prediction, which appears in the “Predicts 2018: AI and the Future of Work” (link here for subscribers).

One of those parameters is that I say the workers will rely on AI.  By this I mean they aren’t just playing around with an NLP query engine or checking out people and document recommendations once in a blue moon.  They will reach a point where they depend on the insights of AI to do their jobs. AI will electrify the productivity tools these workers use, bringing them to another level of power and accuracy that become part of the way they work and redefine expectations for what type of work they do and the level of quality they can produce.  At that point, taking away their AI would be like a craftsman having their electric woodworking tools replaced with manual ones.  They’re more likely to fight you off with a nail gun!

I also specify nonroutine tasks – the work that isn’t highly repeatable or structured and requires the worker to invent how to get the task done as they go.  With outsourcing and automation taking more and more of the routine work, nonroutine work is where developed economies generate the most value and differentiation. Because it is tacit, applying simple automation can be difficult, but techniques like deep learning can be applied.

And if you read between the lines, you’ll notice that I’m implying these workers still have jobs!  I’m predicting that workers will rely on AI rather than being replaced by it.  General purpose knowledge work could only be fully replaced by general purpose AI, which is still in the realm of science fiction.

At this point any organization that depends on nonroutine work should be exploring the capabilities built into their existing email, office, content management, and social tools such as natural-language queries of datasets, autoclassification of content, notification of “important” emails or instant messages, and introductions to colleagues who have similar interests. With a bit of digital dexterity these capabilities can be incorporated into your digital workplace.

And vendors need to start building out their AI infrastructure (if they haven’t already): their ability to accumulate and analyze the methods and outputs of knowledge work such as emails and their metadata, information in employee profiles, spreadsheets and the decisions made from them, lists of team members, and usage information from devices and things in the instrumented workplace. Investments today will really start paying off by the end of this five year timeframe.

The Gartner Blog Network provides an opportunity for Gartner analysts to test ideas and move research forward. Because the content posted by Gartner analysts on this site does not undergo our standard editorial review, all comments or opinions expressed hereunder are those of the individual contributors and do not represent the views of Gartner, Inc. or its management.

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