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AI will impact employers before it impacts employment

AI will hardly affect the job market in 2018—but since it demands new structures, enterprises will feel pressure to retool. This is just one of eight PwC predictions about how AI will shape business in the coming year.

Everyone has seen the headlines: Robots and AI will destroy jobs. But we don’t see it that way. We see a more complex picture coming into focus, with AI encouraging a gradual evolution in the job market that—with the right preparation—will be positive. New jobs will offset those lost. People will still work, but they’ll work more efficiently with the help of AI.

Most people have heard that AI beat the world’s greatest grandmaster in chess. But not everyone knows what can usually beat an AI chess master: a “centaur,” or human and AI playing chess as a team. The human receives advice from an AI partner but is also free to override it, and it’s the established process between the two that is the real key to success.

This unparalleled combination will become the new normal in the workforce of the future. Consider how AI is enhancing the product design process: A human engineer defines a part’s materials, desired features, and various constraints, and inputs it into an AI system, which generates a number of simulations. Engineers then either choose one of the options, or refine their inputs and ask the AI to try again.

This paradigm is one reason why AI will strengthen the economy. At the same time, however, there’s no denying that in some industries, economies, and roles—especially those that involve repetitive tasks—jobs will change or be eliminated. Yet in the next two years, the impact will be relatively modest: PwC’s international jobs automation study, estimates that across 29 countries analyzed, the share of jobs at potential high risk of automation is only about 3 percent by 2020.

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Why organizations will succeed or fail

The upshot? In 2018, organizations will start realizing they need to change how they work. As they do so, they’ll need to be especially mindful of what has come before: failed tech transformations. There are several reasons why this happens, but two in particular are relevant to the way so many organizations are approaching AI. They’re pigeon-holing AI talent. And they’re thinking and working in silos.

AI-savvy employees won’t just need to know how to choose the right algorithm and feed data into an AI model. They’ll also have to know how to interpret the results. They’ll need to know when to let the algorithm decide, and when to step in themselves.

At the same time, effective use of AI will demand collaboration among different teams. Consider an AI system that helps hospital staff decide which medical procedures to authorize. It will need input not just from medical and AI specialists, but also from legal, HR, financial, cybersecurity, and compliance teams.

Most organizations like to set boundaries by putting specific teams in charge of certain domains or projects and assigning a budget accordingly. But AI requires multidisciplinary teams to come together to solve a problem. Afterward, team members then move on to other challenges but continue to monitor and perfect the first.

With AI, as with many other digital technologies, organizations and educational institutions will have to think less about job titles, and more about tasks, skills, and mindset. That means embracing new ways of working.

Implications

Popular acceptance of AI may occur quickly

As signs grow this year that the great AI jobs disruption will be a false alarm, people are likely to more readily accept AI in the workplace and society. We may hear less about robots taking our jobs, and more about robots making our jobs (and lives) easier. That in turn may lead to a faster uptake of AI than some organizations are expecting.

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The organizational retooling will commence

It will be a lengthy process, but some forward-thinking organizations are already breaking down the silos that separate data into cartels and employees into isolated units. Some will also start on the massive workforce upskilling that AI and other digital technologies require. This upskilling won’t just teach new skills. It will teach a new mindset that emphasizes collaboration with co-workers—and with AI.

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Anand Rao

Anand Rao

Global AI Lead; US Innovation Lead, Emerging Technology Group, PwC US

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Chris Curran

Chris Curran

Chief Technologist, New Ventures, PwC US

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Michael Shehab

Michael Shehab

Principal, Labs & Tax Technology, PwC US

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