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According to Google Trends, we hit “peak AI” in May 2017. In that month, Google searches for the term “artificial intelligence” in U.S. business and industry sources outpaced any period since March 2004 (when the AI film “I Robot,” with Will Smith, was released).

It’s not surprising. I think we’ve all been feeling oversaturated AI news lately: Advocates are hyping the benefits of machines that teach themselves to solve the world's biggest problems and critics warn that we humans will lose our jobs, privacy and maybe even our perch at the top of the planet’s pecking order.

We heard theoretical physicist Stephen Hawking warn in 2014, “The development of full artificial intelligence could spell the end of the human race,” once AI teaches itself to emulate human consciousness, experiences, memories and thoughts. And we’re somewhat comforted by humanists like Deepak Chopra who, in a July 2016 essay in New Perspectives Quarterly declared, “Artificial Intelligence will never rival the deep complexity of human minds.”

My money is on Chopra—whose perspective offers useful insights for leaders in professions where AI is about to have a major impact. What makes us human, he wrote, “is that consciousness can go where logic can’t…We make quantum leaps. We follow ridiculously indirect paths in life—from the perspective of a logic machine—and find ourselves wiser for the experience.”

Go local, organic

The best way for enterprises to prepare for the AI invasion, therefore, is to focus on the kind of intelligence that isn’t artificial: the local, organic kind that, at least for now, only humans possess.

There is little disagreement that AI is about to upend every white-collar profession in the same the way that the first industrial robot, called the Unimate and installed in a General Motors factory in 1959, heralded the massive displacement of blue-collar assembly line jobs. Much of the routine tasks involved in law, medicine and architecture, for example, soon will be replaced by AI software that can handle them faster and more accurately.

While AI will, in fact, disrupt all these professions and cost jobs, it will also liberate those who remain to use their organic intelligence to carry out jobs humans do best: create, plan, decide, implement, work as a team. In a word: Innovate.

Remember, the displacement of assembly line workers also sparked such new, human-dependent innovations as quality assurance, agile teamwork, just-in-time supply chains and logistics management. In a similar way, white collar professionals will need to retrain, amassing job skills that best utilize their own unique intelligence. As “legal tech” automation handles tasks like e-discovery, contract management and routine services, lawyers will need to focus on client interaction, negotiating, counseling and leveraging relationships. Doctors will spend more time relating to patients, exploring AI-derived options for therapies and innovating with customized treatments the way only humans can do. Architects will spend less time drawing and researching specifications and more time creating 3D models, managing projects, building customer relationships and getting involved in community design.

Business schools also must awaken to this change. After decades of cranking out MBAs who know how to run fancy statistical models and market-beating algorithms, demand will grow instead for managers who know how to innovate, motivate teams and make quick decisions.  Today’s MBA student “can pass a calculus exam, but they can’t identify or solve problems on job, or negotiate," or lead a meeting, concluded four business school researchers in a harsh July 2016 critique of business schools. “In each case, workers will be asked not just to produce more with fewer resources (aka optimization); they'll now be asked to innovate in new ways, as teams.”

Blue-collar workers have spent decades adjusting to labor-saving automation. Now that robots are thinking for themselves, and are being promoted to the front office, we’re about to see how well white-collar professionals learn and adapt.

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