Artificial intelligence and advanced robotics are making it possible for machines to take on tasks that once required a person to do them. By some accounts, almost half of all jobs in the U.S. economy could be made obsolete. So how should companies prepare strategically to thrive in this new world? Business leaders must take steps now to shape their workforces for the emerging intelligent enterprise. Companies that think beyond labor substitution and cost savings will see a much greater payoff. Consider using technology to augment human skills and reinvent operating models. Take the opportunity to redefine jobs and rethink organizational design. And make employees your partners in building the intelligent enterprise in order to strike the right balance between investing in intelligent technologies and maintaining existing businesses. Those companies that actively seize control of what can be done now will position themselves to thrive in this exciting new era.

Yaroslav Kushta/Getty Images

The future of the workforce is one of the biggest issues facing CEOs today. It’s abundantly clear to all that artificial intelligence, big data analytics, and advanced robotics make it possible for machines to take on tasks that once required a person to do them. How should companies prepare, strategically, to thrive in this world?

Views on what to expect vary dramatically. By some accounts, almost half of all jobs in the U.S. economy could be made obsolete. Others have described how intelligent machines will actually create jobs — including entirely new categories of jobs. Some people even talk about a world of superabundance where work will be about pursuing your passion, on your own terms.

It’s critical for companies to understand the range of opinions on this issue, because implicitly or explicitly, they will influence the way business leaders create the workforce of the future. And while a lot will shake out in years to come, this issue is already front and center. Companies are making decisions today that will matter hugely to their ability to compete tomorrow and throughout the 2020s.

Insight Center The Risks and Rewards of AI Sponsored by SAS Assessing the opportunities and the potential pitfalls.

Most companies are already moving rapidly to acquire new capabilities. In a new Accenture survey (“Reworking the Revolution,” which published on January 23rd) of 1,200 C-level executives worldwide, 75% say that they are currently accelerating investments in AI and other intelligent technologies. And 72% say they are responding to a competitive imperative — they recognize the need for new tools to keep up with rivals, both by improving productivity and by finding new sources of growth. Some companies are transforming themselves into “intelligent enterprises,” in which all processes are digitized, decisions are data-driven, and machines do the heavy lifting — both physical and cognitive.

So, there’s a great deal at stake in the debate over productivity and jobs. Leaders must understand the debate and be prepared to address tough questions: What kind of new skills do we need? How should we be organized? How do we define jobs? How can we bring our people along with us, in a way that benefits everyone?

Through research, we’ve identified five schools of thought in this debate.

The Dystopians

Position: Man and machine will wage a Darwinian struggle that machines will win. AI systems will take on tasks at the heart of middle- and high-skill jobs, while robots will perform menial work that requires low-skill labor. The result will be massive unemployment, falling wages, and wrenching economic dislocation. Falling incomes will have grave consequences in places like the United States and Europe, where consumption accounts for 56% or 69% of GDP, respectively, requiring new social supports, such as a universal basic income.

The Utopians

Position: Intelligent machines will take on even more work, but the result will be unprecedented wealth, not economic decline. AI and computing power will advance in the next two decades to achieve “the singularity” — when machines will be able to emulate the workings of the human brain in its entirety. Human brains will be “scanned” and “downloaded” to computers and billions of replicated human brains will do most of the cognitive work, while robots will do all the heavy lifting. Economic output could double every three months. The singularity may even lead to a world where little human labor is required, a universal income program covers basic needs, and people apply their talents to meaningful pursuits.

The Technology Optimists

Position: A burst of productivity has already begun but is not captured in official data because companies are still learning how intelligent technologies can change how they operate. When companies do take full advantage of intelligent technologies, a leap in productivity will produce a digital bounty — creating both economic growth and improvements in living standards not counted in GDP, such as consumer surplus (from better, cheaper products) and the value of free apps and information. However, based on current trends, the bounty won’t be distributed evenly, and many jobs will be displaced. To avoid negative income and employment effects, there will be a need to invest in education and training alongside investments in technology.

The Productivity Skeptics

Position: Despite the power of intelligent technologies, any gains in national productivity levels will be low. Combine that with headwinds from aging populations, income inequality, and the costs of dealing with climate change, and the United States will have near-zero GDP growth. In the end, there isn’t much to do except brace for stagnant growth in advanced economies.

The Optimistic Realists

Position: Digitization and intelligent machines can spur productivity gains that match previous technology waves. Productivity will advance rapidly in certain sectors and for high-performing companies. New jobs will be created, but intelligent technologies may exacerbate the trends of the recent past, in which demand rose for both high- and low-skill workers whose jobs could be easily automated, while demand for middle-skill workers fell. With no simple solutions, more research is needed into the true relationship between productivity, employment, and wages to uncover effective responses.

Three Actions for Shaping the Future

Our crystal ball for what things might look like in 10 years is cloudy. What we do know is that business leaders must take steps now to shape their workforces for the emerging intelligent enterprise. Our research and experience point to three critical imperatives:

Use technology to augment human skills and reinvent operating models. Companies that think beyond labor substitution and cost savings will see a much greater payoff. For example, a new class of adaptive robots can function safely alongside workers and can take on difficult and tedious work. Consider this example: At BMW’s Spartanburg, S.C. plant, robots are installing door-sealing gaskets, an awkward and tiring job for workers. This speed up the line, improves quality, and gives workers more time to do higher-value work. Researchers estimate that using adaptive robots this way could cut time wasted on non-value-added work by 25%. Employee surveys show that workers have more positive views of the new robots, which they regard as useful helpers. Away from the factory, companies are using AI to offload routine work from employees and to give them new analytical tools to improve customer experience and discover new possibilities for products, services, and business models that drive growth.

Take the opportunity to redefine jobs and rethink organizational design. Companies cannot optimize their investments if they have the same old job descriptions and organizational structures. Executives should assess the tasks that need to be done, anticipate which ones will be transferred to machines, then reconfigure jobs by adding new tasks or creating entirely different roles that are needed for managing intelligent technologies. A factory worker, for example, can be trained to run robots. AI systems also need human help to train and correct algorithms and override fallible machine judgment. For example, at Stitch Fix, an online clothing subscription service, 3,400 human stylists work with an AI recommendation engine to make personalized suggestions for customers. The machines give stylists the speed they need to be productive, and the stylists provide the additional judgment needed for accurate recommendations (and fewer returns). To function effectively, an intelligent enterprise should have a non-hierarchical organization, in which employees collaborate across functional and operational silos. This enables the intelligent enterprise to act quickly on the insights from data-crunching machines and deploy human talent to swarm on problems, experiment, iterate, and get solutions into the market.

Make employees your partners in building the intelligent enterprise. To strike the right balance between investing in intelligent technologies and maintaining existing businesses, companies need help from their employees. In our (above-referenced) research, we have found that employees are far more willing — even eager — to master new technologies than employers appreciate. They want to learn new skills, not least because they know they will need them to remain employed. Investments in both technology and training will help companies make a smooth transition to the intelligent enterprise. Companies that do this stand to outperform competitors because they will unleash the human talents that machines still can’t match and that are essential to growth — creativity, empathy, communications, adaptability, and problem-solving. “As basic automation and machine learning move toward becoming commodities,” says Devin Fidler, research director at the Institute for the Future, “uniquely human skills will become more valuable.”

The debate over technology and jobs will rage on. Business leaders must follow this debate — and participate in it, too. And much more research is needed to fully understand the implications of intelligent technologies on work. In the meantime, companies that actively seize control of what can be done to prepare will position themselves to thrive in this exciting new era.

The author thanks his colleagues in Accenture Research, Svenja Falk, David Light, and Geoffrey Lewis, for their contributions to this article.

Editors’ note: We’ve updated this article with the correct number of human stylists at Stitch Fix.