Technology, Not Policy, Will Drive Economic Growth

01/02/2017 03:54 pm ET Updated Jan 03, 2017

President-elect Donald Trump’s economic growth plan has sparked debate from economists on the left and the right. Both sides question whether Mr. Trump’s plans to overhaul the tax code, trade and policy proposals will work in the long-run to achieve sustained economic growth. Arguably, politics does not drive growth; productivity does. It comes down to how much people are working and how productive they are, which policy alone won’t solve.

Productivity hasn’t seen a surge since the late 1990s and early 2000s when advances in IT drove exceptional growth. The economy’s future growth demands companies try to do more with less. In recent years this has caused many companies to push their employees to do more in less time while delivering higher quality. But, we’re reaching the point where employees can’t do more without technology stepping up again. The secret to doing more with less is machines, not people.

The greatest gains in productivity will be achieved when the nature and structure of work changes. Workers spend 2 out of 5 business days each week on routine work that is not core to their jobs. Using manual tools that are ill-suited to the tasks they need to complete—email, spreadsheets, personal visits—workers waste almost as much time on busy work as they spend on doing the real work. A McKinsey multi-year study found that 30 percent of workers’ basic activities could be automated for about 60 percent of occupations.

Advances in automated bots, machine learning, messaging and the availability of data of all kinds will drive the next productivity surge needed for economic growth. These advancements will make it easier to build technology solutions that do the busy work so that workers can focus on business issues, allowing companies to increase productivity. According to ServiceNow’s State of Work research, organizations with 5,000 employees collectively across the United States could save $575 billion a year by automating unnecessary tasks and inefficiencies which would equal a 3.3 percent gain in the U.S. GDP, or approximately the combined annual profits of America’s 50 largest public companies.

People tend to think of automation on a factory line where technology can be used to assemble or package products faster than humans. This is a limited view. Automation enabled by machine intelligence will improve the productivity of knowledge workers as well. People are creating 2.5 quintillion bytes of data every day. This quantification of information shows no signs of slowing down. It is expected that M2M connections will reach 27 billion by 2024.It is impossible for humans to manage all of this data and analyze all of the relationships between people, information and things. But machines can.

Machines can be taught to understand the things that humans understand like tone or language. Today, you can take a fragment of text and a machine will tell you which language it is and whether the text is conveying happiness, sadness or anger. In customer service settings, these are both useful to know for routing and client management perspectives. This level of automation enabled by machine intelligence can personalize and speed customer service tasks today, boosting productivity.

The application of these software bots will extend well beyond customer support tools in 2017 and beyond. As the bot landscape expands and bots improve to provide contextual recommendations, bots will move beyond basic tasks. Bots will serve as digital virtual assistants to help workers reach their highest productivity. Based on ever-increasing data inputs, bots will evaluate how workers’ time is spent and make recommendations to improve productivity and quality. Using algorithms, bots will guide positive changes to employee behavior because they will be able to leverage individual contextualization.

Machines will become faster, smarter and more proficient than humans at many tasks. The highest levels of collaboration and productivity will be achieved when machines understand activities, context and motivation and can make the appropriate decision for humans. That does not mean we’ll all be losing our jobs to bots. Humans are not yet ready to move to a pure robotic world. But our economic growth will depend on using these increasingly capable technologies to improve our productivity to the point where workers can focus on the creative, value-add business issues that only humans can solve.

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