Last year, economists were buzzing as the United States posted some of its best productivity growth in three years. Perhaps the economy had finally emerged from the woods of the IT boom’s conclusion in the early aughts and the aftermath of the 2008 financial crisis?
Yet, while the economy looked very strong in 2018, the big question on everyone’s mind is: How do we ensure this is sustained productivity growth? After all, December brought a new wave of market volatility that bred a new fear of insecurity.
There’s no doubt, however, that productivity will continue. Automation and artificial intelligence will spur sustained, long-term productivity growth. Perhaps the question we should be asking isn’t whether the United States can maintain its heightened rate of productivity, but how humans and robots can work together as co-pilots of that growth.
Investment in automation machines is one factor. What about humans?
Although many people are worried that robots might take jobs away from workers, it’s more likely that automation will allow a greater number of workers to be more productive as they oversee technology and automate repetitive processes.
Businesses are already answering the clarion call to automate portions of work. One survey report showed that 80% of enterprises already have some form of AI in production today, and 30% of enterprises are planning to expand their AI investments over the next 36 months.
Yet, technology alone rarely yields productivity growth. For example, even though investment in IT took off in the early 1970s, productivity growth was actually sluggish for more than two decades. This is partly because new technology’s impact can lag as companies try to figure out how to effectively apply new technology. This holds true for everything from the steam engine to the lightbulb to AI.
The real issue, as Vox Senior Columnist Matthew Yglesias pointed out in an article, is ensuring robots continue to add value to the workforce. The recent surge of technology, for example, has transformed our leisure time more than how we function in our workplaces, shifting the ways we watch television more than the way we might organize medical records in an office. Making real, sustained productivity improvements in the workplace using AI means we’ll need to have humans and robots become peers. This can be done by training human workers in new skills so that they can use AI technology more effectively and adapt business processes to meet new workflows.
Businesses must embrace training and reskilling workers
Unfortunately, training human workers to efficiently use AI is easier said than done. Despite all the buzz about AI, many businesses are ill-equipped to apply machine learning and data science principles in their businesses because they themselves don’t know how to use the new technologies. In addition, there are major shortages of workers with breadth of knowledge in these areas.
This trend is not limited to tech and other knowledge industries. As baby boomers retire, even the manufacturing sector is facing a shortage of the kind of skilled workers required to make partly automated smart factories run. For example, a Benteler Automotive plant in Indiana is losing $4,000 to $5,000 an hour due to a lack of employees who can perform tasks like “shape metal within a few thousandths of an inch.” The ideal person to work jobs shared by robots isn’t an engineer, but rather a skilled tradesperson with a two-year degree who can operate cutting-edge equipment. There simply aren’t enough of these workers, making hiring, training and retraining workers a hot topic in boardrooms and among upper management at companies.
Yet, just hiring skilled workers to handle new AI technology won’t be enough for companies to fully take advantage of AI’s full potential for productivity. For that, they’ll need to train robots to help human workers by taking over some of the tasks humans used to do for purposes of increasing efficiency. For example, UPS automates repairs previously done by humans in its fleet of Boeing aircraft using an AI-driven predictive maintenance system. The system collects data from pilot logbooks, performance monitoring systems and other sources to predict when particular parts may be about to fail, causing costly service delays. It then alerts maintenance control, which sends instructions to human line mechanics about which components to fix or replace before they break. UPS estimates that the system has yielded substantial efficiency gains.
This “connected worker” model stands to grow productivity by supporting workers, enabling them to increase output while requiring minimal training for them to become sufficiently skilled to master the technology. Examples of successful connected worker applications include everything from decreasing nonproductive time for energy companies to managing quality checks and starting work orders in factories.
The stakes for firms
Firms that want to boost productivity growth and succeed in any economy — no matter if markets are volatile — won’t do so simply by automating tasks and eliminating human jobs. They will do so by partnering human workers with AI robots and using machine-driven processes, allowing for more workplace efficiencies that lead to increased productivity.
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