RALEIGH – Dr. Mike Walden, an economics professor at N.C. State, writes about a new report on the future of work from McKinsey Global Institute in his latest column.

Here’s a look at more details from that analysis.

“There is work for everyone today and there will be work for everyone tomorrow, even in a future with automation. Yet that work will be different, requiring new skills, and a far greater adaptability of the workforce than we have seen,” the report explains.

“Training and retraining both midcareer workers and new generations for the coming challenges will be an imperative. Government, private-sector leaders, and innovators all need to work together to better coordinate public and private initiatives, including creating the right incentives to invest more in human capital. The future with automation and AI will be challenging, but a much richer one if we harness the technologies with aplomb—and mitigate the negative effects.”

‘Ten Things to Solve for’

“[T]he focus should be on ways to ensure that the workforce transitions are as smooth as possible,” the report adds. The authors note 10 “actionable and scalable solutions in several key areas:. They are:

  • Ensuring robust economic and productivity growth. Strong growth is not the magic answer for all the challenges posed by automation, but it is a prerequisite for job growth and increasing prosperity. Productivity growth is a key contributor to economic growth. Therefore, unlocking investment and demand, as well as embracing automation for its productivity contributions, is critical.
  • Fostering business dynamism. Entrepreneurship and more rapid new business formation will not only boost productivity, but also drive job creation. A vibrant environment for small businesses as well as a competitive environment for large business fosters business dynamism and, with it, job growth. Accelerating the rate of new business formation and the growth and competitiveness of businesses, large and small, will require simpler and evolved regulations, tax and other incentives.
  • Evolving education systems and learning for a changed workplace. Policy makers working with education providers (traditional and nontraditional) and employers themselves could do more to improve basic STEM skills through the school systems and improved on-the-job training. A new emphasis is needed on creativity, critical and systems thinking, and adaptive and life-long learning. There will need to be solutions at scale.
  • Investing in human capital. Reversing the trend of low, and in some countries, declining public investment in worker training is critical. Through tax benefits and other incentives, policy makers can encourage companies to invest in human capital, including job creation, learning and capability building, and wage growth, similar to incentives for private sector to invest in other types of capital including R&D.
  • Improving labor-market dynamism. Information signals that enable matching of workers to work, credentialing, could all work better in most economies. Digital platforms can also help match people with jobs and restore vibrancy to the labor market. When more people change jobs, even within a company, evidence suggests that wages rise. As more varieties of work and income-earning opportunities emerge including the gig economy, we will need to solve for issues such as portability of benefits, worker classification, and wage variability.
  • Redesigning work. Workflow design and workspace design will need to adapt to a new era in which people work more closely with machines. This is both an opportunity and a challenge, in terms of creating a safe and productive environment. Organizations are changing too, as work becomes more collaborative and companies seek to become increasingly agile and nonhierarchical.
  • Rethinking incomes. If automation (full or partial) does result in a significant reduction in employment and/or greater pressure on wages, some ideas such as conditional transfers, support for mobility, universal basic income, and adapted social safety nets could be considered and tested. The key will be to find solutions that are economically viable and incorporate the multiple roles that work plays for workers, including providing not only income, but also meaning, purpose, and dignity.
  • Rethinking transition support and safety nets for workers affected. As work evolves at higher rates of change between sectors, locations, activities, and skill requirements, many workers will need assistance adjusting. Many best practice approaches to transition safety nets are available, and should be adopted and adapted, while new approaches should be considered and tested.
  • Investing in drivers of demand for work. Governments will need to consider stepping up investments that are beneficial in their own right and will also contribute to demand for work (for example, infrastructure, climate-change adaptation). These types of jobs, from construction to rewiring buildings and installing solar panels, are often middle-wage jobs, those most affected by automation.
  • Embracing AI and automation safely. Even as we capture the productivity benefits of these rapidly evolving technologies, we need to actively guard against the risks and mitigate any dangers. The use of data must always take into account concerns including data security, privacy, malicious use, and potential issues of bias, issues that policy makers, tech and other firms, and individuals will need to find effective ways to address.

The report’s authors are:James Manyika chairman and director of the McKinsey Global Institute and a senior partner at McKinsey & Company based in San Francisco, and Kevin Sneader is McKinsey’s global managing partner-elect, based in Hong Kong.

You can read the full report online.