The Future of Work


For more than a century, the promise of stable work and respectable income drew workers to the factory floors and assembly lines of West Michigan. A high school diploma and willingness to put in a good day’s work were essentially tickets to the middle class for generations.

Not so anymore. As we learned in the years following the Great Recession – and witnessed in the span of just a few months during the COVID-19 pandemic – the world of work is changing at an ever-faster rate. Driven by artificial intelligence, automation and an increasingly global economy, this transformation is every bit as significant as the Industrial Revolution.

As automation increases, however, so does employer demand for the innately human qualities – communication, teamwork, problem-solving, flexibility – that help employees thrive in the modern workplace.

This is not the paradox it appears to be. Instead, it is an opportunity: a path for our region and state to take advantage of the modern workplace revolution so new generations can find their place and thrive in the new economy.

This report, a collaboration of Talent 2025 and Calvin University’s Center for Social Research, is intended as a tool to help advance on that path. The following dashboards are provided as public resources to encourage exploration.

We convened groups of stakeholders to make recommendations aligned to the Talent 2025 Working Groups. However, we invite all users to draw their own conclusions and take action needed to ensure our workforce is ready for the knowledge-based economy. 

Data, Research, and Insights

How Risk of Job Loss to Automation Declines

One irony of increasing adoption of automation and artificial intelligence is that the share of jobs deemed “at-risk” continues to shrink. That’s because jobs previously in the “at risk” category have shifted to become automated, while emerging jobs require increasingly specialized skills for workers to operate and monitor equipment.

The problem is not necessarily that robots will take over jobs. McKinsey makes it clear that the world’s economy will need every erg of human labor working to overcome demographic aging trends. The problem actually lies in the disappearance of low-skill jobs and greater emphasis on skills that are uniquely human — social-emotional skills, commonly referred to as soft skills.

We can look to other states to yield a probable 20-year trajectory for the rate at which low-skill jobs might be automated in Michigan. Our review of U.S. Bureau of Labor Statistics data shows the declining trend of automation risk in Michigan largely tracks the rest of the country over the 20-year period from 1998 to 2018.

Try selecting and comparing different geographies and occupations to see how automation risk varies over time. Hover over any point on the graph for more information. 

What’s interesting is that Michigan had the same level of risk for jobs lost to automation in 1998, at 62 percent, as the level faced in 2018 by the three most at-risk states, Nevada, South Dakota, and Alabama. In other words, three years ago, the states with the most risk were picking up where Michigan left off over 20 years ago.

Michigan’s risk has declined to 57.5 percent as recently as 2018 – nearly identical to the level of risk associated in 1998 with the three most-resistant states. As we approach the level of risk attributed to the lowest-risk states back in 1998, we can look to states like Maryland, Connecticut, and Massachusetts to plot a path forward. This helps identify which jobs will be most resistant to automation so we can determine the best methods to upskill and retrain our workforce in preparation for the impending future of work. 

Strong Correlation Between Soft Skills, Salaries, and Automation Risk

Using data from the O*NET database , we can see that occupations that place the greatest importance on soft skills also generally face the lowest risks of being automated and earn the highest average wages.

Try selecting and comparing different soft skills or occupation groups and hover over any bubble in the chart for more information. Then see the summary at the end of this section for some key findings we discovered.

Healthcare and Management occupations are two examples that rank extremely high in soft skills as well as average wages, while also facing the lowest risk from automation. Conversely, occupations in Farming or Production are associated with the highest automation risk, the lowest average salaries, and place the least importance on soft skills. 

Tracking the Growth of Soft Skill Importance

Considering how automation risk has declined in Michigan over the past 20 years, it should come as no surprise that the importance placed on soft skills has grown. The interactive below illustrates that in 1999, 36.1 percent of jobs in Michigan and 36.2 percent of jobs in the U.S reported that soft skills were “very important.” As of 2018, that share had risen to 37.0 percent in Michigan and 37.4 percent across the nation.

Try selecting and comparing across different occupation groups, soft skills, and geographies to review the gaps between “very important” vs. “not very important.” Hover over any point on the graph for more information. Then see the summary at the end of this section for some key findings we discovered.

Disaggregating this data to isolate specific skills — filtering by “measure” in the interactive dashboard — shows that the greatest growth occurred for jobs requiring adaptability/flexibility and stress tolerance. Meanwhile, skills such as innovation showed no signs of potent demand. 

Soft Skill Importance Varies by Sector

In the aggregate, the 16 soft skills (i.e., work styles) yield an average importance score of 3.9 out of 5 in both Michigan and the nation. Irrespective of geography or occupation, dependability is widely regarded as the most important soft skill for a majority of jobs. Importance scores can vary substantially when looking across occupational groups.

Try selecting different occupations and geographies to see how importance scores can vary. Hover over any bubble in the chart for more information. Then see the summary at the end of this section for some key findings we discovered.

As shown below, occupations in Community and Social Services generally place the greatest importance on soft skills — with an aggregated importance score of 4.3 out of 5 — while Agriculture and Transportation jobs place the least importance on workers possessing these 16 characteristics, with average importance scores of just 3.25 and 3.58, respectively. 

Depending on the nature of work performed in a specific occupational group, a skill that was critical in one sector could become entirely irrelevant in another, or vice versa. For example, innovation is the least important skill in the aggregate, with an average importance score of just 3.4, but its importance becomes greater than average when looking at Arts, Computer, or Education occupations. Compare the examples below for Education, Health Care and Computer occupations. 


What the Future Holds

The coming wave of automation will affect some of the largest occupational categories in the economy, including jobs in office support, food service, production, and customer service and retail sales. A common theme among shrinking roles is that they involve many routine or physical tasks, while jobs requiring both analytical and interpersonal skills show the greatest employment and wage growth in recent times. For individuals in disrupted industries who find themselves automated out of a job, adaptability and resilience will help them quickly shift to a different role that might not require similar hard skills, but where soft skills and knowledge of processes will help them gain a foothold.

The coming period of technological change will not reduce demand for technical skills. Humans will still require technical knowledge to interpret and contextualize autonomous outputs. Technology greatly enhances analytical capacity, but it cannot adapt or solve problems without human direction.

Soft skills are the true value add of human capital; they are uniquely human and cannot be replicated by automation.

Social-emotional, interpersonal, and cognitive skills will be critical for talent to remain competitive. Workers will be required to solve complex problems in fluid, rapidly changing, team-based settings.

Recommendations to Prepare for That Future

After collecting and reviewing existing research on the effects of automation, the core team behind the Future of Work project consulted with leaders in K-12 education, higher education, workforce development, and HR leaders to compile recommendations. These include the policy and programmatic changes that will be necessary in each sector to build a more agile and resilient talent base in preparation for this impending future of work.

These recommendations are summarized below. 

Early Childhood

Brain development and the emergence of soft skills are the greatest between the ages of 0-5. 

Recommendation: Increase the capacity of child care providers and invest in a well-trained workforce.

Recommendation: Ensure every child has access to a high-quality early childhood education prior to entering Kindergarten.

  • Increase the capacity of child care providers to serve working families who need care.
  • Invest in a well-trained child care workforce.
  • Expand access to quality preschool for at-risk families.

Recommendation: Emphasize the value of early childhood education with parents through a developmental screening to ensure children are developmentally on track 0-5.

Recommendation: Increase equity and funding for child care providers and pre-school programming that serve working families.

Recommendation: Increase the supply of infant/toddler child care slots in high-poverty communities or shortage areas.

Recommendation: Streamline literacy efforts from birth to 3rd grade.

K-12 Education

The development of soft skills should be emphasized as much as academic knowledge. 

Recommendation: Shift to flexible scheduling to allow students to manage their pace of learning, develop time management skills, and gain additional work experience during traditional school hours.

  • Address connectivity and transportation insecurities in rural and high poverty areas as a support strategy. We need to find a way to have students “present” so they can engage.
  • Identify and work with employers and content experts to design a framework for high school credit to be embedded in work experiences outside of traditional career-technical education.

Recommendation: Emphasize value of developing soft skills and establish methods to measure their development in students.

  • Support development of the assessment and then recognize and promote its value. What gets measured gets done and data becomes a point of reference to rally around.
  • Work with K-12, higher education and industry to create an acceptable “student profile” that highlights the totality of a learner, such as GPA, test scores, work habits, etc. Changing the transcript to what it can be will provide more value than GPA or standardized test scores alone.

Recommendation: Help educators to incorporate examples of occupations, careers and real-world problems. Use interdisciplinary project-based learning to mimic how adults use information to solve problems.

  • Provide educators with industry mentors to define relevant projects or problems.
  • Provide funding for training.
  • Incentivize and clarify that K-12 professional development should include teacher-to-industry work. This allows teachers to answer student questions of why they need to learn subjects.
  • Fund liaison personnel to connect business and schools. K-12 staff is already overwhelmed with competing priorities.

Recommendation: Incorporate examples of occupations, careers and mathematical problems encountered in the real-world in courses such as Applied Math, Accounting, Business Math, Financial Literacy or Personal Finance.

  • Provide educators with industry mentors to identify and define relevant mathematical projects or problems.
  • Include statistics and data analysis in some form – discernment is key with an overabundance of information everywhere.

Recommendation: Prioritize equity when providing opportunities for work-based learning and soft skill development to support at-risk students who may lack prior exposure and experiences.

  • Recognize that students come with varying degrees of exposure to soft skills. Frame student experiences in a positive manner to highlight skill acquisition and application.

Postsecondary Education

The development of soft skills should be emphasized as much as technical knowledge.

Recommendation: Emphasize the development and real-world application of soft skills in coursework, not just the accumulation of knowledge.

Recommendation: Eliminate the fear of failure in academic pursuits. Encourage and reward risk-taking and the learning that accompanies it.

Recommendation: Prioritize equity when providing opportunities for work-based learning and soft skill development.

  • Support at-risk students who may lack prior exposure and experiences.

Recommendation: Increase alignment of soft skills in coursework between K-12, post-secondary, and employers.

  • Increase communication between employers and educators on emerging technologies, industries, and occupations.
  • Publish and periodically update the soft skills that employers expect of employees by industry and occupation.

Recommendation: Accrediting bodies must become flexible to allow for shorter-term, micro-credential educational pathways.

Workforce Development

The development of soft skills should be emphasized in workforce training and development programs.

Recommendation: Include real-world opportunities to develop digital and soft skills in adult education and training programs.

  • Use contextualized learning to expose adult learners to real-world problems encountered in local, in-demand jobs.

Recommendation: Provide career path coaching to adults, aligning their career goals and the needs of employers.

Recommendation: Encourage employers to provide clearer demand signals by detailing the credentials and competencies required for employment in job postings and by publishing career pathways within their organizations.

  • Engage employers to evaluate and contribute to curriculum and training design to align programs to in-demand competencies, industry-recognized credentials, and career pathways.

Recommendation: Provide funding for short-term, stackable credentialing programs to encourage lifelong learning and to allow adult learners to accumulate in-demand knowledge and skills.

Recommendation: Incentivize employers to invest in upskilling their workforces.

  • Offer rapid attachment to employment as a component of learning through apprenticeships, internships, and work study positions.
  • Identify and publish career pathways, detailing competencies and credentials required for career progression.

Recommendation: Enhance Michigan’s ability to measure the effectiveness of education and workforce training programs by implementing Talent 2025’s seven recommendations (PDF) to improve longitudinal data systems.


Recommendation: Partner with K-12 and postsecondary education to encourage and support the development of soft skills among students.

Recommendation: Increase project- and work-based learning opportunities for K-12 and postsecondary students to gain real-world experience, explore careers, and develop soft skills.

Recommendation: Use skill/evidence-based hiring practices to identify transferrable skills of job applicants from other industries.

Recommendation: Invest in upskilling workforces to meet future demand.

Recommendation: Clearly define and communicate competency requirements to education and training providers and jobseekers through detailed job descriptions.

Methods & Acknowledgements

About This Project

The Future of Work project is a collaboration of Talent 2025 and Calvin University’s Center for Social Research. 

It began with a recognition that current outcomes for K-12 students are too narrow, while workforce development prioritizes re-employment. Even as the evolution of the modern workplace accelerates, it is clear we lack a long-term plan to develop our talent to meet emerging needs and changes in industry.

The first phase of the project brought together a core project team from leading companies and organizations. This team reviewed existing research and data on the effects of automation and other technologies. The second phase drew from recommendations of 32 focus group participants representing K-12, post-secondary, workforce development and employers.

An Ongoing Effort

The dashboards in the Data, Research and Insights section are interactive. These draw from 20 years of state-level data for 21 job sectors, more than 802 occupations, and 16 soft skills defined by the U.S. Department of Labor’s O*NET. 

Users are encouraged to conduct their own analysis by adjusting parameters for date range, geography, occupation, soft skills and more.

You also are encouraged to share your findings or explore how to get involved with advancing our recommendations:

Although statewide information is currently displayed in the interactives throughout the report, we are working to include detailed information for geographies as small as metropolitan statistical areas (MSAs) and should have the capability to report MSA-level data very soon. These customized outputs will be made available to interested parties for a nominal fee through Calvin University’s Center for Social Research. 

Additional Resources

An influential 2019 report by McKinsey & Company, “The future of work in America: People and places, today and tomorrow,” provides insights into the current state of hundreds of communities across the country. For example, it classifies Grand Rapids as a “mixed middle” manufacturing hub, part of a group it identifies as “America’s makers.” See the report .

For an overview of the importance of soft skills, see this report in Higher Ed Dive on how Kentucky colleges are embedding these skills into curricula. In the article, Aaron Thompson, president of the Kentucky Council on Postsecondary Education, explores the role of postsecondary education in developing and measuring soft skills.

To learn more about stackable credentials (which factor into some of our recommendations for post-secondary and workforce development), see these articles: