The economy is changing fast. Driven by technology, 37% of the top 20 skills requested for the average US job have changed since 2016. And, according to a World Economic Forum survey, employers anticipate 23% “Labor market churn” in the next five years, “constituting a mixture of emerging jobs added and declining jobs eliminated.”
For institutions committed to their students’ career-readiness, this rate of change presents an obvious challenge. How do you create and maintain credentials (whether full degrees or shorter-term microcredentials) that prepare students for jobs that may not even exist yet?
Thankfully, as the rate of change in the economy has increased, so have the tools we have for understanding and tracking those changes. In a recent webinar with leaders from Microsoft, Dr. John Barnshaw (VP of Education Success at Lightcast) showed how different categories of labor market data, including real-time job postings as well as industry and occupation metrics, can help institutions spot emerging trends and anticipate demand for jobs that don’t yet exist.
In this article, we’ll summarize the three categories of “jobs that don’t yet exist” and outline Dr. Barnshaw’s recommended strategies for responding to each. Briefly, the three categories are:
Jobs that don’t yet exist regionally
Jobs that don’t yet exist professionally
Jobs that don’t yet exist currently
Let’s unpack what those mean, and then finish with four ways you can take action to ensure students are ready for the future of work.
Jobs that don't yet exist regionally
Just because jobs don’t exist in your region yet, doesn’t mean they don’t exist anywhere.
Similar to how the US is made up of states, “the US economy” comprises many regional economies – each with its own unique resources, challenges, and opportunities. Some of these economies are more likely to feel the effects of disruption and innovation within a particular industry than others. Those regions then become “bellwether economies” that can provide a preview of the skills and education learners will need to move into emerging fields and jobs.
For example, Barnshaw pointed to the recent explosion of electric vehicle (EV) manufacturing in Georgia. Using Analyst, we can see spikes in job posting activity within the Automobile Manufacturing industry in that state – and see that they began before production started, and continued to climb as production ramped up.
Even better, Barnshaw showed how those same job postings provide insight into the actual skills manufacturers are looking for, and how that demand compares with the supply of those skills in the regional workforce. This detailed breakdown shows that “human skills,” like Project Management and Process Improvement, are as in-demand as more technical skills like Python and Mechanical Engineering.
With this data, institutions anywhere in the country could anticipate the skills and competencies their students will need to compete for high-growth jobs in the emerging EV manufacturing sector.
Jobs that don't yet exist professionally
Sometimes, new fields emerge and start impacting the economy before they show up in traditional labor market information (e.g. what you’d get from the Bureau of Labor Statistics). In this case, we could say that a job doesn’t exist yet “professionally,” in the sense that it hasn’t yet formalized into a well-defined role with a standardized job title and official O*NET-SOC code.
For example: Want to become a nurse practitioner, civil engineer, or certified public accountant? These highly professionalized roles are relatively easy to track in labor market data and the educational pathways and credentials required to qualify for them are clear and widely understood.
By contrast, new and emerging jobs are notoriously non-standardized and harder to track. Because of this, new fields can emerge and start impacting the economy long before they show up in traditional labor market information (e.g. what you’d get from the Bureau of Labor Statistics).
So, how can educators see these changes coming and keep themselves, and their students, ahead of the curve? That’s where skills data shines.
As Barnshaw pointed out in his presentation, “As a field professionalizes, you can see in real time what skills are in demand.” This is possible because skills data comes from job postings, which are created, modified, and removed in real time according to employers’ staffing needs. Thus, skills data provides several unique advantages over other types of labor market information, including greater timeliness when it comes to spotting emerging trends and evolving occupations.
To illustrate, Barnshaw showed a Hot and Cold Skills report from Analyst that identified the fastest growing skills – in terms of job posting demand – related to “generative AI.” This data helps academic leaders and curriculum developers understand the core, fundamental skills (both technical skills and otherwise!) students can learn to set themselves up for success in an emerging field like “generative AI,” even before it's fully “professionalized.”
Importantly, these skill-based insights allow you to see not only new roles that are emerging, but also how existing roles are evolving or being disrupted. For example, Barnshaw found that the commercial banking industry has an unusually high posting intensity for generative AI, indicating strong interest in that skill set from that sector. Digging deeper, Barnshaw found opportunities for those with generative AI skills to apply for positions in everything from fraud detection to senior management roles at financial institutions.
Jobs that don't yet exist currently
At the end of the day, some jobs really don’t exist yet – not in any region or stage of professionalization. By definition, we don’t know what these jobs will be. They’ll likely come about as the result of some new technology, or new application of an existing technology, or some innovative service arising in response to an unforeseen need or challenge. In the absence of a crystal ball, what’s an institution to do about preparing themselves and their students for these jobs?
While we don’t know the future, we can use the recent past to create data-informed projections about what’s coming next. When doing so, it’s usually helpful to zoom out a bit and consider bigger picture trends. For example, we may not be able to pinpoint the exact jobs that students should be preparing for, but we can track which areas of the economy look promising through the lens of three fundamental metrics: salary, growth, and size.
Salary - As the spotlight on ensuring and measuring student ROI grows brighter, institutions can’t afford to ignore their students’ future earning potential. Not to mention the fact that it’s important to learners themselves: “Financial gain” was the fourth most popular response in a recent survey of over 9,000 alumni, asking about their motivation to enroll (#1 was “career success” and #3 was “required for my career aspirations”; both responses that may imply aspirations for economic mobility as well).
Growth - When considering the future, we have to think about trajectories. There are jobs that look appealing today in terms of wages and availability…but are projected to decline in the future. This doesn’t mean they aren’t worth pursuing! But it does mean students should be aware of their prospects, and may want to scope out other pastures before committing to a career path. On the positive side, there are also fields that make up a relatively small slice of the workforce pie today, but are growing rapidly (like AI!). As institutions work to serve students who may be anywhere from two to six or more years away from completing their education and entering the workforce, it’s imperative to keep an eye on which areas of the economy are growing (or shrinking).
Size - Looking at the size of an occupation or industry helps us determine how much opportunity there is for students to find work in that field. Some jobs may promise a plump payday, but not many openings to go around (NFL head coach is an extreme example, which pays an average salary of $6.6 million per year…for the 32 people that qualify). This is also an important data point for properly interpreting growth trends. An occupation might be growing by 100% year-over-year… but if there were only 5 jobs in your region to begin with, that isn’t necessarily a game changer for the local economy.
Looking at occupations and industries through these three metrics can help institutions, and their students, anticipate opportunities. Dr. Barnshaw showed an example, highlighting a range of jobs, from musician to cardiologist:
Next steps: Taking action to ensure student success
1) Adapt existing programs - Consider starting with what you already have. As we saw above, emerging jobs often begin as emerging skills or technologies before they become fully-defined occupations. If you already know the skills taught in your academic programs, you can more easily spot opportunities to add or update course content so it aligns with market trends. This may be as simple as adding a new topic to the syllabus (the course equivalent of a textbook revision), or could extend to adding a new elective to an existing major. These smaller, incremental adjustments are a good way to validate and build student interest while laying the groundwork for future investment and growth.
2) Create new credentials - In some instances, you may identify growing demand for a skill or bundle of skills that can best be taught in a sequence of courses. In that case, a new credential may be warranted. This might (eventually) mean “degree program,” but it could be wise to start with a non-credit continuing ed. program geared towards working professionals looking to rapidly upskill or reskill. Besides being more feasible to launch and scale quickly, non-degree credentials are often more adaptable and better suited to the kind of agile program management approach that helps institutions test, validate, and improve new program ideas.
Whether you launch a course, a microcredential, or a degree, try to pick a level of investment that matches the level of growth and opportunity evident in the data.
3) Advise & guide students (current and prospective) - The same market insight that helps your institution make program decisions can help prospective students make enrollment decisions. This is especially true of learners from underprivileged backgrounds whose personal experiences and networks may not expose them to the full range of career possibilities that higher education can unlock. You can empower individuals to make data-driven choices by embedding relevant career data directly into academic program pages, or by using a tool like Career Coach that closes the gap between career exploration and academic planning, allowing students to seamlessly transition between jobs data and relevant offerings at your institution.
4) Track alumni outcomes - As you start making these changes, you’ll want to ensure you have a system in place for capturing feedback and tracking learners’ outcomes. First destination surveys (FDS) are a great place to start and will offer the earliest possible signals of success. But more in-depth alumni surveys administered five or ten years after graduation can supplement FDS data with richer insight into the high impact practices that drive long-term career success. Online professional profile data, enriched by enrollment and transfer data from the National Student Clearinghouse, can also be used to track long-term alumni outcomes, and even help you discover alumni who may already be working in emerging fields like AI or EV manufacturing.
Conclusion
Planning for an uncertain future is tough, especially amidst a fast-changing labor market. But data can help eliminate the guesswork and create clarity for institutions and students alike – even where jobs don’t yet exist regionally, professionally, or currently. Insight into wages, job growth, job posting trends, and in-demand skills can all help institutions make decisions that support learners’ career success both today and tomorrow. And, when shared on program pages or career exploration platforms, can even help prospective students make data-driven solutions about which pathway to pursue.
To learn more, watch the full webinar on The Impact of AI and Preparing for Jobs That Don’t Yet Exist, or contact us if you have questions about using Lightcast data to inform your work.
