“How do you educate students today for the jobs they’ll have tomorrow—when those jobs may not even exist yet?”
This was the perplexing question that senior edtech leaders responded to in a recent webinar titled “The Impact of AI and Preparing for Jobs That Don’t Yet Exist”. Hosted by John Barnshaw, VP for Education Success at labor market analytics company Lightcast, the forum also featured Dr. Lynn Letukas, Microsoft’s Director of Education Strategy, and Microsoft Technology Strategist Melissa Hortman, EdD.
The wide-ranging discussion touched on the ethical and social implications of AI in the context of higher education as well as how to equip students with “future-ready” skills. As noted by the group, the world has been suddenly inundated and disrupted by artificial intelligence in recent times. These game-changing circumstances are producing a sizable ripple effect throughout labor markets and the education and training sector.
“AI will reinvent every industry.”
- Melissa Hortman, EdD, Microsoft Technology Strategist
Didn’t we see this coming?
Futurists like Google’s Ray Kurzweil have been predicting a period like this for decades (in a 2006 interview with Computerworld, when asked about the future of IT professionals, Kurzweil replied, “The good news is IT is going to become more and more important. Ultimately, everything of importance will be comprised of IT.”).
Kurzweil didn’t mean every person will eventually work in a high-tech profession. But his remarks strongly (and accurately) predicted that the digital revolution would impact everyone’s jobs. Now that the time is here, educators must take note that this is only the beginning!
Meanwhile, for students who haven’t figured out what they want to do yet, this transformative phase in society’s evolution may feel daunting. At least for some. But for others, it’s predictable.
Today’s high school students, who fall under the category of “Generation Z,” are “the first true generation of digital natives,” writes Navigate360. “Born into a technological world, information has been placed at their fingertips and social media use has become the norm.”
For many (but not all) college-ready learners, the idea of a high-tech future seems like a no-brainer. Many saw the writing on the wall long ago. They recognize that they’ll probably need to excel at STEM subjects, at least to some degree, if they want to succeed in the future labor market. That includes learning about, or at least learning how to use AI.
Ready or not, AI is here
AI is already augmenting our daily activities in myriad ways and the pace is only going to pick up. From healthcare and finance to retail and manufacturing, AI is streamlining workflows and tackling huge chunks of labor-intensive, time-consuming tasks. It’s not only enhancing productivity and optimizing processes but also adding functionality and even contributing to creativity!
Employees in the near future will be expected to know how to augment their own roles with the help of AI tools. Those who can go a step beyond and learn how to innovate using AI will be able to distinguish themselves. All of this will require incorporating responsible AI principles and ethics as well as ensuring accuracy.
“AI doesn’t know when it’s wrong.”
- John Barnshaw, Lightcast VP for Education Success
Employees of the future will use AI as a tool, but they will still need to do plenty of quality control checking. As smart as AI seems, it will be many years before it can achieve parity with the human mind. Thus, humans have to constantly double-check the work of AI to ensure accuracy and non-biased output.
In the meantime, workers such as prompt engineers are striving to provide valuable inputs and feedback to AI models, training them to become better. This is just one of the many AI-related jobs that should grow in the coming years.
As John Barnshaw notes, numerous AI-related jobs don’t even exist yet (or at least, they don’t exist everywhere yet). He breaks these down into three categories in which they don’t exist—regionally, professionally, and currently. Let’s review what those categories mean.
3 categories where future AI jobs don’t exist yet
AI Jobs That Don’t Exist Regionally
Some AI jobs exist…but only in certain geographic regions at the moment!
For example, there are automobile manufacturing companies in some parts of the world using AI and other advanced technologies. Thus, they have AI-skilled workers on hand. But not every such company is using those technologies yet.
Requiring regional AI job skills creates a problem for learners and educators. It causes confusion about which job skills students need to work at such companies in general. An older workforce profile (on O*Net or the Bureau of Labor Statistics, for instance) might not list the types of advanced skills that appear in the regional job postings for companies using AI.
In other words, skills in an even slightly outdated career profile won’t always align with the current skills regional employers may list in their job ads on Indeed, et. al. This disconnect can cause learners—and educators—to misunderstand the importance of advanced job skills such as project management, automation, Python, mechanical engineering, etc., many of which require special training to obtain.
AI Jobs That Don’t Exist Professionally
Most professional occupations have at least some professional organizations to support them. Many also have standardized credentialing options that allow job seekers to quickly demonstrate to employers that they’ve completed training in a particular program and are qualified to perform certain tasks.
Unfortunately, some existing AI jobs have no such professional organizations or credentialing options!
There is no occupational professionalization of any kind for some roles. This puts employers in a bind because it can be difficult to gauge whether or not an applicant does, in fact, have the proper qualifications for the role. Simply holding a generalized college degree means very little when a company is hiring someone to do highly specialized tasks (such as AI-related tasks).
This wasn’t a problem a few years ago. In 2014, less than 0.6% of job postings in the US even mentioned the term “AI.” Now that has jumped to over 2%, quadrupling in under a decade. The term “Generative AI” skyrocketed from virtually zero appearances in job postings to over 1,500 within the span of only a few months. These trends are expected to continue.
In addition to AI terms, job postings are also listing in-demand hard skills related to machine learning, Python, computer science, data science, etc. Many of the companies hiring for these skills—especially generative AI—are in commercial banking, fraud detection, planning and consulting, and financial engineering.
AI Jobs That Don’t Exist Currently
We’ve looked at AI-related jobs that only exist regionally or in a non-professionalized manner. The third category is jobs (and associated skills) that don’t exist currently—but will in the near future!
In truth, the faster AI advances, the harder it gets for us to predict what’s going to happen next and what jobs will be needed.
To some extent, this falls in line with certain definitions of the technological singularity. “The technological singularity usually refers to a point in time where machines become intelligent enough to improve themselves, creating a runaway effect which is supposedly impossible to predict,” writes scientist Sabine Hossenfelder. “It’s called a singularity because of this impossibility to make a prediction beyond it, which is indeed very similar to the mathematical definition of a singularity.”
What we can predict, however, is growth. The tech sector in general is projected to grow by a whopping 17% in the coming years, with salary potentials growing to match. Some jobs are bound to grow even more than that.
As Lightcast notes:
Data scientist jobs may grow by 33%, with salaries ranging from $73,000-$131,000 per year (and an average of $98,000).
Information security analyst jobs may grow 30%, with salaries from $79,000-$131,000 (and an average of $102,000)
Computer scientist jobs may grow 22%, with salaries from $99,000-$164,000 (and an average of $131,000)
Computer and information systems manager jobs may grow 18%, with salaries from $118,000-$196,000 (and an average of $156,000)
The above is a sample of tech jobs requiring AI skills. It doesn’t cover the countless jobs that don’t yet exist, nor the non-tech jobs that will also utilize AI (and therefore require AI-related skills that tie into areas such as information technology, customer and client service, marketing, or even public relations).
Degree majors and AI jobs
As Boston Consulting Group’s Shifting Skills, Moving Targets, and Remaking the Workforce notes, about one-third of the top 20 skills requested by employers have changed in the past five years. Therefore it is vital that all workers commit to being lifelong learners in order to stay current and relevant.
“AI has rapidly impacted nearly
every facet of the labor market.”
- Dr. Lynn Letukas, Microsoft Director of Education Strategy
As for today, educators must help students recognize and learn the skills they’ll need for the future. Otherwise, they’ll be left out of in-demand jobs. As we wrote in a previous post, “A college degree can prepare students with the skills they need to land better-paying jobs than those who didn’t go to college. But just because it can doesn’t mean it will.”
Already, many of today’s graduates report that they went to school to get a good job, only to discover they didn’t learn the skills they’d actually need. This decline in satisfaction was noted by the Strada Center for Education Consumer Insights in their article Changing the Value Equation in Higher Education.
Students majoring in Visual and Performing Arts, English, History, Liberal Arts and Sciences, and Social Sciences were among the least satisfied in terms of how they viewed the career and cost values of their degrees. In contrast, Computer Science and Engineering majors found considerably more value in these areas.
Addressing the talent gap
Such reports contribute to the growing concern that the modern college experience may be overvalued for a huge percentage of students. They also alarmingly suggest that colleges may be failing to train future workers in sufficient numbers, which in turn will cause or exacerbate the projected talent gap crisis.
It’s already predicted that millions of jobs will be left unfilled by 2030 because of a lack of qualified, tech-skilled workers. But if that gap could be somehow filled before it’s too late, it would equate to ~$8.5 trillion of increased productivity added to the global economy by 2030. This could be done through investing in teaching skills of the future to current—and next generation—workforces.
The key is taking action now and ensuring students know what to study and that schools (or private companies) are providing such instruction. This leads us to the rising trend of credentialing!
Note, we are not just talking about certificates offered by colleges (which students can earn by taking a set number of associated college courses). We’re referring to third-party certifications granted by independent organizations (often companies) that specialize in assessing and verifying particular skills, knowledge, or competencies. These organizations are not affiliated with educational institutions.
For years, companies have offered credentialing programs to anyone who wants to sign up. Examples include Microsoft's Azure AI Engineer Associate or Azure Data Scientist Associate certificates. Such third-party certificate (or credentialing) programs empower learners with specific, concrete skills—and concrete proof of those specific skills. Employers who see credentials on a resume are more likely to view candidates as valuable assets.
Colleges and universities have long offered college credit to students who hold third-party certifications. But now many schools are going further, by allowing students to knock out third-party credentials as part of their degree programs. Ideally, this trend will continue and allow students in non-STEM majors to complete tech-oriented certifications. Why? Because, as Dr. Letukas points out, students in fields like social sciences may be the solution to the talent gap problem.
Enabling non-STEM students and workers with tech skills
Many tech jobs, in particular ones related to AI, require multidisciplinary skills that include both hard technical skills and soft skills linked to effective communications, understanding human behavior, ethics, and more.
Making it easier for non-STEM major students to earn tech-related certifications—and encouraging them to pursue such certifications—will ultimately be instrumental in bringing a much-needed diversity of skills into the tech sector of the future. It’ll also address the projected talent gap and provide employers with access to new talent pools possessing both the hard and soft skills they’re looking for.
“The main driver of change
in requested skills is technology.
Technology is reshaping many, if not most, jobs.”
- Boston Consulting Group
All this will require non-tech educators to start aligning curricula and goals to help achieve such key outcomes. In other words, they must look beyond traditional learning goals (that are becoming outdated and less valuable in the workforce) and expand upon them to include and synchronize with the future world of work.
In addition, recent graduate job seekers must be shown how to better explain their skills in resumes, during job interviews, and even during conversations with their social and professional networks. Tools such as skills or competency crosswalks, which compare skills, knowledge, and competencies between different jobs, will help identify such transferable skills and qualifications. Crosswalks can also help job seekers recognize how their skills may be relevant and applicable in different contexts.
Meanwhile, colleges and career navigation platforms can use (or create) crosswalks to articulate how the skills gained via non-tech majors translate to tech job requirements (i.e., what tech jobs can you get with what non-tech degrees, if combined with certifications). A good example is the role of the prompt engineer.
Case study: Prompt Engineers
“The hottest new programming
language is English.”
- Andrej Karpathy, former AI chief at Tesla
Prompt engineers work in a new field that didn’t exist until fairly recently, but there’s currently a high demand for them. As we recently wrote in one of our Gladeo career profiles, there is a generative AI race going on right now, thanks to the advent of OpenAI’s ChatGPT-4, Google’s Bard, Microsoft’s new Bing AI, and other competitors.
How do these AI programs function and get better? How do they “learn” to communicate more effectively? In part, through the hard (and patient) work of prompt engineers!
Within the AI field, there’s a subfield called natural language processing (or NLP). NLP essentially teaches computers how to learn and understand written and verbal messages in a way that’s similar to how humans learn.
Prompt engineers come up with text-based prompts that help train these incredible AI models.
The programs then use another aspect of AI—machine learning (or ML)—to analyze inputs and generate responses. As advanced as artificial intelligence is, it’s only that way because of the patient, behind-the-scenes work of prompt engineers and other NLP and ML experts. That’s why, at least for now, prompt engineers are being offered lucrative salaries.
Long term, that may not be the case, since AI will naturally get smarter and better able to generate its own prompts.
“These are jobs that probably only 500 people could do right now, so there are these insane salaries,” states prompt engineer Rob Lennon. “But in six months, 50,000 people will be able to do that job. The value of this knowledge is greater today than it will be tomorrow.”
In the interim, employers need tech-enabled prompt engineers who are also able to generate clear, concise, grammatically correct prompts that can help their AI models produce the right results. That’s why social studies and liberal arts students majoring in English or writing could be perfect candidates once they “level up” by taking the right classes and getting certified or otherwise credentialed!
As Microsoft CEO Satya Nadella said, “There is no better time to reimagine education and how technology can support that transformation.” We hope this article helps educators and stakeholders on their missions to empower students with future-ready skills via a reprioritization of outcomes and reimagination of curricula, activities, and academic counseling.
Addition resources mentioned in the Lightcast webinar:
AI Foundations: Imagine Cup Junior - a 1 hour, 34-minute learning path in four modules that introduces the fundamentals of artificial intelligence and how it's applied in everyday life.
AI learning and community hub - designed by Microsoft Learn to “help you get skilled up and ready to power AI transformation with the Microsoft Cloud. Build AI skills, connect with the community, earn credentials, learn from experts, and discover upcoming events.”
Get tips and tricks for teaching AI-900 Microsoft Azure AI Fundamentals - a 31-minute module about “preparing for your first teaching session, which labs to use, when and how to introduce technical topics, as well as other resources and materials.”
Introduction to Artificial Intelligence - a free LinkedIn Learning course by Doug Rose, “designed for project managers, product managers, directors, executives, and students starting a career in AI.”
Introduction to Azure OpenAI Service - a 1 hour, 3-minute module explaining the “connection between artificial intelligence (AI), Responsible AI, and text, code, and image generation. Understand how you can use Azure OpenAI to build solutions against AI models within Azure.”
Microsoft Azure AI Fundamentals: Get started with artificial intelligence - a 1 hour, 37-minute learning path in two modules, which helps students prepare for Exam AI-900: Microsoft Azure AI Fundamentals.
MS Learn for Educators - enables educators “to bring Microsoft Official Curriculum and the instructor-led training materials into your classroom to build your students’ technical skills for the future.”
What Is Generative AI? - a free LinkedIn Learning course by Pinar Seyhan Demirdag, AI Director of Seyhan Lee.