Periods of rapid economic growth have frequently followed moments when young people were able to gain in-demand skills. The post-World War II era in the United States is a prime illustration.
The GI Bill allowed millions of veterans to receive education and job training, which in turn helped fuel massive economic expansion. This influx of skilled workers into key industries like manufacturing and technology drove immediate productivity gains and innovation. Between 1945 and 1960, U.S. GDP surged from $228 billion to $500 billion.
This wasn’t just about increasing the number of workers; it was about aligning the right skills with the economy's needs. Training programs were tailored to real-world applications, such as automotive manufacturing and home construction—sectors vital for economic growth at the time.
These workers learned by doing, directly in the marketplace, which rapidly enhanced their ability to contribute meaningfully. This blend of targeted education, practical experience, and alignment with economic demands created a workforce that was not only ready to meet the challenges of the time but also drive an era of unprecedented economic growth.
The personal computer and networked computing era also saw a shift in how people acquired new skills. But instead of government-directed programs tied to national economic goals, people learned independently, through colleges, or through private sector training. While this led to significant economic growth, it may have meant that the benefits were not as evenly distributed.
Software and AI today make building future-ready skills accessible for everyone who can reach a computer with a reasonable internet connection. But the solution won't be in the format of education we are used to experiencing.
In recent decades, there's been a significant shift from valuing work experience as the foundation of career preparation to over-emphasizing academic credentials. This change has made higher education the main route to success, but it has also resulted in an oversupply of degrees that don't always align with market needs. While degrees, especially in liberal arts, hold inherent value, they often fail to provide the specific technical skills demanded by today’s rapidly evolving job market.
This disconnect between employer needs and workforce capabilities has left many graduates underemployed in jobs that don’t match their educational levels, and often saddled with debt that disincentivizes risk taking while redirecting consumer funds away from productive economic growth. This mismatch doesn’t just affect individual careers— it slows broader economic growth.
For all the talk about skills-based recruiting, hiring managers ultimately make the call on who to hire. And those hiring managers will continue to default to professional experience — which takes up 80% of one's resume or Linkedin — as a proxy to pre-assess skills.
I believe the takeaway is clear: real work experience, not just academic qualifications, is crucial for preparing individuals to meet the challenges of the modern economy.
The overemphasis on academic degrees at the expense of work experience has clear economic repercussions. A labor market crowded with degree holders who lack practical skills leads to underemployment and stagnant wages. Will the hiring manager prefer the graduate who knows the theory or the graduate who can execute with speed? Unless you work in a research or academic job, the choice should be obvious.
Workers without sought after skills in real-world experience struggle to command higher compensation and roles that bring more challenges and more learning opportunities. In turn, this dampens consumer spending which stifles economic growth. When workers aren’t fully productive, businesses can’t justify paying more, leading to reduced disposable income and lower consumption—critical drivers of the economy. The set of gears all work in concert.
Therefore, professional experience is vital, not just for individual advancement, but for broader economic health. If hiring managers prefer candidates with experience, then the pool of experience will primarily include those who already possess it. Ergo, experience will perpetuate itself within those who are already experienced.
There’s an opportunity to ignite an economic boom similar to the post-WWII era, but this time with a focus on future-ready skills like generative AI. Just as the post-war workforce was trained to meet the demands of emerging industries, today’s workers including those coming out of college can be equipped with advanced AI skills—prompt engineering, AI tool usage, and machine learning.
This training could democratize AI-driven productivity across all sectors, empowering employees of all backgrounds to perform tasks previously reserved for specialized engineers. As these skills become more widespread, companies will inevitably discover new ways to leverage this talent, sparking demand for roles that don’t yet exist.
The economic rationale is straightforward: new skills generate new capabilities, which then create fresh opportunities for innovation. However, this demand isn’t a given; it depends on how quickly businesses innovate, how fast consumers adopt AI-driven products, and broader market conditions.
For instance, if AI-driven products gain widespread consumer acceptance, businesses may rush to innovate, creating new jobs that utilize these capabilities. Conversely, slow adoption could delay the expected surge in demand for these skills. So far, the trend appears on track: Microsoft’s 2024 Work Trend Index says 66% of leaders wouldn’t hire someone new without AI skills, and 59% of Gen Z acknowledges the need to re-skill due to the prevalence of Gen AI according to Deloitte.
Widespread adoption of generative AI holds the potential to trigger an economic renaissance, marked by rapid innovation, increased productivity, and the development of products and services that were previously unimaginable.
While the post-WWII era provides a type of blueprint, the differences between that time and today are stark. Back then, technological advancements were broad, spanning multiple sectors like medicine and manufacturing.
More recently, networked applications, and now AI have become the aperture for much of tech's progress. The U.S. government once had centralized power to mobilize the economy, but today's fragmented regulation means market forces, not government, must drive the adoption of skills.
Higher education now faces bureaucratic inertia, hindering its ability to quickly adapt to technological shifts. Most universities struggle to provide practical, future-ready training, highlighting the need for a shift toward work experience-based learning.
In the private sector, focus on efficiency has led to a focus on hiring more experienced global talent rather than investing in training new graduates. This shift has decreased corporate investment in internships (down 7% year over year) and apprenticeships, emphasizing the need for a system that incentivizes company employees to participate in the development of Gen Z upskilling in professional experiences.
Systemic inefficiencies plague the current work experience model. Companies grapple with the high administrative burden of managing internships, limiting their capacity to offer meaningful training. These issues are compounded by manual processes and geographical constraints, reducing the availability and quality of work experiences.
Addressing these challenges requires more than government intervention. It calls for the creation of a scalable, technology-driven infrastructure that aligns the needs of students and companies. This new system must incentivize companies to make employee time more accessible for mentorship and upskilling through real-world projects.
By leveraging software, AI, and a unified platform, companies can streamline recruitment, training, and evaluation processes, engaging more students meaningfully. Such a system would ease the administrative burden on companies while ensuring that students gain the practical skills necessary for success in the modern economy.
Investing in future-ready skills has the potential to disrupt service industries that have traditionally concentrated earnings among a select few. Fields like high finance, corporate law, and traditional software engineering have long been dominated by individuals with prestigious degrees.
However, the democratization of knowledge through online education and practical training models embedded in real work experience can dismantle these barriers. Generative AI, with its capacity to automate tasks handled by highly paid professionals, will pave the way for new sectors where skill and innovation matter more than pedigree.
This shift could lead to a more equitable distribution of income and opportunities, making high-productivity industries accessible to a broader population.
But how can we incentivize companies to create more of these work experiences for young people that train future-ready skills, similar to how the GI Bill created a wave of government-directed training for the the economy of its day? This is where the Externship model that we've developed at Extern can build a scalable solution with win-win incentives.
Unlike traditional internships, which are limited due to laborious efforts required of employees, Externships are designed to provide low lift projects that engage employees and align directly with the needs of companies. By embedding students and early career professionals in actual work environments, Externships ensure that participants gain the skills that are most relevant to today’s economy.
The idea behind the Externship is analogous to MapReduce in software engineering in that it breaks down large, complex projects — that are normally out of reach for most students' abilities — into byte sized tasks for students. Just as MapReduce processes data in parallel across multiple nodes, the Externship model allows numerous students to work on different parts of a project simultaneously, contributing to a larger outcome. And as with MapReduce, the results are aggregated and refined into a final, coherent output that benefits the company employee.
Externships are particularly well-suited to the generative AI era. By offering hands-on experience in applying AI tools to real-world problems, Externships can help bridge the gap between academic knowledge and practical application.
This not only benefits the participants, who become more employable, but also the companies, which gain access to Gen Z insights across marketing, product, customer development, data analytics, R&D, and more. Here, the value of real experience becomes evident, as it prepares Gen Z to meet the demands of a rapidly changing economy.
The traditional internship model is plagued by inefficiencies. Companies must invest significant time and resources into recruiting, training, and managing interns, often without a clear return on investment. This fragmented approach limits the number of opportunities available and reduces the overall effectiveness of the experience for both the intern and the company. But what about all of the teams, at companies large and small, that would be open to working with students but don't have the time or resource to train and support them?
Externships streamline these processes by providing a unified platform that manages work experience programs for employees who have projects that are experientially out of reach for 99% of students. By automating administrative tasks such as recruiting, training, mentorship, feedback, and evaluation, Externships allow a single employee or manager to scale their own experiential learning program to hundreds of students for just a couple hours per month.
This not only increases the availability of work experience opportunities, but also ensures that these opportunities are accessible to a broader range of students and early career professionals. Real work experiences provided by Externships not only fill the skills gap but also enhance the productivity and innovation potential of the workforce.
Externships also emphasize the importance of practical, hands-on experience, which is often missing in traditional academic settings. By allowing students to work on real-world projects, Externships provide the kind of experiential learning that is crucial for developing future-ready skills. This not only benefits the students, who gain valuable experience and insights, but also the companies, which gain access to a pool of motivated, skilled Gen Zers who are ready to learn.
As the global economy continues to evolve, the need for practical work experience has never been more critical. The skills gap poses a significant threat to economic growth, but it is a challenge that can be overcome with the right approach. Externships offer a practical, scalable solution that aligns education with the needs of the market, ensuring that the next generation of workers is not only educated but also equipped to drive innovation and productivity.
By embracing the scalable, experiential work model of the Externship, we can address the inefficiencies of the current system, incentivize employees to help close the skills gap for young people, and unlock the full potential of the next generation. In doing so, we will not only boost productivity and economic growth but also create a more equitable and prosperous future for more new graduates who are feeling left behind in today's market.
Learn more about the case for inventing a new work experience model, the Externship, by diving deeper into the manifesto here: https://www.extern.com/manifesto
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