AI technology is nothing new. In fact, it’s been around since the 1950s. But something different happened with the launch of ChatGPT in November 2022. Unlike previous AI breakthroughs that were confined to research labs or tech companies, ChatGPT became the first widely adopted AI tool for everyday users. It took just two months to reach 100 million users—far outpacing the adoption rates of the telephone (75 years), the Internet (8 years), and Facebook (5 years).
Why? Accessibility. AI is no longer reserved for engineers and data scientists. Tools like ChatGPT are available to anyone with a computer or smartphone. No coding, no complex interfaces—just natural language inputs that allow users to engage seamlessly.
Another key factor is AI’s evolving capability. Today’s AI isn’t just about automation—it generates new, human-like content, from written articles to complex data analysis. The result? AI is becoming a general-purpose technology that will transform nearly every industry.
That transformation is already underway. AI investments are set to skyrocket, with 75% of companies planning to invest in AI within the next five years. Analysts predict AI-driven automation could impact up to 30% of work hours and 50% of tasks across industries. Goldman Sachs even estimates a 7% increase in global GDP over the next decade due to AI advancements.
As Bill Gates put it: “AI’s impact will be as big as the introduction of the PC. Word processing applications didn’t do away with office work, but they changed it forever.”
AI Won’t Take Your Job—But Someone Using AI Might
Some jobs will be eliminated, but more will evolve. Journalism is already seeing AI-generated content at scale. Basic coding, technical writing, and financial analysis are also shifting. But AI isn’t just replacing jobs—it’s transforming them.
Job postings reflect this shift. Consider these real listings from Indeed:
- Graphic Designer: “Familiarity with AI and ChatGPT technology.”
- Protein Sciences Research Scientist: “Experience utilizing artificial intelligence for protein design and related applications.”
- Content Writer & Researcher: “Proficiency in AI prompting and navigation.”
AI skills are no longer confined to tech roles. Job postings requiring AI proficiency have increased by 1,800% over the past two years. This follows the historical pattern of disruptive technology—just as the Internet revolutionized business in the 1990s, AI is now reshaping work.
Economist Richard Baldwin captured this reality: “AI won’t take your job. Somebody using AI will take your job.”
The AI Skills Gap: Employers vs. Higher Education
Here’s the problem: Employers want AI-ready talent but struggle to articulate what they need that talent to do. And higher education is struggling to keep up.
- Job postings remain vague. In the past year, 71% of postings mentioning AI included no details on what AI tools or skills were required. Companies struggle to define specific AI applications in their roles, leaving students and universities unclear on what to teach.
- AI skills are barely mentioned in entry-level hiring. Only 7% of entry-level job postings request AI-related skills, and most are for technical roles, leaving nontechnical fields behind.
- Higher education operates on a different timeline. Universities analyze job market data, but curricula and new degree programs evolve too slowly to keep pace with AI’s rapid development. Without clear employer signals, universities risk teaching outdated or irrelevant AI skills.
This disconnect is a missed opportunity. The organizations that successfully integrate AI into hiring and the higher education institutions that weave practical use cases into their curriculum will shape the future of work.
AI as a Case Study: The Need for Employer-Education Partnerships
We’ve seen successful collaboration before. Consider the accounting field, where the National Accounting Board works directly with higher education faculties to shape curricula based on industry needs. This ensures students graduate with relevant skills, reducing the learning curve for new hires.
The same approach is needed for AI. Employers and universities must work together to identify:
- Which tasks AI will automate vs. augment. For example, cybersecurity analysts used to manually evaluate phishing attempts. With AI handling detection, analysts now focus on broader security strategy.
- Where AI complements existing work. The World Economic Forum predicts that for data scientists, 35% of tasks will be automated, 55% augmented, and 10% unaffected.
Understanding these breakdowns across fields, disciplines, and jobs will help universities adjust their programs accordingly.
Bridging the Gap with Job Simulations
This is where Forage comes in. Job simulations offer a scalable, real-world solution to closing the AI skills gap.
Forage connects early- to mid-career talent with leading companies through virtual job simulations that reflect real employer needs. Instead of theoretical coursework, candidates engage in practical tasks—like learning how a company uses AI for data analysis, marketing, or coding.
For companies, this provides a way to signal AI skill requirements more clearly than traditional job postings. For the candidate, it offers tangible AI experience before entering the workforce. Talent walks away knowing what to expect before applying for the role with skills employers actually need.
Preparing for the AI-Driven Workforce
AI’s impact on the workforce is undeniable. But the transition won’t be smooth unless employers and universities collaborate to define AI competencies. The future of work won’t be dictated solely by AI’s capabilities—but by how well we prepare the next generation to use it.
