AI Job Futures: The Path to a Co-Pilot Economy

ByChase Banger

“The transformations that once appeared as distant futures now arrive at speed and scale.” 

So reads a line in the executive summary of the World Economic Forum (WEF)’s report, Four Futures for Jobs in the New Economy: AI and Talent in 2030. 

Much has been said about AI and how it can be used to change the future. Of work, of life, of the planet. In its report, the WEF outlines four job futures, ranging from dystopian to idealized. And AI heavily impacts each of them. 

“Considering the impact of AI alone, LinkedIn estimates that the demand for AI literacy skills has increased by 70% between 2024 and 2025,” the report says. 

By 2030, it’s projected to increase even more. The WEF report predicts four possible futures: two with bad outlooks for organizations because of a lack of workforce readiness, and two with positive outlooks thanks to widespread workforce readiness. 

Negative AI Outlooks: 

  • Age of Displacement 
    • “Businesses race to automate as a stopgap, displacing workers faster than education and reskilling systems can respond.” AI accelerates too quickly for workforces to keep up. 
  • Stalled Progress 
    • “Steady AI progress meets a workforce lacking critical skills.” AI’s potential goes unrealized because people aren’t able to harness it. 

Positive AI Outlooks: 

  • Co-Pilot Economy: 
    • “Countries and businesses that invested early in training, mobility, digital infrastructure and AI governance have created conditions to absorb and advance emerging technologies.” AI adoption and potential is measured and equitable thanks to training and policy. 
  • Supercharged Progress 
    • “Many jobs have disappeared, but new occupations emerge and scale fast, in part with humans directing portfolios of capable machines and becoming agent orchestrators.” AI scales quickly and displaces many, but new jobs are created in the meantime. 
A graph titled Four Scenarios for the future of jobs in 2030. There are two axes: the X axis is "workforce readiness" and the Y axis is AI advancement. Supercharged progress is plotted top right; age of displacement is top left; stalled progress is bottom left; co-pilot economy is bottom right.

Future of Jobs Scenario Summary

Supercharged Progress: 

  • The workforce transformation lives up to its hype, completely reshaping how business exists. Armed with AI tools and the ability to use them, productivity increases dramatically and the global economy becomes AI-centric. 
  • Jobs are rapidly displaced and, while new ones are created, too, social safety nets and governance aren’t able to keep up.  
  • Companies enjoy increased productivity but “displacement and job quality degradation are common across all sectors and geographies.” 
  • Labor productivity growth increases the most in this scenario. 

The Age of Displacement 

  • AI advances too quickly for the workforce. Companies displace workers and people can’t upskill fast enough. There’s an increase in productivity, but also a tear in the social fabric as people lose their livelihoods and buying power.  
  • The unemployment rate increases the most in this scenario. 

Co-pilot economy: 

  • AI-ready workforces meet the requirements of an AI-powered economy. Companies us AI to augment their workforces rather than automate them, and the ones who invest in upskilling early and often reap the greatest rewards. 
  • The unemployment rate remains steady in this scenario. 

Stalled progress: 

  • The global workforce lacks the necessary skills to take advantage of the promise of AI. Productivity gains are minimal or non-existent as companies struggle to hire or train for the skills they need to excel with AI. 
  • Manual occupations and skilled trades become more valuable as more workers leave white-collar careers. 
  • The S&P 500 operating margin—which the WEF uses as a benchmark for financial gains—remains flat in this scenario, as does labor productivity growth. 

Our Take on an AI Job Future: 

In either of the optimistic scenarios for businesses, upskilling and workforce skills reign supreme. AI has the potential to transform work as we know it—and already has had a lasting impact—but for businesses to truly realize its potential, they need to build workforce capabilities. And more importantly, with the pace of AI advancement, they need to be repeatable. Employees won’t just learn AI skills and then check the box; those skills will require consistent upkeep as the technology evolves. 

In the WEF’s best case for businesses, Supercharged Progress, companies who adopt AI and have the skills to wield it realize the largest productivity gains. But with huge workforce disruption and social security nets lagging behind, consumer confidence and spending will wain. 

The most desirable of the WEF’s predictions is the Co-Pilot Economy. In this scenario, measured AI progress aligns with humans’ abilities to use it, and the workforce (and consumer base) enjoys gains alongside firms. 

To realize that future, organizations need to focus on upskilling their employees beyond using AI as a job aid. They need those, too, in the form of YouTube videos, webinars, easily referenced online resources. But for the AI future that the WEF predicts, they need a deeper understanding of AI tools and their possibilities. 

Preparing for a Better AI Job Future 

The four futures in the report are transformative, and they’re predicted to come quickly. Organizations can start planning for each possibility today by setting up their workforce with the skills needed to thrive or, at least, survive. 

If there isn’t one already, an AI skill arms race is on the horizon, regardless of which AI job future we come to realize. Preparing your organization for this reality—and, importantly, treating your existing talent as your future AI talent—should be priority number one. 

Dozens of separate studies and reports have shown that hiring a new employee is more expensive than retaining an existing one. That goes especially for roles with high-demand skills, and that includes AI skills. When AI architects and prompt engineers have multiple offers from different companies, you’ll be glad you developed those skills internally. 

Assess Your Skills (and Skill Gaps)

Identify what AI skills already exist in your company, and identify the gaps. Unlike a traditional skill assessment, this one’s going to be a lot more lopsided toward gaps. AI is an emergent technology, at least insofar as widespread adoption, and so you can expect there to be significant gaps to start. This process will be messy and imperfect as jobs, titles and responsibilities evolve with the technology. But having a starting point is critical as you embark on developing learning pathways. 

Then, invest in education for your team. Not just lunch-and-learns and YouTube videos (although there’s value in these as well), and not just micro-credentials. Instead, focus on accredited, deep learning opportunities from institutions that have shown the ability to adapt curriculum for emerging technologies before. Just as importantly, make sure they’ve shown they can support adult learners. These learning opportunities—aside from being more prestigious and desirable for your employees—are how you can ensure knowledge acquisition rather than serve as reference materials. 

Read: How Skills-Based Organizations Redefine growth

Winning in an AI job future starts with building your company’s AI skills today. Whichever prediction, if any, comes to pass, your organization will have a competitive advantage if it has a strong roster of AI skills while others are scrambling for talent. 

Curious how SkillsWave can help your organization prepare for any of the WEF’s four scenarios through workforce development? Let’s talk.