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The Emergence of the Augmented Workforce Economy
7 August 2026
Insights
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Explore how AI is reshaping the US workforce. Drawing on analysis of 1,870 occupations and 50,000 skills, this whitepaper examines which jobs are growing, which face automation risk, and where AI augmentation is creating new opportunities across the economy.
See an excerpt below, or download the full whitepaper.
The Future of Jobs in the US: A Macro View
QS Labour Market Intelligence shows that the US labor market is growing but is concentrated in roles where AI complements human capability. Over 60% of roles in our dataset of 1,870 different jobs are seeing growth of some sort through to 2030, and these high growth roles are the most likely to be augmented by AI. The inverse also holds – the roles with declining demand are at higher risk of automation.
Automation risk is concentrated in routine, rule-based work, which is also where wages are lowest. Task complexity drives a low automation score and higher median wages. Lower paid occupations, such as cashier ($32.4k median compensation) and fast-food worker (~$31.7k) have high automation scores of 3.5/5 or higher. Higher-paid professions, such as financial manager ($133.3k) and IT project manager ($119.9k) show low or moderate automation scores.
The relationship between AI exposure and growth is not perfectly linear. Automation scores are broadly similar across stable and growing occupations, suggesting that lower automation risk alone does not drive stronger demand. Instead, the clearest divide is between occupations in decline and those with stable or rising demand, pointing to a threshold effect. Once roles move beyond a certain level of automation risk, factors such as skill scarcity, productivity gains from augmentation and wider market demand become more important in shaping growth outcomes.
Growth will concentrate in cross-functional, AI-augmented roles, not traditional industries. Business intelligence analysts, marketing analysts and project management analysts are not beholden to individual industry performance, and consistently show strong growth, high augmentation and mid-to-high median wages. With this in mind, it becomes imperative to produce adaptive, systems-level thinkers.
Some roles – graphic designers, content editors, or logistic analysts – have both a high propensity for augmentation and automation. The routine elements of these jobs are at risk of automation, but the creative, interpersonal and judgement-based work can be augmented. It’s here that re-skilling matters most, where displacement can be avoided by integrating AI into workflows.
In effect, AI has the potential to enhance returns on human capability. The more a role depends on interpretation, creativity, or systems thinking, the more it stands to benefit from augmentation, and the more it is rewarded in the labor market.
We have weighted the data to minimize the impact of small-headcount roles – such as Head of State – to show a more accurate reflection of the overall workforces’ propensity for augmentation or automation.
Demand Is Concentrated in Augmentable Sectors
Overall demand remains positive, with no sector shrinking, but growth trends towards industries with higher augmentation, and is focused in sectors and roles that can absorb AI effectively. The focus, therefore, shifts to role design. Sector positioning matters, but the ability to restructure work around AI will determine where growth is sustained.
Conclusion
Higher Education
The labor market is shifting toward roles that combine expertise with the ability to work alongside AI. Growth is strongest in occupations that require interpretation, systems-level thinking, and cross-functional application, rather than narrow technical specialization or routine execution. This places pressure on curricula to move beyond static knowledge delivery toward adaptive capabilities, embedding data literacy, problem framing, and interdisciplinary learning across programs. It also elevates the importance of continuous reskilling pathways, particularly for roles where augmentation and automation overlap, and where workers must actively integrate AI into their workflows to remain relevant. Institutions that can tighten the feedback loop between emerging skills demand and educational provision will be best positioned to produce graduates aligned with future growth areas.
Employers
Workforce strategy is now defined by how effectively roles are redesigned to incorporate AI. Growth is concentrated in positions where AI enhances productivity without replacing human judgement, while routine, rule-based functions face greater automation risk. This creates a clear imperative to restructure work: separating automatable tasks from higher-value activities, and equipping employees to operate in augmented environments. The strongest returns will come from investing in hybrid roles - those that translate data into decisions or coordinate complex systems - rather than relying on traditional job definitions. Organizations that actively redesign roles and embed AI into workflows will capture productivity gains while mitigating displacement risks, particularly in roles where augmentation and automation pressures coexist.
