A new report from the McKinsey Global Institute (MGI) suggests that artificial intelligence and robotics could, in theory, automate more than half of all work currently done in the United States – and put around 40 percent of jobs in highly automatable categories – if companies fully redesign their workflows around intelligent machines.
In its study, Agents, robots, and us: Skill partnerships in the age of AI, MGI says that “today’s technologies could theoretically automate more than half of current US work hours”.
The authors stress that this is “not a forecast of job losses” but an indication of how profoundly work could change as “work in the future will be a partnership between people, agents, and robots – all powered by artificial intelligence”.
57 percent of work hours, 40 percent of jobs
The report estimates that “currently demonstrated technologies could, in theory, automate activities accounting for about 57 percent of US work hours today”.
At current capability levels, the authors say agents – software systems that automate non-physical work – could perform tasks that occupy “44 percent of US work hours today”, while robots could in principle handle “13 percent”.
McKinsey frames the impact in terms of tasks and “technical automation potential” rather than a simple jobs-lost headline.
Yet, buried in its occupational analysis is the figure that will attract political and media attention: at the most automatable end of the spectrum, “roles with the highest potential for automation by agents or robots… make up about 40 percent of total jobs”.
These are concentrated in legal and administrative services and in some physically demanding roles such as drivers and machine operators.
The report is careful to note that many of these jobs are likely to evolve rather than disappear outright. Tasks will be redistributed between humans, AI “agents” and physical robots, with people still needed “to guide, supervise, and verify”.
Charts show where the pressure lands first
Several of the report’s exhibits – which many news outlets are already reproducing – highlight where AI and robotics could bite hardest.
Exhibit 1 maps the US workforce by physical versus non-physical work. McKinsey notes that non-physical work accounts for about two-thirds of US work hours, and that the most automatable activities “represent about 40 percent of total US wages and span roles in fields from education and healthcare to business and legal”.
Exhibit 2 presents a 2×2 matrix of people, agents and robots, showing how much of today’s work could technically be handled by each.
In McKinsey’s framing, tasks occupying “more than half of current work hours could potentially be automated, primarily by agents”, but a large share of work that depends on social and emotional skills remains beyond current AI.
Subsequent charts classify roughly 800 occupations into seven archetypes – from “people-centric” roles to “agent-centric”, “robot-centric” and mixed people-agent-robot jobs – and show how much of the workforce falls into each.
People-centric roles, such as many healthcare and building maintenance jobs, remain largely human-led. Agent-centric and robot-centric roles, by contrast, overlap strongly with that “about 40 percent of total jobs” with high automation potential.
Skills changing, not disappearing
One of the central themes is that AI is more likely to transform how skills are used than to make most skills obsolete.
The authors say “more than 70 percent of the skills sought by employers today are used in both automatable and non-automatable work”, and later estimate that “roughly 72 percent of skills are required both for work that could be done by AI and for work that must be done by people”.
To track this, McKinsey introduces a new “Skill Change Index”, described as “a time-weighted measure of automation’s potential impact on each skill used in today’s workforce”.
Digital and information-processing skills are expected to see the biggest shifts, while “assisting and caring skills see the least change”.
The report highlights a core set of eight “high-prevalence skills” – including communication, management, problem-solving, leadership, customer relations and writing – that remain essential across industries.
These sit in the middle of the Skill Change Index distribution: they are widely used, partly automatable, and likely to be reshaped rather than eliminated as people “work more closely with AI-powered agents and robots”.
AI fluency demand jumps sevenfold
Employers are already changing what they hire for. Drawing on US job-posting data, McKinsey finds that demand for “AI fluency – the ability to use and manage AI tools – has grown sevenfold in two years, faster than for any other skill in US job postings”.
One of the report’s charts (Exhibit 7) shows that the number of workers in occupations where AI fluency is explicitly required has risen from around 1 million in 2023 to about 7 million in 2025.
Demand for technical AI skills is also rising, although more slowly. Another chart (Exhibit 8) shows that three-quarters of AI skill demand is currently concentrated in three groups – “computer and mathematical”, “management”, and “business and financial operations” – with relatively little demand so far in construction, transportation and food service.
At the same time, mentions of skills such as “general science and research” and “writing and editing” are declining in job listings, even though, as the report notes, these skills “remain essential for much of the workforce”.
$2.9 trillion prize – if workflows are redesigned
Beyond headline job numbers, McKinsey argues that the real economic story lies in redesigning entire workflows rather than bolting AI onto individual tasks.
In its midpoint adoption scenario, the report says “AI-powered agents and robots could generate about $2.9 trillion in US economic value per year” by 2030 – but only “if organizations prepare their people and redesign workflows, rather than individual tasks, around people, agents, and robots working together”.
A heatmap in Exhibit 14 shows that around 60 percent of that value sits in sector-specific workflows – for example, supply chain management in manufacturing, clinical diagnosis and patient care in healthcare, and risk management in finance – with the rest in cross-cutting functions such as IT, finance and administration.
To make this concrete, McKinsey includes case studies where agents and robots are already embedded in workflows:
- A global tech company uses multiple AI agents to qualify sales leads and schedule meetings, allowing human specialists to “spend more time negotiating and building relationships”.
- A large utility uses conversational agents to handle common customer queries, cutting the average cost per call “by about 50 percent” while humans focus on complex or emotionally sensitive issues.
- A pharmaceutical company deploys generative AI to draft clinical study reports, reducing “touch time for first human-reviewed drafts” by nearly 60 percent and cutting errors by around 50 percent.
- A regional bank uses AI agents to accelerate code migration and IT modernisation, with engineers shifting from manual rewriting to “planning, orchestration, and testing”.
Across these examples, managers move away from routine supervision and towards “orchestrating systems in which people, AI agents, and robots collaborate”, supported by new performance metrics and AI-related skills.
Partnership – or displacement?
The McKinsey report is explicit that its 57 percent and 40 percent figures describe technical potential, not a prediction that half of US workers will be out of a job.
The authors write that the estimate “reflects the technical potential for change in what people do, not a forecast of job losses”, and argue that “AI will not make most human skills obsolete, but it will change how they are used”.
However, by quantifying the share of work that could move to agents and robots – and identifying that “roles with the highest potential for automation by agents or robots… make up about 40 percent of total jobs” – the report gives policymakers, employers and workers a clearer view of where the pressure is likely to land first.
For the robotics and automation sector, the message is double-edged. On one hand, the numbers imply a very large addressable market for both physical robots and AI agents across white-collar and blue-collar work.
On the other, McKinsey insists that the biggest gains will come not from simple headcount reduction, but from “reimagining work itself – redesigning processes, roles, skills, culture, and metrics so people, agents, and robots create more value together”.
