AI Will Touch 40% of Jobs and Widen Inequality, the IMF Warns: What the Fund's Analysis Really Means for Workers, Wages and Nations

Artificial intelligence is set to affect nearly 40% of all jobs around the world, according to a new analysis by the International Monetary Fund (IMF) — and in most scenarios, the Fund's managing director Kristalina Georgieva says, the technology will likely worsen overall inequality. Those two sentences, published in the IMF's findings and reported by BBC News on 15 January 2024, capture the uncomfortable core of what has become the defining economic debate of the AI era. The machine-learning boom that began with the surge in popularity of applications like ChatGPT is no longer just a technology story. In the IMF's framing, it is a labour-market story, a wages story, a distributional story — and ultimately a story about inequality both within countries and between them.

What makes the Fund's intervention significant is not merely the headline percentage. It is who is delivering the warning, when, and against what backdrop. The analysis arrived just as global business and political leaders were gathering at the World Economic Forum in Davos, Switzerland, where AI topped the agenda. Georgieva did not mince words: policymakers, she argued, should address what she called a troubling trend, in order to prevent the technology from further stoking social tensions. That is the language of an institution whose day job is macroeconomic stability — and it places AI squarely in the same category as the shocks the IMF was created to help countries manage.

An uneven map of exposure: 60, 40 and 26

The most analytically useful part of the IMF's work is that it refuses to treat the world as a single labour market. The Fund's numbers draw a sharply differentiated map of exposure to artificial intelligence, and the differences between the three figures are as important as the figures themselves:

1. Advanced economies: around 60% of jobs. The IMF said AI is likely to affect a greater proportion of jobs in advanced economies — put at around 60%. These are the countries with the highest concentration of white-collar, information-intensive and digitally connected occupations, precisely the kind of work that current AI systems are best at assisting with or performing.
2. The world as a whole: nearly 40%. Averaged across rich and poor economies alike, almost two of every five jobs globally are expected to feel the technology's impact in one way or another.
3. Low-income countries: just 26%. The IMF projects that AI will affect a much smaller share of jobs in the poorest economies — but, as the analysis makes clear, lower exposure is not the same as lower risk.

Read carelessly, the gradient from 60% to 26% could be mistaken for good news for the developing world: less AI, less disruption. The IMF's own commentary demolishes that reading. Georgieva noted that many of these countries simply do not have the infrastructure or the skilled workforces needed to harness the benefits of AI, raising the risk that, over time, the technology could worsen inequality among nations. In other words, low-income economies are not spared by the technology — they are excluded from its upside. The 26% figure measures contact with AI, not capacity to profit from it, and the gap between those two things is where a new global divide could open up.

For advanced economies, the mirror-image warning applies. A 60% exposure rate means that the vast majority of the workforce in rich countries will have to renegotiate its relationship with machine intelligence — through retraining, through changing job content, or through displacement. The IMF is explicit that in about half of those instances, workers can expect to benefit from the integration of AI, which will enhance their productivity. The other half is where the analysis turns sombre, and where policy, in the Fund's view, must move fastest.

Two faces of the same technology: augmentation versus substitution

The IMF's framework distinguishes between two fundamentally different ways AI touches a job, and the distinction is the analytical heart of the report. In the beneficial half of cases, AI acts as a complement to human labour: it enhances productivity, allowing workers to produce more or better output with the technology at their side. In the other set of cases, the Fund finds that AI will have the ability to perform key tasks that are currently executed by humans. That, the analysis warns, could lower demand for labour — affecting wages and even eradicating jobs.

This is why the 40% headline, taken alone, is close to meaningless. The same statistic contains two opposite futures. A worker whose tasks are amplified by AI may see their value to an employer rise; a worker whose key tasks are replicated by AI may see their bargaining power collapse. The distribution of outcomes — who lands on which side of the augmentation-substitution line — is precisely what will determine whether the technology delivers the productivity boom its advocates promise or the displacement its critics fear.

The IMF also identifies who is most likely to end up on the winning side. More generally, the analysis finds, higher-income and younger workers may see a disproportionate increase in their wages after adopting AI. Lower-income and older workers, the Fund believes, could fall behind. This is a crucial nuance: the inequality the IMF describes is not only a question of jobs disappearing. Even among those who keep their jobs and adopt the technology, the wage gains are expected to accrue unevenly — tilted towards the already well-paid and the young, who typically find it easier to absorb new tools into their working lives.

The policy implication is stark. If left to market forces alone, AI adoption could compound existing disparities: higher earners pull further ahead, older workers on modest incomes find their skills depreciating, and the social tensions Georgieva warned about become self-fulfilling. This is why the Fund's prescription, discussed below, is framed not as a technology policy but as a social policy.

The Goldman Sachs echo: 300 million jobs in the balance

The IMF's analysis does not stand alone, and its credibility is reinforced by convergence with earlier private-sector research. As the BBC noted, the Fund's findings echo a report from Goldman Sachs in 2023, which estimated that AI could replace the equivalent of 300 million full-time jobs — but which also argued there may be new jobs created alongside a boom in productivity. The two institutions, one public and one private, arrived at broadly compatible conclusions from different directions: massive displacement potential on one side, massive productivity potential on the other, with the net outcome depending on how quickly economies can convert the second into new forms of the first.

The pairing matters analytically for three reasons. First, it shows the 40%-of-jobs figure is not an outlier of institutional caution: an investment bank's research desk and the IMF's staff, working independently, are describing the same order of magnitude of disruption. Second, the Goldman Sachs framing keeps alive the optimistic counterweight — new jobs and a productivity boom — that a purely defensive reading of the IMF numbers would lose. Third, the convergence across 2023 and into January 2024 suggests that expert consensus on the scale of AI's labour-market impact was hardening well before most national policies had caught up with it.

What neither the IMF nor Goldman Sachs could tell policymakers is the speed of the transition. A 300-million-job-equivalent displacement spread over three decades is a manageable structural shift; compressed into five years, it is a social emergency. The Fund's emphasis on preparation — safety nets and retraining established in advance — is best understood as an argument that countries should act as if the transition will be fast, because waiting to find out would be the one guaranteed way to lose.

Davos as the backdrop: the moment AI became an economic-policy issue

Timing is part of the message. The IMF analysis was published as the World Economic Forum convened in Davos, Switzerland — the annual gathering where global business and political leaders set the tone for the year ahead. AI was a central topic of discussion there, following the surge in popularity of applications like ChatGPT, which had brought generative AI from research laboratories into everyday use within a remarkably short period.

That the IMF chose this moment to publish is itself an analytical signal. The Fund is not in the business of competing for attention at Davos; it is in the business of telling member states what the macroeconomic risks are. By dropping its inequality warning into the middle of the week when the world's economic elite were assembled, the IMF was effectively saying that AI could no longer be discussed as a corporate-strategy topic or a venture-capital thesis. It had become a matter of public economic policy — with all that implies for governments, finance ministries and social-protection systems.

The Davos context also helps explain the political temperature of Georgieva's language. Phrases like troubling trend and warnings about further stoking social tensions are calibrated for an audience of policymakers who can act. The IMF managing director was not predicting dystopia; she was describing a fork in the road and urging the people in the room — and the governments they represent — to choose the branch that leads somewhere more inclusive.

A tightening regulatory ring: Brussels, Beijing, Washington and London

The BBC's reporting situates the IMF's warning within a fast-moving regulatory landscape: the technology is facing increased regulation around the world, and by January 2024 the major economies had each begun building their own frameworks. Four developments stand out in the account:

• The European Union. In December 2023, EU officials reached a provisional deal on what was described as the world's first comprehensive laws to regulate the use of AI — a horizontal legal framework rather than a sector-specific patchwork.
• China. The country introduced some of the world's first national regulations on AI, including rules concerning how algorithms can be developed and deployed — an approach that reaches directly into the engineering layer of the technology.
• The United States. In October 2023, President Biden signed an executive order compelling developers to share safety results relating to AI with the US government — making transparency to the state a condition of operating in the world's largest technology market.
• The United Kingdom. The following month, the United Kingdom hosted an AI Safety Summit, at which a declaration on the safe development of the technology was signed by multiple countries — the first attempt to build a genuinely multilateral floor of agreement on AI safety.

Read together with the IMF's analysis, this regulatory wave takes on a different character. The EU, Chinese, US and UK initiatives are, in the main, safety-and-governance instruments: they are concerned with how AI systems are built, tested and disclosed. The IMF's contribution is about something the safety frameworks largely do not address — what happens to wages, employment and inequality once the technology is widely deployed. A country can have world-class AI safety regulation and still face the distributional shock the Fund describes, because the shock does not come from AI failing; it comes from AI succeeding at tasks that humans used to perform.

This is the analytical gap the IMF's January 2024 intervention exposed. Safety summits and comprehensive laws address the risks of the technology misbehaving. The Fund's 40% figure addresses the consequences of the technology working exactly as intended, at scale, across labour markets that were never designed to absorb such a transition. The two agendas — safety regulation and social adaptation — are complements, and by early 2024 only the first one had real momentum.

Georgieva's prescription: safety nets and retraining, before the shock lands

The IMF did not leave its diagnosis without a treatment. It is crucial for countries to establish comprehensive social safety nets and offer retraining programmes for vulnerable workers, Georgieva said. In doing so, she argued, we can make the AI transition more inclusive, protecting livelihoods and curbing inequality. The prescription has three components worth unpacking, each aimed at a different failure mode identified in the analysis:

• Comprehensive social safety nets — directed at the substitution half of the exposure: workers whose key tasks become performable by AI, whose labour demand falls, and whose wages or jobs are at risk. Safety nets convert what would otherwise be abrupt individual catastrophes into manageable, collectively absorbed transitions.
• Retraining programmes for vulnerable workers — aimed squarely at the groups the IMF singles out as most likely to fall behind: lower-income and older workers, for whom the disproportionate wage gains of higher-income younger adopters will not materialise automatically. Retraining is the mechanism by which workers move from the substitution side of the ledger towards the augmentation side.
• Inclusiveness as the explicit goal — the Fund frames the entire transition in distributive terms. The objective is not simply to ride the productivity boom the technology promises, but to ensure the boom is shared, curbing the inequality that, in most scenarios, the IMF expects AI to worsen by default.

What gives the prescription urgency is sequencing. Georgieva's call is preventive: establish the safety nets and offer the retraining now, before displacement has already destroyed livelihoods and before social tensions have been stoked further. The IMF's framing treats the AI transition as something countries can prepare for, rather than a weather event they can only endure. That is also an implicit judgement on the state of readiness in January 2024: the Fund would not be calling for comprehensive systems to be established if most member states already had them.

For low-income countries, the same prescription acquires an additional dimension. If, as Georgieva warns, many of these countries lack the infrastructure and skilled workforces to harness AI's benefits, then retraining and investment are not just social policy — they are development policy, and the risk that the technology could worsen inequality among nations over time is a risk that international institutions, including the IMF itself, have a direct mandate to help manage.

What the analysis leaves open

An honest reading of the IMF's January 2024 analysis must also note its limits — the questions it raises but does not answer. The Fund says AI will affect nearly 40% of jobs, but affecting a job is a deliberately broad category: it spans the office worker made more productive by an assistant tool and the worker whose tasks are entirely replicated and whose position is eradicated. The 60/26 split between advanced and low-income economies describes exposure, not outcome; the actual distribution of gains and losses will depend on choices — corporate, national and international — that had not yet been made when the analysis was published.

Similarly, the finding that higher-income and younger workers may see disproportionate wage increases is a projection about adoption patterns, not a law of nature. It describes what is likely to happen if policy stands aside. The Goldman Sachs counterpoint — new jobs emerging alongside the productivity boom — remains the unquantified variable in the equation, just as it was in the earlier report. And the speed of everything, the variable that most determines whether this transition is a structural adjustment or a social crisis, is the one thing no institution in early 2024 could credibly forecast.

What the IMF did accomplish was to move the debate from speculation to measurement. By January 2024, the question facing governments was no longer whether AI would transform labour markets — the Fund, an investment bank's research division and the Davos agenda had all converged on the answer to that. The question became what the transformation would do to inequality, and what states intended to do about it. Georgieva's warning that in most scenarios AI will likely worsen overall inequality is not a prophecy; it is a description of the default path. The IMF's message to the policymakers gathered in the Alps and to everyone else is that the default path can be changed — but only by countries that build their safety nets and retraining programmes before the 40% becomes a lived reality for their workers.

Based on reporting by Annabelle Liang for BBC News, 15 January 2024.