WASHINGTON – The Office of the United States Trade Representative (USTR) will hold public hearings starting on Tuesday, July 7 and continuing through Thursday, July 9, regarding proposed responsive action in the Section 301 investigations of the acts, policies, and practices, of 60 economies related to the failure to impose and effectively enforce a prohibition on the importation of goods produced with forced labor.
The hearings will be held at the U.S. International Trade Commission (500 E Street SW, Washington, DC) starting at 10:00 am ET.
Please consult the USTR website for the hearings schedule.
Note: The hearings are on the record but no external cameras or video recording will be allowed in the hearing room. The hearings will not be livestreamed. A full transcript of the hearings will be posted on ustr.gov after the hearings. Please contact media@ustr.eop.gov with questions or for more information on media arrangements.
 
 
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The European Commission has presented a plan to address the risks and harness the opportunities of advanced artificial intelligence (AI) in cybersecurity.
While the AI can improve security, it can also be misused to identify vulnerabilities, automate attacks, and significantly increase the scale and speed of cyber incidents. The new plan will bring together EU countries, industry, and EU-level organisations to strengthen the cybersecurity of our digital landscape against the vulnerabilities posed by advanced AI.
Key actions

Evaluating AI models: The AI Act requires advanced AI models to be evaluated and their risks to be assessed before they are placed on the EU market. The Commission will help establish an EU evaluation capacity to strengthen third-party assessment of AI capabilities and risks globally, supporting the regulatory function of the AI Office.
Accessing advanced AI models: Europe needs clear and transparent conditions for accessing the most advanced AI systems. The Commission will work with the EU Agency for Cybersecurity to define a European blueprint for structured access to advanced AI capabilities for cybersecurity, supporting public and private organisations in accessing advanced AI models.
Testing AI for cybersecurity: The EU Agency for Cybersecurity and the Commission’s Joint Research Centre will create a secure platform to test AI for cybersecurity, including using simulated environments. This will bring know-how on the safe use of AI to operators in critical sectors.
Reinforcing the EU’s cybersecurity and fixing vulnerabilities: The EU must protect its critical infrastructure. In line with the EU’s cybersecurity rules, organisations should intensify cyber hygiene practices, risk management measures, and security by design principles. They should also start using available AI capabilities to fix vulnerabilities faster, as well as prevent and respond to cyberattacks. EU Agency for Cybersecurity will assist them in this transition, including guidance, recommendations, and best practices, as well as a campaign to secure critical open source software.
Scaling European AI capabilities for cyber: The EU must continue investing in its own advanced AI capabilities. For this, the AI Factories and future Gigafactories infrastructure and the European Tech equity capacity, announced in the Tech Sovereignty Package, are available. The Commission will also launch the EU Grand Challenge on AI for cybersecurity, bringing together companies, researchers, and organisations to develop AI solutions for cybersecurity and support the growth of the EU market.

The new plan aims to strengthen the EU’s cybersecurity framework. It builds on existing EU rules, including the AI Act, the Cyber Resilience Act, the Network and Information Systems Directive, and the Cyber Solidarity Act.
 
 
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Long list of downstream products added to carbon border adjustment mechanism (CBAM)

Tougher anti-circumvention rules to prevent abuse

A temporary decarbonisation fund to protect EU firms in export markets

Environment Committee MEPs have backed extending the EU’s carbon border adjustment mechanism to downstream goods and setting up a fund to support industry’s low-carbon transition.

The Committee on the Environment, Climate and Food Safety adopted its position on proposed changes to the CBAM by 56 to 11, with 12 abstentions.
The MEPs agree with the Commission’s proposal to extend the scope of CBAM beyond basic materials to a long list of downstream products – finished steel and aluminium goods such as fasteners, wire, springs and household articles – but insist it must be based on transparent, quantitative methodologies. They also added an exemption for electricity flows from non-EU countries used by grid operators to keep networks stable.
Closing loopholes
On anti-circumvention rules, the MEPs clarified that the practice of “slightly modifying” goods must also cover slight processing and tightened the rule so it targets only arrangements set up purely to dodge CBAM, and not normal business decisions to lower a company’s costs.
They also empowered the Commission to apply the true country of origin’s default values where a pattern of circumvention is found. They deleted the Commission’s proposed safeguard that would have allowed goods to be removed from the scope in the event of price shocks.
The committee also wants new rules for online sales to close an online imports loophole. It recommends a single weight-based limit be applied to a seller’s shipments as a whole, rather than parcel by parcel, with new reporting duties, and retroactive liability for shipments that are split to stay under the threshold.
Finally, the MEPs propose simplified reporting for least-developed countries and a technical assistance framework, but removed the Commission’s option to count Paris Agreement Article 6 carbon credits against CBAM obligations, since this issue is likely to be discussed in the context of the upcoming revision of the EU emissions trading system (ETS).
Temporary decarbonisation fund
The Environment Committee also adopted their position on the related temporary decarbonisation fund (TDF) to protect EU producers on export markets, by 59 votes to 16, with 6 abstentions.
The MEPs want financial support from the TDF to run from 2027 to 2029 and not only from 2028 as proposed by the Commission. As fertilisers are a strategic input for food security, they also want to open the fund to fertiliser producers and downstream users facing higher carbon-related input costs, with products such as urea, ammonium nitrate and ammonium sulphate added to the list of eligible goods.
Finally, all downstream operators – firms that use CBAM-covered goods as inputs in their production – should be eligible for support from the fund, while leftover revenue could be redirected to the EU’s international climate finance commitments under the Paris Agreement instead of being returned to member states, as the Commission proposed.
Quotes
CBAM rapporteur Mohammed Chahim (S&D, NL) said: “This compromise makes the CBAM stronger, fairer and more resilient. We have closed important loopholes, strengthened enforcement against circumvention, and expanded the mechanism’s scope where it matters most. It is a balanced package that protects European industry as it decarbonises while safeguarding the environmental integrity of the mechanism.”
Rapporteur for the temporary decarbonisation fund Pascal Canfin (Renew, FR) said: “Today we have taken a big step towards making Europe a safe place for investment in decarbonisation: we are broadening product coverage to enhance the level playing field and we are setting out stronger anti-circumvention rules, notably against resource shuffling from China. We are also offering a more robust solution for our farmers hit by fertiliser costs, and an export scheme to protect our companies on export markets where their competitors do not pay a carbon price.”
Next steps
Parliament is scheduled to adopt its mandate for negotiations with EU member states on the final shape of the bill during the September plenary session.
Background
The EU’s carbon border adjustment mechanism is the EU’s tool to equalise the price of carbon paid for EU products operating under the ETS with that of imported goods, to reduce the risk of carbon leakage and to encourage greater climate ambition in non-EU countries. In 2025, Parliament adopted simplification measures to exempt 90% of importers from CBAM rules while still maintaining climate ambition, as 99% of CO2 emissions are still covered.

 
 
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Interview with Les Échos conducted by Guillaume Benoit and Christophe Jakubyszyn on 24 June 2026

On 11 June, the ECB raised its key interest rates. Do you still think that was the right decision, given that just ten days later Iran and the United States agreed a 60-day ceasefire?
We are confident that we made the right choice. As early as April, a large majority of Governing Council members were already prepared to take a decision. But at that point we still didn’t have all the necessary information.
All the data we have received since then have confirmed our analysis. We are facing an external supply shock that is currently spreading to the rest of the economy and whose indirect effects we can already see. We are also keeping a close eye on the risk of second-round effects, even though they have not yet materialised.
What form are these tensions taking?
Inflation excluding energy and food is accelerating, rising from 2.2% to 2.5%. This is partly due to services prices, which have increased by 3.5% as compared with the 3% that was projected. When you have rising inflation, rising services prices and inflation projections of 3% for 2026, 2.3% for 2027 and 2% for 2028, the monetary policy decision seemed clear.
And this holds true even under the more favourable scenario (the war ending, the Strait of Hormuz reopening quickly, a fall in the oil price…), which we considered in addition to two other scenarios – adverse and severe – that we presented back in March.
Isn’t there a risk that this monetary tightening could slow the economy too much?
We only lowered our growth forecast by 0.1 percentage points, from 0.9% in March to 0.8% in June. The unemployment rate is close to its historic low and labour force participation continues to increase – more slowly, admittedly, but it is still increasing. The financial sector is robust, with well capitalised banks and no known risk of significant financial instability. I have to say that we considered lowering our growth forecasts a little more. But the national central banks, who contributed to the June economic projections, saw sufficient signs of growth in activity.
Should we expect further tightening at one of the upcoming meetings?
I honestly don’t know. At the end of each monetary policy meeting, during the press conference, I repeat the same line. We take a decision at each meeting, based on our assessment of the inflation outlook and the risks surrounding it, the incoming economic and financial data, the dynamics of underlying inflation and the strength of monetary policy transmission. As I have said before, I have a general sense of the direction we will take, but the facts will guide us within our monetary policy framework, which is very clear.
You said recently that the renminbi was undervalued. Do you think we’re on the cusp of a new currency war between China, the United States and the European Union?
It’s certainly the case that there are excessive current account imbalances. That does not necessarily translate into a currency war. But when some estimates of the International Monetary Fund conclude that the renminbi is undervalued by around 16%, you have to take the issue seriously, even if these estimates are subject to a degree of uncertainty. If Heads of State or Government decide to address the problems of current account surpluses, the Chinese will inevitably have to be part of the discussion.
What role can Europe play between the Americans and the Chinese?
Europe is often still described as a giant with feet of clay, even though we are a large economy with 450 million consumers, 360 million of whom are in the euro area. We have untapped productivity reserves and innovative capacity that have yet to be fully exploited. And above all, we have significant amounts of dormant savings – around €35 trillion – far too little of which is being invested in Europe!
It’s imperative that we take action, rather than just enduring. If we act on the fifteen or so major reforms set out in the Draghi report, in combination with the Letta report – which aims to create a genuine internal market by removing as many barriers as possible – we will be much stronger.
The European Parliament’s Economic and Monetary Affairs Committee has given the green light to the digital euro. What will this mean for citizens?
Merchants, who typically pay a fee to the generally foreign-owned operators of international card schemes or other payment networks, will pay much less. Because the ECB, as a central bank, is not looking to make a profit.
And individuals will be able to use the digital euro at all points of sale, on all e-commerce sites, and even for person-to-person payments, just like euro coins and banknotes. Additionally, a foreign power won’t be able to deprive them of their means of payment! I’m thinking in particular of the French judge Nicolas Guillou, at the International Criminal Court, who can no longer use his payment cards operated by foreign companies, simply because the US Administration sanctioned him for authorising the arrest warrants against the Israeli Prime Minister, Benjamin Netanyahu.
Are there no reservations?
We have put a lot of effort into explaining it, and we must continue to do so, because this is a project that isn’t easy to grasp and populists won’t hesitate to exploit it. For example, they are claiming that your employer will have to pay your wages in digital euro, that the government will thus be able to monitor all your spending and that, with a “programmable” euro, you could be prevented from spending your money as you see fit. That’s science fiction, it’s Big Brother reinvented, but it’s not true!
The banks have called for a cap on digital euro holdings. Are they right to be concerned that it could drain the deposits that are essential to their monetary power?
Even assuming that everyone over the age of 14 had a digital euro account and was always at their holding limit – which has not yet been determined but is expected to be around €3,000, maybe higher – the total outstanding amount would be minimal compared with total deposits in bank accounts. And we should not forget that the mechanism we have designed requires the intermediation of banks. They are the ones who will offer you this “central bank” euro account, just as they offer card services or systems using the networks of major international operators.
Let’s talk about financial stability. Are you concerned about the levels of public debt?
Looking at the public debt of Member States – in my case focusing on the debt of the euro area – we are at around 88% of GDP. We are indeed not within the prescribed limits. And there are significant divergences between, on the one hand, countries such as Greece, Italy, Belgium and France, and, on the other, Luxembourg, Estonia and Ireland. Clearly, there are public debt and indebtedness trajectories within Member States that need to be monitored very closely – and, in some cases, corrected. But I take a consolidated view for the euro area. So no, I am not concerned, provided that commitments are honoured.
Do you think that France’s main handicap today is its fiscal situation?
It is above all its inability to reform. I am not saying that the fiscal situation is not serious, but the main challenge is being unable to carry out structural reforms, which, if successfully implemented, would improve the fiscal outlook.
Do you see any risks that are not being sufficiently taken into account at present?
Yes, I do. Artificial intelligence is a source of productivity gains and opportunities, but it also poses a major risk.
For about a decade now we have been talking about cybersecurity risks, hacking, data theft and so on. But with the acceleration and deepening of AI models, we are confronted with a much more serious risk. Because it is happening very, very quickly, and because the means of defence – and the funding required for them – have yet to be found.
Were you worried by the US Government’s provisional decision to make the Mythos 5 and Fable 5 systems available only to US nationals?
Europe is on the back foot: those who can test these tools gain a competitive advantage and are better able to protect themselves against their malicious use. We need an international framework, because one party’s vulnerability ultimately becomes everyone’s vulnerability.
At one point, you strongly advocated the view that monetary policy should also have a social and environmental component. Have you succeeded in this?
Yes, I believe that the European Central Bank, within the limits of its mandate and its roadmap, must urgently address the dual issue of climate change and biodiversity conservation.
Failing to take climate change into account when drawing up macroeconomic projections means that you miss out on factors that will be decisive for growth and inflation. Climate change is now incorporated into our macroeconomic projections and, accordingly, into the models we work with.
And secondly, we also need to incorporate this into risk management. When we allow banks to obtain funding from us and then to grant loans, we need to know the value of the claims they provide as collateral. In simple terms, if the collateral consists of a mortgage loan on a property located in a flood-prone area or on a cliff-edge, it is probably worth significantly less than its stated value. We now apply this type of haircut to new refinancing requests.
There has been a lot of conflicting information about your possible early departure. So, how long will you continue to serve as President of the ECB?
My term runs until October 2027. And I see my mission as ensuring price stability. Given that we are once again going through a turbulent period, I believe the captain of the ECB ship must stay on board.
Does this mean that if the waters calm down, you do not rule out the possibility of leaving earlier? For example, if you wish to take part in the French political debate in 2027?
It’s possible. I believe that a European voice needs to be heard in the French presidential debate.
If this debate were to reveal a more limited vision of France’s place within Europe, I think it would be necessary to explain why that would be a painful path for our country and for our fellow citizens.
You are not ruling out, in the coming months, in your capacity as ECB President, having a frank discussion with some of the candidates?
That is certainly possible.
What would you say to them?
I would speak with a French and a European voice, because I am profoundly both. I would tell them that France must play a decisive role in the economic future of our continent. And that without this European environment and anchoring, our economic prospects would, at the very least, be unclear.
France will have to take courageous decisions on difficult issues. Candidates in the presidential election have a duty to address these issues and to propose solutions. And, contrary to what I often hear from politicians, the French are fully aware of the situation, and they expect a candid discussion along with concrete solutions.
Given the political context, and the possibility of extremist parties gaining power, might you at some point consider getting involved in the campaign, to support a candidate, or even to stand yourself?
I will reflect on it.
You will reflect on it?
No, I’m joking. I don’t think that’s currently on the agenda.

 
 
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Policy choices will determine whether tokenized finance strengthens or fragments the financial system.
Tokenization is often described as a technological upgrade enabling faster settlement, cheaper payments, and programmable assets. But it is a lot more.
When financial assets and liabilities move onto shared digital ledgers, the structure of the financial system itself changes. Processes that today occur sequentially — execution, clearing, settlement —can now happen simultaneously, governed by software rather than institutional processes. Risk could migrate away from the balance sheets of institutions such as banks and investment funds towards the companies managing services and market infrastructures. The potential points of failure could change, so the policy frameworks must adapt accordingly.
Our research shows that policy choices made now will shape whether tokenization strengthens or fragments the financial system. Additional work goes deeper into new trends in payments and asset tokenization and how financial market infrastructures will evolve in a tokenized economy.
What really changes?
Payments, securities, and derivatives have been digital for decades, but they still run on centralized databases and sequential processes. Instructions are transmitted, trades are matched, settlements are delayed on purpose, and reconciliation follows. These frictions add cost and time but provide buffers, safety, and liquidity management, by allowing time for intervention in moments of stress or errors.
Tokenization goes a step beyond simple digitization by embedding ownership and transfer directly within the asset itself. When a tokenized asset changes hands, smart contracts can execute trades, transfer ownership, and move payments simultaneously — all on a shared ledger. Processes that once required days of clearing and reconciliation are now completed in moments.
Frictions disappear — but so do buffers. Liquidity demands materialize in real time, collateral calls can be automated, and failures can propagate faster than institutions or supervisors can respond.  Risk that once were borne by the balance sheet of individual institutions behind a transaction become increasingly concentrated in the platforms and code that govern these transactions.
This shift fundamentally challenges a system built around reconciliations, reporting cycles, and delayed settlement.
Settlement in a tokenized world
Every financial system depends on a core settlement asset. Traditionally, that role has belonged to central bank money — in particular, the risk-free reserves that financial institutions hold at the central bank. Tokenization reopens this question by enabling multiple forms of digital money to circulate on shared ledgers. Three forms are emerging.

Tokenized bank deposits are a new digital representation of an existing liability — the commercial bank deposit — and inherit its regulatory and institutional framework. Programmability enables atomic (simultaneous) settlement and more efficient liquidity management. But continuous settlement reduces banks’ ability to react to unforeseen circumstances, heightening the importance of real-time liquidity backstops.

Stablecoins offer programmability and global reach, but they rest on a promise: par convertibility with other forms of money. Maintaining that parity depends on reserve quality, market liquidity, and issuer resilience — and even fully backed stablecoins have been vulnerable under stress.

Tokenized central bank reserves eliminate credit risk in the settlement asset itself. But they require central banks to operate — or closely govern — new programmable infrastructures, extending their operational role well beyond traditional payment systems. How much functionality to embed in public platforms, and how much to leave to the private sector, remains an open and consequential design choice.

Banks will change, not disappear
Tokenization does not eliminate banks. It changes how they fund themselves, manage liquidity, and bear risk.
On the liability side, tokenized deposits unify payments, client settlement, and treasury functions on shared ledgers. On the asset side, tokenized lending allows rules — interest accrual, collateral triggers — to be embedded in smart contracts. Risk monitoring becomes continuous, allowing timely enforcement.
Capital markets face a similar transformation. Tokenized securities compress issuance, trading, settlement, custody, and compliance into integrated workflows. Counterparty risk declines, but liquidity demands become continuous. Automated redemptions and margining can improve efficiency in normal times—and accelerate stress in periods of market strain.
Collateralized markets may be among the earliest beneficiaries. High‑quality assets can be mobilized quickly and across platforms. But when infrastructure becomes the central hub, governance failures become systemic events.
Efficiency meets concentration
Permissioned shared ledgers concentrate activity on fewer platforms. This consolidation improves liquidity and efficiency, but amplifies the importance of operational resilience, cybersecurity, and crisis management.
Interoperability is equally critical. Fragmentation and fragile links between platforms could trap liquidity and reintroduce risk through the back door.
Instantaneous and 24/7 settlement is a defining feature of tokenization that challenges central banks’ and markets’ practices designed around business‑day cycles. Liquidity backstops may need to operate directly on tokenized infrastructures, at machine speed. Designing them raises complex questions about access, control, and moral hazard.
As financial logic moves into smart contracts, the rules governing transactions are increasingly written in code and procedures become automated.
Effective oversight must therefore extend beyond institutions to the code itself. Critical smart contracts could become too important to fail — requiring increased oversight and supervision, much as systemically important financial institutions do today.
Legal foundations matter just as much. Market participants must know whether tokenized records constitute definitive ownership, whether settlement finality is legally recognized, and which jurisdiction’s law applies. Without clarity, tokenization will remain fragmented and peripheral.
Heightened risks
For emerging and developing economies, faster and cheaper cross‑border payments, improved market access, and more efficient settlement could help overcome long‑standing inefficiencies. But the risks are equally significant.
Tokenized assets and money can move across borders almost instantaneously, bypassing the frictions that currently slow down capital flows and give policymakers time to respond. Volatile capital movements, rapid currency substitution, and erosion of monetary sovereignty become more likely — especially if privately issued global stablecoins become dominant means of payment.
Strong domestic policy frameworks remain the first line of defense. But international coordination is essential if tokenization is to support, rather than undermine, inclusion and stability.
Policy choices
The future of tokenized finance will be determined by a complex set of decisions that policymakers will have to make about issues such as the role of public and private money; the degree of interoperability; legal frameworks; code governance; liquidity backstops, and others. The best outcome would be of a system that provides elements of the required public goods such as risk-free settlement assets and internationally aligned oversight, while encouraging and enabling desirable features such as interoperability.
 
 
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Across the OECD area, the share of science and engineering professionals reached 3.7% of the workforce in 2024; information and communication technology (ICT) professionals grew to 3.1%. R&D personnel in turn rose to almost 1.6%.
The professional science, technology, engineering and mathematics (STEM)  workforce has continued to grow across OECD and EU economies, according to the latest data from the Research and Innovation Careers Observatory (ReICO). The share of science and engineering (S&E) professionals rose from 3.2 to 3.7% of total employment across OECD countries between 2017 and 2024. Information and communication technology (ICT) professionals, comprising software and applications developers and analysts as well as database and network professionals, rose from 2.0 to 3.1% on average across OECD economies.
ReICO, a joint OECD-EU initiative, charts the development, labour market footprint and circulation of the research and innovation (R&I) workforce across more than 50 countries. It views that workforce through two complementary lenses. One counts people by occupation: the STEM workforce of S&E and ICT professionals. The other counts by function: R&D personnel, the researchers, technicians and support staff who work on R&D whatever their occupation. The two overlap but do not coincide, since many STEM professionals do not work on R&D, and not all R&D personnel are STEM professionals. The 2026 ReICO hub update expands the set of indicators on the R&I workforce relative to the 2025 beta release, and for the first time includes measures of the professional STEM workforce, drawn from labour force and population census, alongside established and experimental indicators.
Large differences across countries in the size of the STEM workforce and the balance between S&E and ICT professionals
Combined, S&E and ICT professionals represent about 7% of total employment across OECD and EU economies. These occupations require high levels of scientific and technical expertise, and while not all of them directly perform R&D, they contribute to the capacity of economies to develop, adopt, apply and diffuse new knowledge and innovations. Differences across countries are wide. Among OECD Members, the combined share of S&E and ICT professionals exceeds 10% in Finland, Israel, Luxembourg, the Netherlands and Sweden, but falls below 3% in Colombia, Mexico and Türkiye. It is lower still across some partner economies covered by ReICO, below 2% in Argentina, India, Indonesia and Peru.
The same countries with the largest STEM workforce also tend to be the most ICT-intensive. On average in the OECD and EU, the share of S&E professionals still exceeds that of ICT professionals, but the reverse holds in a handful of economies, most markedly in Sweden and the United States, and also in Israel, Luxembourg and the Netherlands.

Steady expansion in R&D personnel and researchers

R&D draws on the STEM workforce, but only a fraction of STEM professionals works directly on R&D, and other occupations contribute to it as well, like lab technicians, product designers and administrative support staff. By 2024, the total workforce dedicated to R&D, measured in full-time equivalents (FTE), reached almost 1.6% of total employment on average across the OECD.
Following the Frascati Manual, OECD estimates of R&D personnel capture the sum of personnel under three functional categories: R&D researchers, R&D technicians and other R&D support staff. Researchers are not only scientific researchers but also R&D professionals, including managers and engineers, engaged in the design and oversight of R&D activities and projects across all sectors. From 2015 to 2024, the share of researchers increased from 0.8% to 1.1% in the average OECD country.

OECD R&D workforce statistics draw on official business and organisational surveys conducted by national statistical organisations, reported within the OECD Main Science and Technology Indicators (MSTI) and in more detail in the OECD R&D Statistics database. The STEM occupation measures draw on a different source: labour force and population census data, classified by the International Standard Classification of Occupations (ISCO). Unlike MSTI, the estimates presented above are based on unweighted averages across countries with available data, but where weighted averages can also be calculated the trends coincide and the differences between OECD and EU averages are negligible.

Differences in R&D personnel intensity and composition across countries

Differences in R&D personnel intensity, the share of R&D personnel in total employment, are almost as wide as differences in R&D expenditure intensity reported in the OECD Main Science and Technology Indicators, reflecting the importance of direct labour inputs to the R&D effort of firms and organisations. Among countries with data covering the whole economy, only five exceed 2% R&D personnel intensity: Austria, Belgium, Denmark, Finland and Korea.
The composition of the R&D workforce also varies. On average, researchers make up 68% of R&D personnel across the OECD and the EU, ranging from 88% in Sweden to 55% in Switzerland. Among the partner economies in the database, the People’s Republic of China (hereafter “China”) reports a share of 42%, the only economy in the database where researchers account for less than half of R&D personnel.

More indicators on the R&I workforce are available on the ReICO hub

The ReICO hub offers a broader picture of R&I workforce capacity, development and circulation across countries. The 2026 edition updates over 400 indicators from the 2025 beta release, widens coverage of the employment conditions of the most highly qualified, and adds new indicators on their quality of life. Further additions include expanded data on the financial resources available for R&D personnel across sectors, and new indicators on the education profile of persons employed in innovative firms.
Access the charts here.

 
 
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What quotas have been put in place on steel imports into the EU and whom do they concern?
The EU’s steel measure, which enters into application on 1 July 2026, reduces duty-free imports of 26 categories of steel products into the EU by an average of 47% as compared with the quotas under steel safeguard. As of 1 July 2026, a total of 18.3 million tonnes of steel will be allowed to enter the EU duty-free each year. Today’s implementing regulation sets out the fair and objective methodology under which that quota will be distributed among the EU’s trading partners. Out-of-quota imports will be subject to a tariff of 50%.
What kind of methodology did the Commission use to determine the distribution of the steel quota?
The EU’s steel quota has been divided amongst the EU’s trading partners using a fair and objective methodology in line with criteria laid down in the Steel Regulation. This methodology is in line with WTO rules and acknowledges any agreements in principle reached between the EU and a trading partner at the WTO (under Article XXVIII GATT negotiations). It also distinguishes between FTA and non-FTA partners, ensuring that FTA partners get better treatment in the form of higher quota volume. Finally, the methodology is mindful of diversification and security of supply issues.
How specifically was the quota divided between individual trading partners?
Half of the EU’s annual import quota of 18.3 million tonnes – so 9.15 million tonnes – has been distributed exclusively to partners with free trade agreements (FTAs) with the EU, with the remaining half available to all trading partners (including FTA partners) without discrimination.
Of the part available exclusively to FTAs, a larger share are country-specific allocations. These are granted to countries which have historically held at least 5% share of import volumes (based on an average share of imports in the years 2022-2024). The remaining volumes are available for exports from all FTA partners on a competitive basis.
What special considerations have been given to the EU’s FTA partners?
The tariff quota distribution aims to minimise the impact of the EU’s steel measure on its FTA partners within the limits of the Steel Regulation and without compromising the measure’s effectiveness.
Half of the EU’s annual import quota has been reserved exclusively for preferential trading (FTA) partners, with the remaining half available to all trading partners – including FTA partners – without discrimination. Moreover, many FTA partners will receive secure country-specific quotas proportionate to their historic import volumes.
Most of the EU’s FTA partners will therefore see a market access reduction significantly lower than the average reduction of 47% foreseen by the Steel Regulation.
How are the EU’s new steel measure and the specific tariff quota distribution WTO-compatible?
Article 28 of the General Agreement on Tariffs and Trade (GATT) allows a WTO member to modify or withdraw its bound tariff rates. To do so legally, the country must enter negotiations with affected trading partners to offer compensatory adjustments to maintain the overall balance of trade concessions.
Since proposing its steel measure in October 2025, the EU has engaged in constructive Article 28 negotiations with more than twenty trading partners (mostly FTA partners) at the WTO. Based on these discussions, the Commission has sought to cater for FTA partners’ main concerns to minimise the impact of the steel measure on them without undermining the measure’s effectiveness. A significant number of partners provisionally agreed to their allocated quotas as a result.
Why have the EU’s EEA trading partners been excluded from the steel measure?
EEA countries are not subject to tariff quotas or duties under the steel measure. Such a differentiated approach is justified due to their very close and unique level of integration in the EU’s internal market.
EEA countries were already excluded from the steel safeguard on the same grounds. Their levels of exports remained stable (and rather limited in volumes) over 8 years. Therefore, the combination of their unique status vis-a-vis the EU, which no other FTA has, and their limited volumes of exports warrant such treatment.
However, to avoid that third country producers attempt to use this exclusion as a loophole in the future, importers of covered steel products from the EEA will need to fulfil melt and pour evidence requirements just as all others concerned.
How does the measure relate to the Windsor Framework solution as regards Northern Ireland?
The Windsor Framework includes a solution for steel of UK origin moving from Great Britain to Northern Ireland, consisting of specific TRQs, for the benefit of the economy of Northern Ireland.
The Implementing Regulation provides the same TRQs volumes for these movements, in full respect of the commitments under the Windsor Framework.
Won’t third countries retaliate against the EU’s measure or specific quota distributions?
The EU’s steel measure has been prepared in line with WTO rules, and the EU has actively engaged in Article XXVIII GATT discussions with its trading partners in Geneva to ensure that preferential partners could maintain their overall level of concessions. As a result, a significant number of the EU’s FTA partners have agreed in principle to their tariff quota allocation.
Ultimately, the only way to avoid this proliferation of unilateral measures is to address the root of overcapacity collectively. The EU remains fully committed to advancing on that objective together with like-minded partners, both bilaterally and collectively in the context of the Global Forum on Steel Excess Capacity (GFSEC).
How will the new quotas interact with existing/future trade defence (TDI) measures on various steel products?
TDI measures such as anti-dumping and countervailing duties apply from the first ton imported. There are several product categories under the scope of the proposal subject to TDI measures. This means that such imports will pay the duties in place under TDI measures and, if they exhaust the tariff quota under the measure, an additional 50% duty would apply.
Why has the EU introduced a measure on steel? 
Global overcapacity, often driven by non-market policies and practices, keeps growing relentlessly, and is already at unsustainable levels – currently over 620 million tonnes, estimated to reach 721 million tonnes – more than 5 times the EU’s annual steel consumption.
In parallel, a growing number of third countries are closing their markets to imports, often in the form of tariffs. This creates a very big risk of trade diversion into the EU market, in a situation where import penetration in terms of imports’ market share remains at historically high levels.
The steel measure entered into force on 1 July 2026 and thus ensures a continued and highly effective level of protection for the EU steel sector following the expiry of the EU’s steel safeguard on 30 June 2026.
It is very important to preserve a strong steel industry, securing investments for its successful decarbonisation, and to avoid undermining our strategic autonomy in this key sector.
The Commission remains fully committed to finding a collective solution to the problem of global overcapacity. However, until that materialises, the EU needs to take firm action and with this proposal, it is doing so.
 
 
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Place-based policies offer regions left behind by globalization a path beyond economic populism.

One of the most firmly held beliefs in economics is that free trade is good for humanity. Yet that confidence in the economic virtue of open markets can blind the profession to the complications of deep global economic ties. When in the 1990s the world leapt into frenzied globalization, policymakers touted the potential efficiency gains but gave short shrift to possible painful distributional consequences. Those consequences have now come back to bite.
The United States’ embrace of higher import tariffs, China’s pursuit of aggressive industrial policies, and the United Kingdom’s exit from the European Union—all of which occurred around 2016—heralded a more fractious global economic order, which, according to Canadian Prime Minister Mark Carney, is steering the world toward geoeconomic rupture.
It took decades to build the international institutions, negotiate the multilateral agreements, and enact the domestic economic reforms that wrought the modern era of globalization. It could be torn down quickly and in unpredictable ways that upend economies. To avoid such a rupture calls for a clear-eyed look at why globalization has become unpopular worldwide and a credible alternative to economic nationalism that addresses the dislocations integration has caused.
The accession of China, India, and other newly liberalizing economies to the World Trade Organization (WTO) in the 1990s and 2000s lifted hundreds of millions of people out of poverty in one of the greatest improvements in human well-being. This much standard economic analysis foretold: We expected efficiency gains and we got them. What economists failed to foresee was the profoundly disruptive impacts of rapid globalization on labor markets in high-income countries (and some middle-income ones, too).
To be sure, emerging technologies and the rise of services were also disruptive. In concert, they probably determined more recent changes in high-income-country living standards than international trade did. But it was signature changes in trade policy—the formation of the EU in 1992, the enactment of the North American Free Trade Agreement in 1994, and China’s accession to the WTO in 2001—that got the public’s attention. Many voters in Europe and the US came to blame these and related policy changes for their economic discontent, which later morphed into support for nationalist and populist political movements that champion economic isolation.
Disruptive globalization
Most economists missed the disruptive impacts of globalization because they misunderstood three things about how labor markets adjust to large shocks. First, they failed to recognize how long-standing industrial specialization patterns exposed manufacturing regions to rising import competition from China and other developing economies.
Since the Industrial Revolution, manufacturing has been highly concentrated geographically, which led Alfred Marshall, the 19th century political economist, to develop his insights on productivity gains from the spatial agglomeration of economic activity. Concentrated first in major urban centers, manufacturing over the course of the 20th century relocated to smaller and medium-sized industry towns and cities.
When China began its spectacular manufacturing export growth in the 1990s, those industry towns were ground zero for the ensuing trade shock. Import-competing regions of France, Germany, the UK, the US, and other high-income nations bore the brunt of manufacturing job loss caused by deepening import penetration. At the same time, superstar cities in those countries, which specialized in business services, finance, high tech, and other knowledge-intensive industries, saw their exports and incomes boom.
Economic models of the time were tuned to capture national impacts of freer trade. Consequently (and consequentially), they missed the highly uneven regional impacts of globalization. We had not expected winners and losers to be so starkly differentiated by place.

Public opinion has soured on globalization in high-income countries because many middle- and low-wage workers ended up on the losing end of economic openness.

Lasting scars
Second, economists did not anticipate the magnitude of the scarring effects from manufacturing job loss. The fetishization of manufacturing by those who espouse economic nationalism is not without reason: The sector has long offered a pay premium relative to what people could earn in other lines of work, especially for those without a college degree. When factories closed or laid off large numbers of employees, as occurred in many high-income countries during the China trade shock, industrial workers lost their pay premium. Most, faced with the alternatives of lower-wage jobs in services or exit from the labor force, never replaced their lost earnings.
Although economists first documented the scarring effects of job loss in the early 1990s, they did not appreciate until later that when job loss is regionally concentrated, individual scarring aggregates into large negative local income shocks. Once displaced, former factory workers spent less on nontraded goods and services, paid less for housing, and contributed less in taxes to support local public services—all of which depressed incomes where manufacturing was declining.
Again, because economic models were tuned to account for national-level adjustment to international trade, they projected that workers displaced in import-competing sectors (manufacturing) would simply shift into sectors in which exports were expanding (knowledge-intensive services). Import displacement and export absorption did occur, but among largely disjointed sets of people.
Lack of mobility
Third, economists overlooked the lack of geographic labor mobility among less-educated and older workers in response to changing economic conditions. Standard economic models posit a spatial equilibrium condition: If real earnings rise or fall in one region, the migration of labor between regions will smoothly arbitrage away spatial differences in pay. In theory, labor mobility transmits localized economic shocks to other regions, dissipating shock impacts and ensuring that regional spikes in joblessness are temporary. In practice, interregional migration works slowly: Spatial equilibration to shocks can take decades.
The slowness of regional migration has been one of the hardest lessons for economists to internalize. Surely, in economies as large as the US and the EU, where millions of jobs are created and millions destroyed each year, job losses in a subset of industrial regions should be easily offset. Such logic is mistaken—first, because it projects frequent job transitions among younger workers to older workers, who are markedly less agile, and second, because it assumes that upward-sloping job ladders available to more educated workers are equally accessible to the less educated. Modern labor markets are undeniably dynamic. But that dynamism has been least evident among workers most exposed to deindustrialization.
Regional disparities
It has been painful for countries to learn of globalization’s dark side, which entails widening regional economic disparities and a tendency for former industry towns to get stuck with high joblessness and few well-paying jobs for less-educated workers. In the moment globalization was causing manufacturing job losses, countries had viable policy options to cope with the disruption, including generous and immediate assistance for displaced workers and safeguard tariffs that would have spread import surges over longer periods of time.
Two decades later, such policies are neither available nor relevant. Countries are left to decide whether and how to address regional economic distress caused by globalization, long after the distress materialized. Selecting the right policies calls for a clear understanding of the economic problems countries are trying to solve.
One option to help left-behind regions is simply to let market forces do their thing. The outmigration of labor and the retirement of displaced workers would ultimately help forsaken regions shrink to a smaller, more efficient size. Businesses would close, downtowns would board up buildings, and young labor force entrants would launch their careers elsewhere. If we believe that there are no economic distortions that impede labor market adjustment to adverse shocks, or if we believe that governments cannot implement effective remedies for such distortions, then laissez-faire may make sense. It is important to recognize, however, that although market forces may alleviate spatial differences in economic well-being, they are likely to do so ever so slowly.
Pittsburgh experience
Consider the experience of Pittsburgh, which many cite as a successful example of adjustment to deindustrialization. Through the first half of the 20th century, the city was a global center for steel manufacturing. After 1970, import competition, technological change, and other forces contributed to a prolonged industrial decline, during which joblessness and economic hardship were endemic. Although Pittsburgh today is home to health care, life sciences, and robotics, its transformation took more than a full generation. During this period the economic opportunity of local people was circumscribed by distress. For every Pittsburgh, there are several other former industry towns that did not find a path back to prosperity. Long-term adjustment meant diminished incomes, housing prices, and urban amenities.
A second option to help left-behind regions is to target affected individuals through means-tested entitlement programs. Unemployment insurance, income support for low-income households, housing and energy subsidies, and subsidized health care are common ways to help people in hard times. If we don’t have confidence that insurance and credit markets can insulate people against adverse shocks, then expansive social insurance programs may make sense.
Yet such programs condition assistance on individual or household well-being—not on the state of the local labor market. Social insurance may help people avoid sharp declines in consumption during episodes of hardship, but they do not address the causes of regional economic distress. Such programs may make economic adjustment less painful, but they are unlikely to speed adjustment along.
Trade tariffs
A third option to help left-behind regions is to target the industries whose decline was responsible for economic distress. Recent US import tariffs, for instance, have been justified in part by the claim that they will help bring manufacturing jobs back to communities hollowed out by globalization. On the surface, addressing the negative labor-market consequences of trade by blocking imports may appear sensible. However, the origin of regional distress is not import competition per se but the scarring effects of job loss and regions’ inability to adjust to decline in a major industry.
Import tariffs would not prevent job loss from technological change, artificial intelligence, or other shocks that may be disruptive in the future. Trade protection targets economic distress indirectly and therefore poorly. It is not surprising that US tariffs have done little to restore manufacturing employment or earnings growth in regions harmed by the China trade shock.
A final option is to target left-behind regions through policies that promote local economic development. Place-based policies subsidize investment in human and physical capital with the aim of upgrading labor productivity, earnings, and economic structures in distressed regions. In theory, such policies are justified if the social return on investment is relatively high in communities with elevated joblessness and low wages. In practice, place-based policy has long been controversial among economists, given concerns over rent capture by special interests and informational challenges in program design.
Successful policy
Recent empirical research clarifies where place-based policy works well and where it does not. Less-effective policies—also among the most visible—include the use of tax subsidies to compete for major investment by large firms. Subsidy competitions tend to transfer most of the economic surplus from new investment to the investors themselves, leaving “winning” regions with a winner’s curse of high tax expenditure per job created.
More effective place-based policies condition subsidies on local distress, monitor compliance with program objectives, and design programs for specific contexts via ongoing experimentation. Examples include tax incentives for investing in low-income communities (such as enterprise zone programs with rigorous selection and auditing of participating firms) and sectoral worker training initiatives (active labor market programs, which have been applied in many high- and middle-income countries).
Of these four options, only place-based policy directly targets outcomes that alleviate regional distress: moving out-of-work adults into employment, bringing more well-paying jobs where they are scarce, and making regions more attractive for future investment.
Public opinion has soured on globalization in high-income countries because many middle- and low-wage workers ended up on the losing end of economic openness. The prosperous future they were promised did not arrive. To restore faith in global economic integration we must correct the mistakes of the past and offer a credible alternative to economic nationalism.

 
 
 
Compliments of the International Monetary Fund The post IMF | Righting Globalizations’ Wrongs first appeared on European American Chamber of Commerce New York [EACCNY] | Your Partner for Transatlantic Business Resources.

From 1 July 2026, the EU will introduce a temporary €3 customs duty on low-value parcels imported from outside the EU, mainly through e-commerce. This includes a wide range of products commonly bought online, such as clothing, toys, electronics, and other consumer goods worth up to €150.
Every day, millions of low-value parcels enter the EU. Many contain products that do not meet EU safety standards or are undervalued or falsely declared to avoid customs duties. At the same time, the current customs duty exemption gives non-EU sellers an unfair advantage over businesses that manufacture or sell products in the EU.
The new duty will apply per item, based on tariff classification and not quantity. In practice, this means

if you buy 5 T-shirts, a €3 customs duty will be applied (as all T-shirts fall under the same tariff classification)
if you buy 3 T-shirts and a watch, a €6 customs duty will be applied (as the T-shirts and the watch fall under two different tariff classifications)

The seller or importer will be responsible for declaring and paying the duty as part of the customs process.
The new measure will help create fairer competition for EU businesses, better protect consumers from unsafe products, tackle customs fraud, and address environmental concerns over mass shipping.
The EU is working to modernise customs procedures to strengthen the single market and ensure that all businesses selling into the EU compete on equal terms while meeting the EU’s safety and compliance standards.
 
 
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Today’s AI policies will shape tomorrow’s job market.
Artificial intelligence has reignited an old fear—that technology will eliminate work faster than economies can adapt. Variations of this concern appear every time powerful new technologies emerge. What feels different today is the speed, scope, and visibility of AI’s advance, particularly in cognitive tasks long assumed to be uniquely human.
Yet history shows that whenever new technology emerges, economies ultimately undergo deep structural transformation. This allows labor markets to adapt to the potential of the new technology.
Inevitably, many jobs will be changed by AI adoption. Some will be enhanced. Others may be rendered obsolete. But the decline of particular types of jobs is not the same as a sustained reduction in overall employment. If history is any guide, it is not the technology itself that could cause mass unemployment, but the policies deployed in response.
The aggregate impact of AI will depend on how the economy adjusts to it, including whether productivity gains reduce costs, expand demand, and support the creation of new tasks and firms and thereby drive workers and capital toward new uses—enough to offset or outweigh the inevitable loss of some positions or categories of jobs.
The outcomes of the transformation will depend not only on the technological shock itself but more importantly on the policies and institutions that govern the adjustment. If policymakers respond to AI with the wrong set of policies—the kind that delay rather than facilitate adjustment—they risk causing worse rather than better labor market outcomes. Misguided policies could end up slowing growth rather than raising it and increasing inequality rather than containing or reducing it.
Past technological shocks
This time could always be different. But the overwhelming weight of historical evidence supports the claim that innovative technologies do not cause mass unemployment.
The emergence of new general‑purpose technologies is not new. Over the past two centuries, economies have repeatedly absorbed technologies that transformed production, reorganized firms, and displaced entire categories of work—from the steam engine and electrification to computing and the internet.
Each of these technologies disrupted existing jobs and skills. Each provoked anxiety about the future of jobs and work. And each ultimately raised productivity, lowered prices, increased real incomes, and supported higher employment.
Handloom weavers were displaced by mechanized looms. Typists declined as word processing spread. Travel agents were displaced by online booking platforms. In each case, the disappearance of a task was visible and politically salient.
But new jobs emerged—often in sectors that barely existed before. Railways created demand for engineers, mechanics, logistics managers, and entirely new financial services. Electrification enabled industries ranging from household appliances to mass retail and refrigeration. Computing gave rise to software development, data analysis, digital design, and a wide range of professional services. Aggregate employment did not collapse. It ultimately increased.
It is important to recognize that these gains were neither automatic nor immediate. They were staggered and gradual and required diffusion, complementary investment, and institutional adaptation. Nonetheless, a systematic review of the economic literature published in 2023, covering more than 100 studies, showed that the labor displacing effect of technology is more than offset by labor creation.
What changed was not simply the number of jobs, but the content of work. As recent IMF research shows, jobs evolve not only because workers move across occupations, but because of shifts in the skills required within the same occupation. Roughly 1 in 10 job vacancies in advanced economies now lists a new skill. This is how technological change usually unfolds: not through wholesale job destruction but by reshaping what workers do and the skills they need.
Markets’ absorption of new technologies reflects a well‑known economic dynamic. As processes become more efficient, costs fall. Lower costs translate into lower prices. Lower prices stimulate demand. And higher demand supports higher output and employment. Economists often refer to this as the Jevons paradox, and it has been observed repeatedly across sectors, from energy to transport to information processing.
The key point is that new technology expands economic activity—by opening new markets, increasing scale, and supporting entirely new forms of production, consumption, and employment.
What this means for AI
This is likely to be the net impact of AI. By reducing the cost of analysis, prediction, communication, coordination, and—increasingly in its agentic form—action, AI makes a wide range of services cheaper and more scalable. This will eventually increase demand, while also enabling new products, services, and firms.
A recurring mistake in today’s debate is a modern version of what economists have long called the “lump‑of‑labor fallacy”—the belief that there is a fixed amount of work to be done, so that if machines do more, there will be less for people to do. History tells a different story: Technological progress has created more jobs than it has destroyed. And as IMF research shows, when AI complements human labor and productivity gains are sufficiently large, AI adoption can lead to higher growth and incomes for most workers.
None of this implies that the adjustment will be smooth or costless. Even when technological change ultimately supports net job creation, the transition can be disruptive. Three issues in particular deserve close attention.
First, we do not yet know what the new work will look like, who will do it, or where it will be located. And the social and political disruption created by that uncertainty, at both the individual and societal levels, can be significant. IMF staff estimates find that approximately 40 percent of jobs globally could be affected by AI in some way—not necessarily eliminated, but changed. That includes changes in task composition, skill requirements, and organizational structure. Many jobs will be enhanced by AI. Some may be rendered obsolete. The structure of labor demand could also change. Emerging evidence suggests near term gains may be strongest for high- and low-skill workers, while demand for middle-skill and entry-level positions could weaken. However, predicting the long-term trajectory of trends in labor demand is exceptionally uncertain. Whatever shifts do materialize will have important political economy consequences that policymakers will need to manage.
Second, AI could accelerate churn in labor markets that may present challenges for some of those markets. The scale of preexisting labor market churn, moreover, is often underappreciated. In the United States, total nonfarm employment is roughly 160 million, and there are approximately 60 million hires and 60 million separations every year. This extraordinary scale of job creation and destruction is happening every day throughout every corner of society. Countries with less flexible labor markets may struggle to reallocate resources in the world of AI more than those with a higher degree of churn.
Third, the labor market adjustment caused by AI could be slowed or distorted by policy choices, institutional frictions, or market failures. We have seen this before. Early uses of electricity focused on powering existing factory layouts rather than reorganizing production lines to seize the full potential of the new technology. Early uses of computing automated clerical tasks before enabling entirely new businesses and organizational forms. In both cases, the largest productivity gains came later, once complementary investments and institutional changes caught up.
Economic historians sometimes describe this dynamic as an “Engels’ pause,” after Friedrich Engels’ analysis of the combination of rapid economic growth and stagnant wage growth Britain experienced in the first half of the 19th century. The term has come to denote a period in which new technologies diffuse through the economy, disrupting existing structures, before new business models and activities fully emerge. During that period, gains can appear uneven, and labor market adjustment can be painful. Distributional changes may be material and cause social and political disruption.
Policies to facilitate adjustment
The task for policymakers will be to maximize the potential benefits from AI while insuring against the potential negative consequences. This won’t be easy: Realizing the benefits from AI will require large shifts in labor and capital across the economy, which can be disruptive if the process of job reallocation is prolonged or poorly managed. What should policy aim to do and not do?
The overarching response to a structural shock like AI should be structural policies—designed to facilitate adjustment rather than prevent it. These include labor market policies that support mobility and reemployment, product market policies that promote competition, and financial and legal frameworks that allow capital and assets to be reallocated efficiently and productively.
Labor market policies are particularly important. Many existing labor market institutions are designed to deal with cyclical, not structural, shocks. Furlough programs, job retention subsidies, and temporary layoff protections can be highly effective when aggregate demand falls temporarily and then recovers. Such measures are much less effective when entire sectors need to shrink, and new ones need to expand. What works for a recession does not necessarily work for a technological transition.
Policies that help workers navigate transitions without locking economies into outdated structures can also play a useful role, especially retraining and upskilling programs. These programs should be widely accessible and designed to maintain private sector incentives for both businesses and employees so that new employment relationships can take hold without government support.
But policymakers should not rely too much on these policies, since the track record of many active labor market policies is mixed and may not sufficiently address the scale of the challenge posed by AI. Governments often lack the necessary information, incentives, and institutional capacity, particularly in fast‑moving technological environments. AI itself will provide a significant opportunity both for upgrading active labor market policies and for turbocharging the employment services industry, given its capacity for personalized education and reducing information frictions.
On the other hand, policies that slow adjustment, by protecting specific jobs, firms, or sectors, would delay reallocation, reduce productivity growth, and ultimately lead to worse labor market outcomes. There is an understandable tendency to respond to disruption with protection. But this can end up harming the very people it is intended to help. If policymakers make it more expensive for companies to employ or fire workers, companies will pay less or not create jobs at all.
AI regulation
A similar nuanced approach should be applied to AI regulation.
Guardrails are clearly necessary in some areas, including when it comes to cybersecurity and the protection of children. In these cases, risks are concrete and externalities are clear. But there should be a presumption against protective action unless there is strong evidence of harm or the presence of clear risks. A rush toward regulation without a clear rationale—for example, generalized fear about job losses—could leave society worse off because of prolonged misallocation of resources and drifting away from the technological frontier.
AI regulation that focuses on permission structures rather than restrictions on AI use can be productive. For example, heavily regulated sectors like health care and finance may need additional regulatory certainty on the suitability of using AI systems in order to realize the productivity benefits of AI adoption.
More broadly, regulation should promote business dynamism. This entails reducing barriers to entry to avoid regulatory capture and excessive market concentration and maintain the significant competitive dynamics currently evident in the AI ecosystem. Policymakers also need to ensure that bankruptcy and restructuring frameworks are working efficiently to support the speedy reallocation of resources.
Developing economies
The stakes are particularly high for emerging markets and low‑income countries.
For these economies, AI presents a genuine leapfrogging opportunity. Digital delivery of services can overcome physical infrastructure constraints. AI‑enabled diagnostics can expand health care access, and automated compliance tools can lower the cost of formality for small firms. Governments can also use AI to improve tax administration, customs, and social protection delivery.
But AI-related risks specific to emerging markets and low‑income countries are substantial. If AI leads to sustained productivity gains in advanced economies first, income gaps could grow. And these gaps would widen further if economic rents from AI became geographically concentrated. Capital could flow uphill, diverting much‑needed financing away from lower‑income countries.
These risks are amplified by existing structural constraints in some developing economies: slow labor reallocation, barriers to firms’ entry and exit, limited access to financing, weak legal systems, and ill-defined property rights.
Policies should therefore be tailored to countries’ level of preparedness. More developed and better-prepared economies should focus on innovation and diffusion—through R&D investment, improved access to financing, and a business environment that fosters innovative firms—along with regulatory frameworks that enable safe and widespread AI use. Lower-income and less-prepared economies should focus initially on building digital infrastructure—especially reliable and affordable power generation—and on education, with a greater focus on earlier attachment to the labor market, lifelong learning, and skills that complement rather than compete with technology. These investments can support AI adoption while advancing broader development goals; they should be embedded in a strategy that safeguards fiscal sustainability and is aligned with absorptive capacity.
Role of the IMF
History offers many examples of policies designed to slow structural change that ended up entrenching inefficiency, delaying recovery, and worsening outcomes. If protection becomes the dominant response, the economic and social disruptions associated with AI adoption could overwhelm the potential benefits. A prolonged and politically difficult period of weak growth and stalled adjustment could ensue—another version of Engels’ pause.
In the worst case, a protective response could cause a political backlash against the technological progress and creative destruction that underpins long-term improvements in living standards. Engels’ pause in the United Kingdom coincided with the rise of the Luddite movement. And while Engels did not coin the term Engels’ pause, his experiences during this period informed his subsequent collaboration with Karl Marx on the development of the political philosophy of Marxism. Though neither the Luddites nor Marxists succeeded in 19th century Britain as a response to Engels’ pause, variants elsewhere have damaged standards of living in the subsequent two centuries.
The goal of policy should not be to protect specific jobs, companies, or industries. It should be to incentivize employees and businesses to adapt and to unlock the productivity gains from AI. This requires flexibility, dynamism and sound structural policies—not stasis.
Institutions like the IMF can help realize this crucial policy goal. We are strengthening our surveillance of AI‑related structural changes. We are supporting members in designing reform strategies and thinking through trade-offs. And we are facilitating international cooperation and knowledge sharing on AI‑related best practices to help avoid some of the pitfalls of earlier periods of economic transformation.
We also see AI as a major opportunity to enhance our own operations. Used effectively, AI can help us do more with the same resources, improve the quality and speed of our analysis, and further increase the value we deliver to our membership.
We do not know what the future of work will look like. But it will be heavily shaped by the policies and institutions that govern how economies adapt to technological change. Our choices today will determine whether this transformation lifts growth and prosperity—or leaves our societies, politics, and institutions struggling to catch up.
 
 
Compliments of the International Monetary Fund The post IMF | Artificial Intelligence and the Economics of Adjustment first appeared on European American Chamber of Commerce New York [EACCNY] | Your Partner for Transatlantic Business Resources.