Lawmakers in the U.S. House of Representatives set April 21, 2026, as the date to hear from and question top Pentagon officials Adm. Brad Cooper, the head of U.S. Central Command, and Gen. Dagvin R.M. Anderson, head of U.S. Africa Command, about the war in Iran. But Republican legislators put off the hearing for a month, giving up – for now – the opportunity to exercise oversight of the war.

Adam Smith, the top Democratic member of the House Armed Services Committee, told The New York Times, “We are six weeks into this conflict. And we still haven’t gotten a public briefing from anyone in the administration about the war.”

President Donald Trump’s military campaign against the Iranian regime is currently in a ceasefire. Despite the low approval rating of the war, the president has not drawn the conflict to a close, and the result of the operation is so far unclear.

The postponed hearing was only one example of how Congress has been noticeably meek about the war, with most Republicans killing the many Democratic efforts to exercise constitutionally granted power over engaging in such military conflicts. For the fourth time, the Senate on April 16, 2026, rejected a war powers resolution.

As scholars who research war powers and have a book coming out about President Barack Obama’s decision-making about the Afghan war, we know that the reluctance of Congress to assert its power is, in fact, history repeating itself, as is the president’s unilateral action.

Historically meek Congress

Article 1 of the U.S. Constitution gives Congress the power to declare war, not the president. But most modern presidents and their legal counsel have asserted that Article 2 of the Constitution allows the president to use the military in certain situations without prior congressional approval – and have acted on that, sending troops into conflicts from Panama to Libya with no regard for Congress’ will.

Based on the 1973 War Powers Resolution – passed over President Richard Nixon’s veto – the president has an obligation to inform Congress about his actions within 48 hours of initiating military action and requires him to seek legislative authorization if the military operation will last over 60 days.

Since its passage, presidents have dutifully informed Congress within the 48-hour window when they unilaterally initiate military operations. Typically, they use the following language: “Pursuant to” their power as commander in chief and chief executive, they are initiating an operation.

Yet presidents since Nixon have never formally acknowledged the constitutionality of the War Powers Resolution. They have, however, mentioned it in their letters to Congress about their actions, and for the most part they have abided by its restrictions. So language is crucial and presidents tend to use the phrase “consistent with” the War Powers Resolution when they inform Congress about military operations.

The second Trump administration has broken with that standard. In Trump’s message to Congress about the Iran war, sent on March 2 2026, he did not acknowledge the War Powers Resolution or the Constitution, let alone pay lip service to either.

Instead, Trump has sidestepped the traditional use of the War Powers Resolution – and avoided the congressional oversight that comes with it – by relying on executive orders to convey his intent to use military power against the Iranian regime. That move, whether legal or not, has provided the president with a great deal of freedom to decide what the military can do, what tools they can use to do it and how long they can do it. His decision to send another carrier group and the addition of thousands of U.S. troops to the region is just the latest example.

Congress has proved incapable or unwilling to check this presidential unilateralism. Shortly after the start of the military campaign against Iran, Democratic Sen. Chris Murphy introduced war powers legislation to constrain Trump that failed to pass the Senate. In the House on March 5, members narrowly rejected a resolution to impede a broader or longer operation.

To a meaningful extent, we are watching history repeat itself: Over the past seven decades during times of war, members of Congress have not wanted to act, and presidents have not wanted to ask permission.

From alacrity to deference

Presidents Woodrow Wilson and Franklin D. Roosevelt made their case for war and obtained a formal declaration from Congress within three days in 1917 and within the same afternoon in 1941, respectively.

Since the start of the Korean War, however, members of Congress have demonstrated more deference and less assertiveness.

In Korea, President Truman did not get congressional authorization for the war.

Following North Korea’s invasion of the South in June 1950, Truman bypassed Congress, making his case for war to the United Nations Security Council. In July 1950, United Nations Security Council Resolution 84 “authorized the United States to establish and lead a unified command comprised of all military forces from UN member states, and authorized that command to operate under the UN flag.”

Truman’s rhetoric about American combat operations on the Korean peninsula being part of a U.N. “police action” became increasingly tenuous, but he managed to avoid seeking congressional permission. In doing so, Truman created a precedent in which a congressional declaration of war was no longer necessary for the American military to carry out combat operations. Sen. Robert Taft, a Republican, opposed this lack of congressional deliberation, declaring that Truman’s actions represented a “usurpation” of the war powers authority.“ But Congress did nothing to stop the war as the tactical and strategic picture in Korea stalemated.

In Vietnam, in the aftermath of the 1964 Gulf of Tonkin incident – a purported attack by the North Vietnamese on American naval vessels that did not, in fact, occur – President Lyndon Johnson used the alleged crisis to push for congressional authorization for the escalation of force in Southeast Asia.

Johnson presented the Gulf of Tonkin Resolution to Congress, which quickly passed it. The resolution allowed Johnson to freely escalate American military involvement in Southeast Asia with a vague authorization to engage militarily as he saw fit, in contrast to the very clear declarations of war that came before it for previous wars.

Col. Harry G. Summers, who wrote an influential strategic analysis of the Vietnam War, points to the Gulf of Tonkin Resolution as evidence that the relevant actors – the executive, Congress and the military – failed to foresee the scale of the course of action they were embarking on.

The resolution significantly increased the president’s freedom of action – and freedom from oversight – and marked a major step toward the Americanization and escalation of the war in July 1965. Despite the deeply troubled engagement in South Vietnam and the passage of the War Powers Resolution, we still see presidents acting alone, without consulting members of Congress, let alone getting authorization.

Refusing responsibility

In Summers’ Vietnam postmortem, he relates a telling anecdote of a professor at West Point. The professor, an Army officer, remarked, "When people ask me why I went to Vietnam I say, ‘I thought you knew. You sent me,’” a comment indicative of “the civilian sector’s growing refusal to take responsibility for the kind of army it needs.”

In the case of Trump’s decision-making concerning hostilities with Iran, Americans will one day need answers to the questions: Why did the United States engage in this war with unclear political objectives? And why did Congress allow it to continue?

This story contains material from an article published on March 6, 2026.

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

Forecasts of the impact of artificial intelligence range from the apocalyptic to the utopian. An October 2025 report from Senate Democrats, for example, predicted AI will destroy millions of U.S. jobs. A couple of years earlier, consultant company McKinsey forecast AI will add trillions to the global economy, while emphasizing job losses can be mitigated by training workers to do new things.

The problem is that many of these claims are based on projections, overly simplified surveys or thought experiments rather than observed changes in the economy. That makes it hard for the public, and often policymakers, to know what to trust.

As a labor economist who studies how technology and organizational change affect productivity and well-being, I believe a better place to start is with actual data on output, employment and wages – which are all looking relatively more hopeful.

AI and jobs

In one of my new research papers with economist Andrew Johnston, we studied how exposure to generative AI affected industries across America between 2017 and 2024, using administrative data that covers nearly all employers. Our analysis covered a crucial period when generative AI use exploded, allowing us to analyze the effect within businesses and industries.

We measured AI exposure using occupation-level task data matched to each industry and state’s occupational workforce mix prior to the pandemic. A state and industry with more workers in roles requiring language processing, coding or data tasks scored higher on exposure, for example, compared with one with more plumbers and electricians.

We then took that exposure ranking by occupation and looked at changes in the standard deviation in occupational exposure, comparing that with labor market and GDP across states and industries from 2017 to 2024.

Think of a standard deviation as roughly the gap between a paramedic – whose work centers on physical assessment, emergency response and hands-on care that AI cannot easily replicate – and a public relations manager, whose work involves drafting communications, analyzing sentiment and synthesizing information that AI tools handle well. That gap in AI exposure is roughly what we’re measuring when we ask: Does being on the higher-exposure side of that divide change your industry’s trajectory?

This data allowed us to answer two questions: When AI tools became widely available following the public release of ChatGPT in late 2022, did states and industries that were more exposed to generative AI become more productive, and what happened to workers?

Our answers are more encouraging, and more nuanced, than much of the public debate suggests.

We found that industries in states that were more exposed to AI experienced faster productivity growth beginning in 2021 – before ChatGPT reached the public – driven by enterprise tools already embedded in professional workflows, including GitHub Copilot for software development, Jasper for marketing and content writing, and Microsoft’s GPT-3-powered business applications. In 2024, for example, industries whose AI exposure was one standard deviation higher saw gains of 10% in productivity, 3.9% in jobs and 4.8% in wages than comparable industries in the same state.

Those patterns suggest that, at least so far, AI has acted as a productivity-enhancing tool that boosts employment and wages rather than a simple substitute for labor.

Augmentation versus displacement

A crucial distinction in the data is between tasks where AI works with people and tasks where AI can act more independently. In sectors where AI mainly complements workers – think marketing, writing or financial analysis – our data show that employment rose by about 3.6% per standard deviation increase in exposure.

In sectors where AI can execute tasks more autonomously – including basic data processing, generating boilerplate code, or handling standardized customer interactions – we found no significant employment change, though workers in those roles saw slower wage growth.

What these findings suggest is that when AI lowers the cost of completing a task and raises worker productivity, companies expand output enough to increase their demand for labor overall — the same logic that explains why power tools didn’t eliminate construction workers.

The economic question is not whether any given task disappears. It is whether businesses and workers can reorganize fast enough to create new productive combinations. And so far, in most sectors, our evidence suggests they can.

But state policies also matter: These benefits were concentrated in the states with more efficient labor markets, meaning that the impact of generative AI on workers and the economy also depends on the types of policies and institutions of the local economy.

Importantly, these findings hold beyond occupational exposure. In additional work with co-authors at the Bureau of Economic Analysis, we found a similar effect on GDP and employment when looking at actual AI utilization — that is how often workers use AI. Drawing on the Gallup Workforce Panel, we measured workers actively using AI daily or multiple times a week. We found that each percentage-point increase in the share of frequent AI users in a state and industry is associated with roughly 0.1% to 0.2% higher real output and 0.2% to 0.4% higher employment.

To put that in context: The share of frequent AI users across all occupations rose from about 12% in mid-2024 to 26% by late 2025, a shift our estimates suggest corresponds to roughly 1.4% to 2.8% higher real output – or about 1 to 2 percentage points of annualized growth over that period.

New technologies rarely leave work untouched. But they also rarely eliminate the need for human contribution altogether. Instead, they change the composition of work, as our research shows. Some tasks shrink. Others expand. New ones emerge that were previously too costly or too hard to perform at scale. Put simply, some occupations might go away, but most of them just change.

If anything, the trends documented here are likely to strengthen rather than fade. Not only are generative AI tools rapidly improving, but also the experimentation and research and development that many workers and companies are engaging in are likely to pay large dividends. These investments – often referred to as intangible capital – tend to get unlocked a few years after a technology comes onto the scene, once complementary investments have been made.

The role of companies and managers

Whether AI leads to anxiety or adaptation for workers depends in part on what happens inside organizations. Using additional data collected over many years in the Gallup Workforce Panel covering more than 30,000 U.S. employees from 2023 to 2026, I found in a 2026 paper that workplace adoption of generative AI rose quickly over the period, with the share of workers using AI often increasing from 9% to 26%.

But the more important finding is that adoption was far more common where workers believed their organization had communicated a clear AI strategy and where employees said they trust leadership. This suggests that growing adoption and effective use of AI depends not only on the availability of the technology but on whether managers make its use clear, credible and safe.

Where that clarity exists, frequent AI use is associated with higher engagement and job satisfaction, and it even reverses the burnout penalties that appear elsewhere.

In other words, the broader economic effects of AI depend not only on how sophisticated the tools are but on whether companies and managers create environments where workers can experiment, reorganize tasks and integrate new tools into productive routines. That is, if employees do not feel the psychological safety to experiment, they are less likely to use AI, and they are especially less likely to use it for higher-value work.

That is precisely the kind of adaptation that I believe makes labor markets more resilient than the most alarmist forecasts suggest.

Christos Makridis is a senior researcher at Gallup.