• Demand for AI skills is expected to grow in 2025, driven by tech and non-tech firms.
• Tech industry hiring could rebound after several slow years, driven by demand for AI skills.
• AI skills are often scarce, with high vacancy rates for roles like natural language processing.

People and companies are placing big bets on artificial intelligence. One of the safer ones is that demand for workers with AI skills will continue to grow.

Labor market watchers told Business Insider that in 2025, as in 2024, many employers will likely be eager to hire people with skills in AI — like machine-learning specialists who train models, one of this year's most-talked-about roles — but also in wider areas that touch the technology.

In the tech industry, which has experienced years of lackluster hiring following a pandemic-era surge, there are early signs of a rebound, Hannah Calhoon, VP of AI at Indeed, told BI.

If that continues, she said, hiring will likely include roles involving AI.

Another area of demand, Calhoon said, could come from employers that aren't tech firms yet that need people skilled in incorporating off-the-shelf AI tools into their businesses and datasets.

However, unlike the tech giants, these employers aren't likely to try to build their own AI platforms, she said. So, rather than trying to recruit data scientists and those machine-learning engineers, these companies might instead want workers who can help decide which AI instruments to use and how to incorporate them into their workflow.

"What they're going to be looking for is people who understand those systems and can help them implement those tools in their business," Calhoon said.

That's likely to translate to increased demand in 2025 for roles involving AI implementation and transformation — jobs like applications administrators or solutions architects, she said.

There are other signs that the demand for talent involving AI is picking up.

Last week, Salesforce CEO Marc Benioff said that the company is experiencing "a big hiring surge" and working to fill thousands of roles to help sell products, including those involving AI. Benioff said the company has 9,000 referrals for the 2,000 positions it's opened.

Masayoshi Son, the CEO of SoftBank, likewise recently talked up AI's potential. At an event with President-elect Donald Trump last week, Son said that the Japanese conglomerate would invest $100 billion into the US over the next four years and create at least 100,000 jobs in AI and related areas.

Already, other employers are looking to grow around AI. According to Indeed, job postings mentioning AI that saw the biggest growth in the first 11 months of 2024 were senior scientists, software engineering managers, research engineers, and researchers.

AI know-how is scarce for some roles

The market may be growing, though it can be hard for employers to hire in some AI-related areas. The talent firm Randstad reports that it's twice as difficult to find and hire senior-level workers skilled in AI and automation as it is for other senior-level jobs in different industries.

Vacancy rates for roles involving specialized AI skills, like developing natural-language processing models, are as high as 15%, Randstad found. That's about double the overall job vacancy rate in the US. Randstad's estimate on AI jobs is based on an assessment of some 10 million job postings and 136 million résumés in the third quarter of 2024.

According to Randstad, employers worldwide are having the hardest time finding workers skilled in natural language processing, predictive modeling, and "stakeholder communication." The firm notes that this is partly because such abilities are specialized yet also in demand across industries.

In the US, Randstad said, the vacancy rate for jobs that require skills like natural language processing stands at 14%.

Starting from a small base

Indeed recently reported that, as of September, the share of US job postings that mention generative AI or related terminology was up 3.5 times year over year.

Yet that doesn't mean that all employers are looking for GenAI whizzes. Indeed found that only 2% of employers globally included skills related to AI in their job descriptions. By comparison, more than 20% called for basic computer skills.

Nevertheless, Calhoon said, employers' demands for AI skills are only likely to grow.

"Maybe not next year, but three or four years from now, in many roles, there will be an expectation that people will have basic fluency in being able to use some of these platforms," she said.

That's likely in part because it's not only major employers that will expect workers to have AI skills.

Andy Schachtel, CEO of Sourcefit, an offshore staffing firm, told BI that businesses of all sizes are looking to AI to boost efficiency.

The US Chamber of Commerce found in a mid-2024 survey of 1,100 small businesses that four in 10 reported using generative AI, up from 23% in 2023. About three-quarters of small businesses surveyed said they plan to adopt emerging tech like AI.

That could add to the already surging demand for leaders who are experts in AI. According to a review of more than 35,000 public and private companies in the US by Altrata, a research firm focused on executive data, the number of people in the role of chief AI officer or its equivalent — a job many people may not have heard of until this year — was up 70% year-over-year through late October.

That demand is likely one reason that workers with AI skills or who possess capabilities working with AI tools are, on average, 34% more likely to change jobs, according to Randstad.

Nicole Kyle, who researches the future of work, told BI that even for parts of a business where AI might be expected to take on a good share of the workload — like call centers —its adoption would likely increase demand for other roles.

She said that in the case of call centers, for example, those added roles might include positions involving data governance and data cleaning, as well as customer experience. That's one reason Kyle, who's cofounder of CMP Research, said she remains optimistic about AI's impact on jobs.

"I do think net-net, it will create jobs the way other technological advancements have," Kyle said.

• Morning interviews may yield higher scores due to interviewer bias, research shows.
• Bias in hiring can be influenced by the time of day, affecting candidate evaluations.
• AI tools could reduce this, offering fairer assessments than manual methods.

If you get to choose when to schedule a job interview, you might want to grab a coffee and go for a morning slot.

That's because some people conducting interviews tend to give higher scores to candidates they meet with earlier in the day compared with the afternoon, a startup's review of thousands of interviews found.

It's not an absolute, of course, and candidates can still kill it well after lunchtime. Yet, in a job market where employers in fields like tech have been slow to hire, even a modest advantage could make a difference, Shiran Danoch, an organizational psychologist, told Business Insider.

"Specific interviewers have a consistent tendency to be harsher or more lenient in their scores depending on the time of day," she said.

It's possible that in the morning, interviewers haven't yet been beaten down by back-to-back meetings — or are perhaps still enjoying their own first coffee, she said.

Danoch and her team noticed the morning-afternoon discrepancy while reviewing datasets on thousands of job interviews. Danoch is the CEO and founder of Informed Decisions, an artificial intelligence startup focused on helping organizations reduce bias and improve their interviewing processes.

She said the inferences on the time-of-day bias are drawn from the datasets of interviewers who use Informed Decisions tools to score candidates. The data reflected those who've done at least 20 interviews using the company's system. Danoch said that in her company's review of candidates' scores, those interviewed in the morning often get statistically significant higher marks.

The good news, she said, is that when interviewers are made aware that they might be more harsh in the afternoon, they often take steps to counteract that tendency.

"In many cases, happily, we're actually seeing that the feedback that we're providing helps to reduce the bias and eventually eliminate the bias," Danoch said.

However, she said, interviewers often don't get feedback about their hiring practices, even though finding the right talent is "such a crucial part" of what hiring managers and recruiters do.

She said other researchers have identified how the time of day — and whether someone might be a morning person or an evening person — can affect decision-making processes.

An examination of more than 1,000 parole decisions in Israel found that judges were likelier to show leniency at the start of the day and after breaks. However, that favorability decreased as judges made more decisions, according to the 2011 research.

Tech could help

It's possible that if tools like artificial intelligence take on more responsibility for hiring, job seekers won't have to worry about the time of day they interview.

For all of the concerns about biases in AI, partiality involved in more "manual" hiring where interviewers ask open-ended questions often leads to more bias than does AI, said Kiki Leutner, cofounder of SeeTalent.ai, a startup creating tests run by AI to simulate tasks associated with a job. She has researched AI ethics and that of assessments in general.

Leutner told BI that it's likely that in a video interview conducted by AI, for example, a candidate might have a fairer shot at landing a job.

"You don't just have people do unstructured interviews, ask whatever questions, make whatever decisions," she said.

And, because everything is recorded, Leutner said, there is documentation of what decisions were made and on what basis. Ultimately, she said, it's then possible to take that information and correct algorithms.

"Any structured process is better in recruitment than not structuring it," Leutner said.

Humans are 'hopelessly biased'

Eric Mosley, cofounder and CEO of Workhuman, which makes tools for recognizing employee achievements, told BI that data created by humans will be biased — because humans are "hopelessly biased."

He pointed to 2016 research indicating that juvenile court judges in Louisiana doled out tougher punishments — particularly to Black youths — after the Louisiana State University football team suffered a surprise defeat.

Mosley said, however, that AI can be trained to ignore certain biases and look for others to eliminate them.

Taking that approach can help humans guard against some of their natural tendencies. To get it right, however, it's important to have safeguards around the use of AI, he said. These might include ethics teams with representatives from legal departments and HR to focus on issues of data hygiene and algorithm hygiene.

Not taking those precautions and solely relying on AI can even risk scaling humans' biases, Mosley said.

"If you basically just unleash it in a very simplistic way, it'll just replicate them. But if you go in knowing that these biases exist, then you can get through it," he said.

Danoch, from Informed Decisions, said that if people conducting interviews suspect they might be less forgiving after the morning has passed, they can take steps to counteract that.

"Before you interview in the afternoons, take a little bit longer to prepare, have a cup of coffee, refresh yourself," she said.

• When my husband was unemployed for seven months, his morale and confidence slipped.
• I helped him through the difficult parts by reminding him he wasn't just a paycheck to our family.
• I also created a daily routine for him, which got him more involved in our kids' lives.

My husband left a stable job for a shiny startup when I was 38 weeks pregnant. The switch didn't go well.

In addition to three kids, bills to pay, and an unfinished building project, he worried endlessly that he wasn't what the company wanted. After giving birth, I'd relinquished my part-time work, which contributed to his mounting pressure to provide.

One night, my body hunched in a C-shape as I nursed our 7-week-old infant, I told him, "If you lose your job, we'll be OK. We'll have each other. There are worse things."

With my free hand, I grasped his. Two weeks later, he came home from work early.

"They let me go," he said, shame washing over his face. "I have a one-month severance package."

Just like that, everything changed. I tried to be supportive throughout my husband's unemployment, but it wasn't easy.

Ghosting has become the norm when job-hunting

We were surprised to learn that many employers were ghosters — either ignored his job application completely or never followed up after an interview.

I remember one time a hiring manager told my husband, "We'll let you know by Wednesday. We aren't one of those places that leave people hanging."

Wednesday came and went. A week later, my husband reached out via email, knowing what they would say even before he sent it: Sorry, we chose the other candidate.

During the seven-month job hunt that ensued, my husband and I felt endlessly discouraged by how often he was offered first, second, and third interviews only to wait weeks for results — or worse, never to hear back at all.

My husband's morale began to slip

My husband struggled with his confidence each time he received a rejection email or a promising job ghosted him. It seemed all of his prior successes did not matter anymore. He questioned his career path and widened his search to include work that didn't excite him or utilize his skill set.

As often as possible, I shared anecdotes of other friends struggling to find employment and encouraged him to keep trying. I told him to focus on the jobs that piqued his interest and matched his background. I also reminded him the struggle to find a new job wasn't a reflection on him but on the current system.

But, most importantly, I made it clear to him that his worth didn't come in the form of a paycheck. No matter what, he was an important family member — both as a father and partner.

I helped my husband lean into routine and other support systems

Another way I helped my husband remain grounded during unemployment was to establish a daily routine. We resolved to live as normally as possible. We divided the morning responsibilities — from packing lunches to school drop-offs — before he settled in and job-hunted.

He applied to at least one job per day, totaling over 200 applications in seven months. He also participated in countless pre-screenings, preliminary interviews, and 15 finalist panel interviews. It was a full-time job applying for a job.

When he took breaks, we ate meals and worked out together. In the afternoons, we divided pick-ups since our children attended different schools. He'd worked a demanding schedule for years, often missing family dinners and extracurriculars. Suddenly, he was home and available to us. Most evenings, after a family dinner, we played board games and took walks. He even found time to volunteer in our children's classrooms.

I wanted my husband to reframe his thinking and see how lucky we were to gain this valuable time together, especially with an infant. He agreed the family time was sweet, but it all still shook his confidence, and he worried about not providing a paycheck.

Supporting one another became the key

Many factors were out of our control during this long period of unemployment. Our support system was family and friends, who joked at our extra frugality and shared in our victories and disappointments.

As trite as it sounds, this seven-month unemployment period, although difficult, worked out for the best. Not only was my husband more present for our children and me, but he eventually landed a job with more flexibility on a team he loves.

Looking back, I know we got through the unemployment season because we leaned on each other. We learned that support can go a long way toward keeping morale up.

• The US added 227,000 jobs in November, greater than the expected gain of 202,000.
• Unemployment ticked up as expected from 4.1% to 4.2%.
• The job market's strength in October was clouded due to hurricanes and strikes impacting data collection.

The US added 227,000 jobs in November, more than the consensus expectation of 202,000.

Unemployment increased as expected, from 4.1% in October to 4.2% in November. The rate has been at least 4% since May. While that's low compared to historical averages, the overall labor market has cooled due to a hiring slowdown.

The new jobs report gives the Federal Reserve better information about the state of the labor market after October's report was hampered by the effects of hurricanes and strikes. Friday's report from the Bureau of Labor Statistics showed October's preliminary gain was revised up — from 12,000 jobs to 36,000. September's growth was also revised upward, from 223,000 to 255,000.

"Some of the story in November is post-hurricane bounce back," Ernie Tedeschi, the director of economics at The Budget Lab at Yale, wrote on X.

Tedeschi said the revisions for October and September increased the three-month moving average job growth to 173,000 a month. That's in line with this year's trend, suggesting that the weak October report was indeed a hurricane- and strike-fueled outlier.

Slightly fewer people were working or looking for work in November. Labor force participation dropped from 62.6% in October to 62.5%.

Wage growth remained steady, with average hourly earnings increasing 4% year-over-year in November, matching October's rate.

The Fed's two most recent interest-rate decisions were both cuts, a 50-basis-point cut in September and a 25-basis-point cut in November. Americans will know if there will be one more rate cut this year on December 18.

The CME FedWatch tool, which shows what traders think Fed rate decisions will be, showed a roughly 90% chance of a 25-basis-point cut in December after the BLS release, up from around 70% before the report.

This is a developing story. Please check back for updates.

Last week, a tweet by Stanford researcher Yegor Denisov-Blanch went viral within Silicon Valley. “We have data on the performance of >50k engineers from 100s of companies,” he tweeted. “~9.5% of software engineers do virtually nothing: Ghost Engineers.”

Denisov-Blanch said that tech companies have given his research team access to their internal code repositories (their internal, private Githubs, for example) and, for the last two years, he and his team have been running an algorithm against individual employees’ code. He said that this automated code review shows that nearly 10 percent of employees at the companies analyzed do essentially nothing, and are handsomely compensated for it. There are not many details about how his team’s review algorithm works in a paper about it, but it says that it attempts to answer the same questions a human reviewer might have about any specific segment of code, such as:

• “How difficult is the problem that this commit solves?
• How many hours would it take you to just write the code in this commit assuming you could fully focus on this task?
• How well structured is this source code relative to the previous commits? Quartile within this list
• How maintainable is this commit?”

Ghost Engineers, as determined by his algorithm, perform at less than 10 percent of the median software engineer (as in, they are measured as being 10 times worse/less productive than the median worker).

Denisov-Blanch wrote that tens of thousands of software engineers could be laid off and that companies could save billions of dollars by doing so. “It is insane that ~9.5 percent of software engineers do almost nothing while collecting paychecks,” Denisov-Blanch tweeted. “This unfairly burdens teams, wastes company resources, blocks jobs for others, and limits humanity’s progress. It has to stop.”

The Stanford research has not yet been published in any form outside of a few graphs Denisov-Blanch shared on Twitter. It has not been peer reviewed. But the fact that this sort of analysis is being done at all shows how much tech companies have become focused on the idea of “overemployment,” where people work multiple full-time jobs without the knowledge of their employers and its focus on getting workers to return to the office. Alongside Denisov-Blanch’s project, there has been an incredible amount of investment in worker surveillance tools. (Whether a ~9.5 percent rate of workers not being effective is high is hard to say; it's unclear what percentage of workers overall are ineffective, or what other industry's numbers look like).

Over the weekend, a post on the r/sysadmin subreddit went viral both there and on the r/overemployed subreddit. In that post, a worker said they had just sat through a sales pitch from an unnamed workplace surveillance AI company that purports to give employees “red flags” if their desktop sits idle for “more than 30-60 seconds,” which means “no ‘meaningful’ mouse and keyboard movement,” attempts to create “productivity graph” based on computer behavior, and pits workers against each other based on the time it takes to complete specific tasks. 

What is becoming clear is that companies are becoming obsessed with catching employees who are underperforming or who are functionally doing nothing at all, and, in a job market that has become much tougher for software engineers, are feeling emboldened to deploy new surveillance tactics. 

“In the past, engineers wielded a lot of power at companies. If you lost your engineers or their trust or demotivated the team—companies were scared shitless by this possibility,” Denisov-Blanch told 404 Media in a phone interview. “Companies looked at having 10-15 percent of engineers being unproductive as the cost of doing business.”

Denisov-Blanch and his colleagues published a paper in September outlining an “algorithmic model” for doing code reviews that essentially assess software engineer worker productivity. The paper claims that their algorithmic code assessment model “can estimate coding and implementation time with a high degree of accuracy,” essentially suggesting that it can judge worker performance as well as a human code reviewer can, but much more quickly and cheaply. 

I asked Denisov-Blanch if he thought his algorithm was scooping up people whose work contributions might not be able to be judged by code commits and code analysis alone. He said that he believes the algorithm has controlled for that, and that companies have told him specific workers who should be excluded from analysis because their job responsibilities extend beyond just pushing code. 

“Companies are very interested when we find these people [the ghost engineers] and we run it by them and say ‘it looks like this person is not doing a lot, how does that fit in with their job responsibilities?’” Denisov-Blanch said. “They have to launch a low-key investigation and sometimes they tell us ‘they’re fine,’ and we can exclude them. Other times, they’re very surprised.”

He said that the algorithm they have developed attempts to analyze code quality in addition to simply analyzing the number of commits (or code pushes) an engineer has made, because number of commits is already a well-known performance metric that can easily be gamed by pushing meaningless updates or pushing then reverting updates over and over. “Some people write empty lines of code and do commits that are meaningless,” he said. “You would think this would be caught during the manual review process, but apparently it isn’t. We started this research because there was no good way to use data in a scalable way that’s transparent and objective around your software engineering team.”

Much has been written about the rise of “overemployment” during the pandemic, where workers take on multiple full-time remote jobs and manage to juggle them. Some people have realized that they can do a passable enough job at work in just a few hours a day or less. 

“I have friends who do this. There’s a lot of anecdotal evidence of people doing this for years and getting away with it. Working two, three, four hours a day and now there’s return-to-office mandates and they have to have their butt in a seat in an office for eight hours a day or so,” he said. “That may be where a lot of the friction with the return-to-office movement comes from, this notion that ‘I can’t work two jobs.’ I have friends, I call them at 11 am on a Wednesday and they’re sleeping, literally. I’m like, ‘Whoa, don’t you work in big tech?’ But nobody checks, and they’ve been doing that for years.”

Denisov-Blanch said that, with massive tech layoffs over the last few years and a more difficult job market, it is no longer the case that software engineers can quit or get laid off and get a new job making the same or more money almost immediately. Meta and X have famously done huge rounds of layoffs to its staff, and Elon Musk famously claimed that X didn’t need those employees to keep the company running. When I asked Denisov-Blanch if his algorithm was being used by any companies in Silicon Valley to help inform layoffs, he said: “I can’t specifically comment on whether we were or were not involved in layoffs [at any company] because we’re under strict privacy agreements.”

The company signup page for the research project, however, tells companies that the “benefits of participation” in the project are “Use the results to support decision-making in your organization. Potentially reduce costs. Gain granular visibility into the output of your engineering processes.”

Denisov-Blanch said that he believes “very tactile workplace surveillance, things like looking at keystrokes—people are going to game them, and it creates a low trust environment and a toxic culture.” He said with his research he is “trying to not do surveillance,” but said that he imagines a future where engineers are judged more like salespeople, who get commission or laid off based on performance. 

“Software engineering could be more like this, as long as the thing you’re building is not just counting lines or keystrokes,” he said. “With LLMs and AI, you can make it more meritocratic.”

Denisov-Blanch said he could not name any companies that are part of the study but said that since he posted his thread, “it has really resonated with people,” and that many more companies have reached out to him to sign up within the last few days.

A system of non-competition clauses enforced by the European Space Agency’s (ESA) workforce suppliers is allegedly trapping aerospace professionals who work at ESA’s facilities across Europe in a professional dead-end street. Their contracts prevent job mobility and the possibility to earn better pay, a large number of contractors have alleged to Ars Technica. And as nations that host ESA facilities have enacted laws that give some contractors greater rights, the ESA itself has adopted a policy that will shift more of its indirect employees to service positions, which would not be protected by these laws.

When asked about these issues, an ESA spokesperson said there are “employment conditions in which ESA is not to interfere” and that non-competition clauses “remain within the remit of the employer and the employee.”

The European Space Agency, Europe’s version of NASA, is an intergovernmental organization comprising 22 member states. With facilities in six European countries, the agency relies on contractors—scientists, engineers, and admin workers—hired through payroll companies. These contractors, who work alongside ESA’s staff on the agency’s space projects, constitute over half of the agency’s workforce, according to available estimates.

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• President-elect Donald Trump has threatened to slap tariffs on goods from Mexico, Canada, and China.
• Tariffs raise money but may also affect prices and employment, and they can lead to trade wars.
• Here's a guide to tariffs, including who pays them, how they work, and how they affect the economy.

Tariffs are back in the spotlight after President-elect Donald Trump pledged to impose 25% tariffs on goods from Mexico and Canada and an additional 10% duty on goods from China, unless those countries stop the flow of illegal immigration and narcotics into the US.

Trump's tariff threat could be a negotiating ploy to win better terms with America's three biggest trading partners. But if the tariffs are imposed, they could affect prices, employment, and the broader US economy — especially given the risk that China, Canada, and Mexico may retaliate with tariffs, triggering a trade war.

Here's what you should know about tariffs and why they matter.

What are tariffs?

A tariff is effectively a government tax specifically levied on foreign goods imported into a country.

Tariffs date back more than 200 years and were historically used by authorities to raise money. The US government collected most of its revenue from tariffs before introducing an income tax in the early 1900s.

Authorities now use tariffs primarily to protect domestic industries from foreign competition and punish trading partners for bad behavior.

There are four types of tariffs:

• An ad valorem tariff is calculated based on the value of the good. If an imported product is worth $10 and the tariff is 10%, the importer has to pay $1.
• A specific tariff is imposed on a per-unit basis, so the value of the item doesn't matter. An importer might have to pay $1 for every pound of cocoa beans it brings into the country, whether it brings in 10 bags or 1,000.
• A compound tariff combines elements of ad valorem and specific tariffs. The tariff on an imported item could be $1 per pound or 5% of its value, depending on which generates more revenue.
• A mixed tariff applies both an ad valorem and a specific tariff, meaning an importer might have to pay $5 a pound and 10% of its value as well.

Who pays tariffs? How do they work?

The news that Trump threatened Canada with tariffs, along with Mexico and China, has made it important to understand who pays tariffs and how they work.

In the US, the simple answer is that the person or business importing the tariffed product into the US pays the tariff, and the money is paid to the US Treasury.

For example, if General Motors imports parts from its factories in Mexico and assembles its cars in the US, it would have to pay tariffs to bring in those parts.

Customs and Border Protection agents collect tariffs at 328 ports of entry, including docks, airports, and border crossings.

How do tariffs affect prices and the economy?

Tariffs raise costs for importers, and to protect their profit margins, importers typically pass on those costs by charging higher prices to their domestic customers — whether they're companies or consumers.

Those price hikes can benefit domestic producers because the hikes make their goods relatively cheaper to bring to market than imported alternatives. For example, they might make it easier for US apparel manufacturers to compete with Chinese fast-fashion companies such as Shein and Temu.

Tariffs can also spur foreign producers to drop their prices to try to keep their products competitive, hurting their domestic industry and their country's economy, and partly offsetting the upward pressure on prices from tariffs.

The countries involved may also trade lower volumes of the product if both supply and demand fall in response to the tariffs.

A 2019 research paper on the initial impact of Trump's first-term tariffs found they fully passed through into the domestic prices of imported goods — and hurt consumer choice by reducing the availability of imported varieties.

Tariffs are frequently pitched as a tool to protect domestic jobs. A National Bureau of Economic Research working paper published in January found that the 2018-2019 trade war did not affect employment in newly protected sectors. The study also found that retaliatory tariffs from other countries contributed to job losses in domestic sectors such as agriculture and were only partly mitigated by federal subsidies.

Advantages of tariffs can include stronger domestic industries, increased government revenue, and pressure on other countries to stop unfair trading practices and help address issues such as illegal immigration and the drug trade.

Disadvantages can include tariffs' effects on consumers in terms of higher prices and reduced choice, plus the risk of retaliatory tariffs that could lead to employment losses in some industries and a full-blown trade war.

Moreover, a study published in The Economic Journal in 2021 found that retaliatory tariffs "disproportionately targeted more Republican areas," suggesting they were aimed at Trump's base to try to maximize their political power.

How Trump's tariff plan would work

Trump is no stranger to using tariffs. He called himself "Tariff Man" during his first term for imposing tariffs on products such as steel and aluminum plus a wide range of Chinese goods.

He replaced the North American Free Trade Agreement with the United States-Mexico-Canada Agreement in his first term, allowing most goods to continue freely passing between those countries.

That would change if Trump goes ahead with sweeping tariffs on Mexican and Canadian goods. Products passing into the US from its northern and southern borders would be subject to duties, and the money collected would flow to the US Treasury.

A key question is whether the tariffs would result in higher inflation. Inflation, or the annualized pace of price increases, hit a 40-year high of more than 9% in 2022, spurring the Federal Reserve to raise interest rates from nearly zero to above 5% in less than 18 months.

Inflation has dropped below 3% in recent months, freeing the Fed to begin cutting rates. The question is whether Trump's tariffs would cause price growth to accelerate again and delay further rate cuts — especially as people's deep concerns about higher living costs was a key reason they reelected him.