Employers are struggling to find the best way to pinpoint the talent they need to drive their businesses to success in the rapidly changing world of AI. Accenture CEO Julie Sweet, though, has a simple question to identify whether her interviewees are ready for the job.

In an interview on the In Good Company podcast with Nicolai Tangen, the CEO of Norges Bank Investment Management, Sweet was asked what she looked for when hiring new consultants at the $64 billion tech giant.

“One question that we ask everyone, regardless of if you’re a consultant or you’re working in technology … we say: ‘What have you learned in the last six months?’ 

“A lot of the time people are asking me, ‘How do I know if someone’s a learner?’ And it’s a very simple way to know. If someone can’t answer that question—and by the way, we don’t care if it’s ‘I learned to bake a cake’—if they can’t answer that question, then we know that they’re not a learner.”

When asked by Tangen what Sweet herself had learned in the last six months, the Accenture CEO said it had mostly been around AI. During an investor call in December, Sweet said she had met with 30 CEOs in the preceding two months, with AI applications at the top of most of their agendas.

Sweet also said she had managed to learn how to bake bread amid her hectic schedule in the last six months.  

Sweet’s curveball question for new hires is indicative of how companies are shifting their recruitment practices following the onset of generative AI, which is upending job specs in every department, requiring a new type of employee.

Bosses have argued that new employees need to be dynamic depending on the changing needs of their business and how AI can be used to supplement their work. 

LinkedIn’s chief operating officer, Daniel Shapero, told Fortune that he asks prospective hires to tell him how they used AI to determine whether they have the desire to learn the tech on the job.

​”What that demonstrates is, if you’re comfortable using AI, then you’re more likely to be someone that helps their organization become more AI-centric,” said Shapero. 

“You hear about people planning family trips, you hear about people summarizing meeting notes. You hear people generating creative ideas for customers. And so there’s a very wide range of things AI can be used for.”

Amid increased uncertainty about the skills and aptitude required for the future of work, Accenture’s Sweet says a strong human resources department has become increasingly vital. 

“I think the best thing to be right now, one of the best fields to be in is HR, because right after gen AI on CEOs’ agendas is talent, and how you train talent has to completely change.”

Editor’s note: A version of this article first appeared on Fortune.com on January 8, 2025.

This story was originally featured on Fortune.com

Source link

President Donald Trump is taking a blowtorch to the rules that have governed world trade for decades. The “reciprocal’’ tariffs that he is expected to announce Wednesday are likely to create chaos for global businesses and conflict with America’s allies and adversaries alike.

Since the 1960s, tariffs — or import taxes — have emerged from negotiations between dozens of countries. Trump wants to seize the process.

“Obviously, it disrupts the way that things have been done for a very long time,’’ said Richard Mojica, a trade attorney at Miller & Chevalier. “Trump is throwing that out the window … Clearly this is ripping up trade. There are going to have to be adjustments all over the place.’’

Pointing to America’s massive and persistent trade deficits – not since 1975 has the U.S. sold the rest of the world more than it’s bought — Trump charges that the playing field is tilted against U.S. companies. A big reason for that, he and his advisers say, is because other countries usually tax American exports at a higher rate than America taxes theirs.

Trump has a fix: He’s raising U.S. tariffs to match what other countries charge.

The president is an unabashed tariff supporter. He used them liberally in his first term and is deploying them even more aggressively in his second. Since returning to the White House, he has slapped 20% tariffs on China, unveiled a 25% tax on imported cars and trucks set to take effect Thursday, effectively raised U.S. taxes on foreign steel and aluminum and imposed levies on some goods from Canada and Mexico, which he may expand this week.

Economists don’t share Trump’s enthusiasm for tariffs. They’re a tax on importers that usually get passed on to consumers. But it’s possible that Trump’s reciprocal tariff threat could bring other countries to the table and get them to lower their own import taxes.

“It could be win-win,” said Christine McDaniel, a former U.S. trade official now at George Mason University’s Mercatus Center. “It’s in other countries’ interests to reduce those tariffs.”

She noted that India has already cut tariffs on items from motorcycles to luxury cars and agreed to ramp up purchases of U.S. energy.

What are reciprocal tariffs and how do they work?

They sound simple: The United States would raise its tariff on foreign goods to match what other countries impose on U.S. products.

“If they charge us, we charge them,’’ the president said in February. “If they’re at 25, we’re at 25. If they’re at 10, we’re at 10. And if they’re much higher than 25, that’s what we are too.’’

But the White House didn’t reveal many details. It has directed Commerce Secretary Howard Lutnick to deliver a report this week about how the new tariffs would actually work.

Among the outstanding questions, noted Antonio Rivera, a partner at ArentFox Schiff and a former attorney with U.S. Customs and Border Protection, is whether the U.S. is going to look at the thousands of items in the tariff code – from motorcycles to mangos — and try to level the tariff rates out one by one, country by country. Or whether it will look more broadly at each country’s average tariff and how it compares to America. Or something else entirely.

“It’s just a very, very chaotic environment,” said Stephen Lamar, president and CEO of the American Apparel & Footwear Association. “It’s hard to plan in any sort of long-term, sustainable way.’’

How did tariffs get so lopsided?

America’s tariffs are generally lower than those of its trading partners. After World War II, the United States pushed for other countries to lower trade barriers and tariffs, seeing free trade as a way to promote peace, prosperity and American exports around the world. And it mostly practiced what it preached, generally keeping its own tariffs low and giving American consumers access to inexpensive foreign goods.

Trump has broken with the old free trade consensus, saying unfair foreign competition has hurt American manufacturers and devastated factory towns in the American heartland. During his first term, he slapped tariffs on foreign steel, aluminum, washing machines, solar panels and almost everything from China. Democratic President Joe Biden largely continued Trump’s protectionist policies.

The White House has cited several examples of especially lopsided tariffs: Brazil taxes ethanol imports, including America’s, at 18%, but the U.S. tariff on ethanol is just 2.5%. Likewise, India taxes foreign motorcycles at 100%, America just 2.4%.

Does this mean the U.S. been taken advantage of?

The higher foreign tariffs that Trump complains about weren’t sneakily adopted by foreign countries. The United States agreed to them after years of complex negotiations known as the Uruguay Round, which ended in a trade pact involving 123 countries.

As part of the deal, the countries could set their own tariffs on different products – but under the “most favored nation’’ approach, they couldn’t charge one country more than they charged another. So the high tariffs Trump complains about aren’t aimed at the United States alone. They hit everybody.

Trump’s grievances against U.S. trading partners also come at an odd time. The United States, running on strong consumer spending and healthy improvements in productivity, is outperforming the world’s other advanced economies. The U.S. economy grew nearly 9% from just before COVID-19 hit through the middle of last year — compared with just 5.5% for Canada and just 1.9% for the European Union. Germany’s economy shrank 2% during that time.

Trump’s plan goes beyond foreign countries’ tariffs

Not satisfied with scrambling the tariff code, Trump is also going after other foreign practices he sees as unfair barriers to American exports. These include subsidies that give homegrown producers an advantage over U.S. exports; ostensible health rules that are used to keep out foreign products; and loose regulations that encourage the theft of trade secrets and other intellectual property.

Figuring out an import tax that offsets the damage from those practices will add another level of complexity to Trump’s reciprocal tariff scheme.

The Trump team is also picking a fight with the European Union and other trading partners over so-called value-added taxes. Known as VATs, these levies are essentially a sales tax on products that are consumed within a country’s borders. Trump and his advisers consider VATs a tariff because they apply to U.S. exports.

Yet most economists disagree, for a simple reason: VATs are applied to domestic and imported products alike, so they don’t specifically target foreign goods and haven’t traditionally been seen as a trade barrier.

And there’s a bigger problem: VATs are huge revenue raisers for European governments. “There is no way most countries can negotiate over their VAT … as it is a critical part of their revenue base,’’ Brad Setser, senior fellow at the Council on Foreign Relations, posted on X.

Paul Ashworth, chief North America economist for Capital Economics, says that the top 15 countries that export to the U.S. have average VATs topping 14%, as well as duties of 6%. That would mean U.S. retaliatory tariffs could reach 20% — much higher than Trump’s campaign proposal of universal 10% duties.

Tariffs and the trade deficit

Trump and some of his advisers argue that steeper tariffs would help reverse the United States’ long-standing trade deficits.

But tariffs haven’t proven successful at narrowing the trade gap: Despite the Trump-Biden import taxes, the deficit rose last year to $918 billion, second-highest on record.

The deficit, economists say, is a result of the unique features of the U.S. economy. Because the federal government runs a huge deficit, and American consumers like to spend so much, U.S. consumption and investment far outpaces savings. As a result, a chunk of that demand goes to overseas goods and services.

The U.S. covers the cost of the trade gap by essentially borrowing from overseas, in part by selling treasury securities and other assets.

“The trade deficit is really a macroeconomic imbalance,” said Kimberly Clausing, a UCLA economist and former Treasury official. “It comes from this lack of desire to save and this lack of desire to tax. Until you fix those things, we’ll run a trade imbalance.”

This story was originally featured on Fortune.com

AI microchip supplier Nvidia, the world’s most valuable company by market cap, remains heavily dependent on a few anonymous customers that collectively contribute tens of billions of dollars in revenue. 

The AI chip darling once again warned investors in its quarterly 10-Q filing to the SEC that it has key accounts so crucial that their orders each crossed the threshold of 10% of Nvidia’s global consolidated turnover. 

An elite trio of particularly deep-pocketed customers, for example, individually purchased between $10 billion and $11 billion worth of goods and services across the first nine months that ended in late October.

Fortunately for Nvidia investors, this won’t change anytime soon. Mandeep Singh, global head of technology research at Bloomberg Intelligence, says he believes founder and CEO Jensen Huang’s prediction that spending will not stop.  

“The data-center training market could hit $1 trillion without any real pullback,” he says. By that point, Nvidia’s share will almost certainly drop markedly from its current 90%. But it could still be in the hundreds of billions of dollars in revenue annually.

Nvidia remains supply constrained

Outside of defense contractors living off the Pentagon, it’s highly unusual that a company has such a concentration of risk among a handful of customers—let alone one poised to become the first worth the astronomical sum of $4 trillion.

Looking at Nvidia’s accounts on a strictly three-month basis, there were four anonymous whales that, in total, comprised nearly every second dollar of sales in the second fiscal quarter; this time at least one of them has dropped out since now only three still meet that criteria. 

Singh told Fortune the anonymous whales likely include Microsoft, Meta, and possibly Super Micro. But Nvidia declined to comment on the speculation.

Nvidia only refers to them as Customers A, B, and C, and all told they purchased a collective $12.6 billion in goods and services. This was more than a third of Nvidia’s overall $35.1 billion recorded for the fiscal third quarter through late October. 

Their share was also divided up equally with each accounting for 12%, suggesting they were likely receiving a maximum amount of chips allocated to them rather than as many as they might have ideally wanted. 

This would fit with comments from founder and CEO Jensen Huang that his company is supply constrained. Nvidia cannot simply pump out more chips, since it has outsourced wholesale fabrication of its industry-leading AI microchips to Taiwan’s TSMC and has no production facilities of its own.

Middlemen or end user?

Importantly, Nvidia’s designation of major anonymous customers as Customer A, Customer B, and so on is not fixed from one fiscal period to the next. They can and do change places, with Nvidia keeping their identity a trade secret for competitive reasons; no doubt these customers would not like their investors, employees, critics, activists, and rivals being able to see exactly how much money they spend on Nvidia chips.

For example, one party designated “Customer A” bought around $4.2 billion in goods and services over the past quarterly fiscal period. Yet it appears to have accounted for less in the past, since it does not exceed the 10% mark across the first nine months in total.

Meanwhile “Customer D” appears to have done the exact opposite, reducing purchases of Nvidia chips in the past fiscal quarter yet nevertheless representing 12% of turnover year to date.

Since their names are secret, it’s difficult to say whether they are middlemen like the troubled Super Micro Computer, which supplies data center hardware, or end users like Elon Musk’s xAI. The latter came out of nowhere, for example, to build up its new Memphis compute cluster in just three months’ time. 

Longer-term risks for Nvidia include the shift from training to inference chips

Ultimately, however, there are only a handful of companies with the capital to be able to compete in the AI race, as training large language models can be exorbitantly costly. Typically these are the cloud computing hyperscalers such as Microsoft.

Oracle, for example, recently announced plans to build a zettascale data center with over 131,000 Nvidia state-of-the-art Blackwell AI training chips, which would be more powerful than any individual site yet existing. 

It’s estimated the electricity needed to run such a massive compute cluster would be equivalent to the output capacity of nearly two dozen nuclear power plants.

Bloomberg Intelligence analyst Singh sees only a few longer-term risks for Nvidia. For one, some hyperscalers will likely reduce orders eventually, diluting its market share. One such likely candidate is Alphabet, which has its own training chips called TPUs.

Secondly, its dominance in training is not matched by inference, which runs generative AI models after they have already been trained. Here, the technical requirements are not nearly as state of the art, meaning there is much more competition, not just from rivals like AMD but also companies with their own custom silicon like Tesla. Eventually inference will be a much more meaningful business as more and more businesses utilize AI. 

“There are a lot of companies trying to focus on that inferencing opportunity, because you don’t need the highest-end GPU accelerator chip for that,” Singh said. 

Asked if this longer-term shift to inferencing was a bigger risk than eventually losing share in the market for training chips, he replied: “Absolutely.”

This story was originally featured on Fortune.com