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Howard Lutnick says Trump’s tariffs will create ‘great jobs of the future’—fixing factory robots. Labor experts disagree

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  • The future of labor is providing maintenance for automated factory technology, Commerce Secretary Howard Lutnick told CNBC. He posited that the growth of manufacturing in the U.S. as a result of President Donald Trump’s tariffs would spur more jobs in the form of factory work. Labor experts are dubious about the growth and sustainability of these jobs.

Commerce Secretary Howard Lutnick sees one positive byproduct of President Donald Trump’s tariff plan: a “manufacturing renaissance” in the U.S. that would lead to the next three generations of Americans holding factory jobs.

Trump proposed steep tariffs during his first days back in office, cracking down on imports from China, Vietnam, and other manufacturing capitals, in an attempt to develop production centers and supply chains to the U.S. Lutnick suggested an increase in factory work—bolstered by automated robotic labor—would provide an opportunity for American workers to find stable and well-paying jobs, beginning at $70,000 to $80,000 per year. 

“It’s time to train people not to do the jobs of the past, but to do the great jobs of the future,” Lutnick told CNBC’s “The Exchange” earlier this week. “This is the new model, where you work in these kind of plants for the rest of your life, and your kids work here, and your grandkids work here.”

Robots are already starting to hit production lines. U.S. automakers installed nearly 10% more robots in factories this year than the year before, according to the trade group International Federation of Robotics. Hyundai Motor Group, for example, acquired robotics company Boston Dynamics for $1.1 billion in 2021.

The increase in automation would provide opportunities for tradespeople—specifically people in community college or those who decide not to pursue higher education—to become highly trained, according to Lutnick.

“You should see an auto plant,” he said. “It’s highly automated, but the people—the [4,000] or 5,000 people that work there—they are trained to take care of those robotic arms. They’re trained to keep the air conditioning [going].”

A Department of Commerce spokesperson told Fortune the agency was committed to reversing the trend of the manufacturing jobs leaving the U.S.. Since 1979, the country has lost 6.5 million manufacturing jobs due to outsourcing and previous policies, the person said.

“Secretary Lutnick is committed to revitalizing critical manufacturing in the United States,” the spokesperson said in a statement.

More robots, fewer jobs

But labor experts aren’t convinced the key to more—and better—U.S. jobs lies in factory automation. The increased use of industrial robots may actually have a negative impact on the workforce, according to a 2020 study from Massachusetts Institute of Technology professor Daron Acemoglu. Along with Boston University professor Pascual Restrepo, he calculated that adding one robot for every 1,000 U.S. workers would cause wages to decline by 0.42%, and the employment-to-population ratio to decrease by 0.2%. These small percentages add up, costing the U.S. about 400,000 jobs so far, according to the study.

While robots do increase factory efficiency, it comes at the expense—not the addition—of factory jobs, the study showed.

“Our evidence shows that robots increase productivity,” Acemoglu said in an interview with the MIT Sloan School of Management. “They are very important for continued growth and for firms, but at the same time they destroy jobs and they reduce labor demand. Those effects of robots also need to be taken into account.”

The role of unionizing

Eric Blanc, a labor historian and Rutgers University labor studies professor, argues that beyond the theoretical idea of creating more factory jobs, there needs to be consideration of the quality and sustainability of those jobs. 

“The reason people associate factory jobs with good jobs and have this nostalgic view of the heyday of American manufacturing in the 1950s, when you could have one breadwinner providing for the whole family—that was the product of unionization,” Blanc recently told Fortune

While a wave of unionization efforts in the 1930s and ‘40s created regulations and standards for factory jobs to be favored among American workers, the Trump administration is decidedly anti-union, Blanc said. In late March, Trump signed an executive order directing federal agencies to cease collective bargaining with federal unions, an action a federal judge has since blocked.

Without factory unions, workers would be subject to 12-hour days, lower wages, and the possibility of injury. A 2016 UC Berkeley Center for Labor Research and Education study found one-third of U.S. manufacturing workers relied on a government assistance program such as food stamps, and pay for manufacturing jobs lag behind non-manufacturing jobs.

“Just promising more factory jobs is not going to bring back prosperity,” Blanc said.

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Genesys CEO: How empathetic AI can scale our humanity during economic uncertainty

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In light of the U.S. tariff announcements and rising economic uncertainty, I believe companies will instinctively turn to efficiency measures to weather potential disruption. And while efficiency is critical, it’s empathy—together with operational rigor—that will determine who thrives.

In an era increasingly shaped by AI, the most memorable customer experiences harness the power of “and”—they are fast and human, automated and deeply personal. Being seen and understood isn’t at odds with scale. It’s what elevates it. 

From transactions to trust

Over the past decade, organizations have invested in technology to make customer service faster, more consistent, and less reliant on human intervention.

While automated chatbots and self-service tools have become commonplace, many experiences still feel impersonal and often frustrating. That’s because they were built for efficiency, not empathy.

But business is shifting from a service economy, where value is measured by speed and volume, to an experience economy, where value is created through emotional resonance, trust, and personalization. 

This concept of the “experience economy” was first introduced by B. Joseph Pine II and James H. Gilmore, who argued that we are moving into an era where the primary offering is not a product or a service, but rather the experience itself. In their words, “work is theatre and every business a stage.” That framing may sound dramatic, but it’s more relevant now than ever. Consumers aren’t just buying outcomes. They’re buying how those outcomes feel.

It’s a shift that’s easy to see in our daily lives. We’ll choose a coffee shop not just for the quality of the coffee, but for how the space makes us feel. We’ll return to a brand that remembers our preferences. We’ll tell friends about the airline that made a frustrating delay easier to navigate with clarity. These experiences create differentiation in a world where many services have become commoditized. In fact, according to a survey we conducted in 2024, 30% of consumers say they have stopped using a brand after a negative experience in the past year.

The five levels of experience

Technology has historically lagged behind this evolution, but that’s changing, too. Artificial intelligence is now capable of understanding sentiment, adapting to behavior in real time and personalizing every interaction. This evolution requires more than incremental upgrades. It calls for a new approach—one where conversations across channels, moments, and touchpoints are designed to feel seamless, personalized, and emotionally intelligent.

To understand how organizations are navigating this shift, we developed a five-level maturity model that maps progress from basic transactions to fully orchestrated, emotionally intelligent experiences.

Levels 1 and 2: Rely on rigid, rules-based systems like legacy phone trees or entry-level chatbots to handle simple customer requests. These interactions are often siloed, reactive, and limited in their ability to adapt. 

Level 3: Integrates predictive and generative AI to personalize interactions in real time. Virtual assistants don’t just answer questions—they start to anticipate needs, resolve problems proactively, and adapt based on context.

Agentic AI is the bridge to the highest levels of experience orchestration, enabling systems to take initiative, make decisions, and coordinate actions across channels to pave the way for emotionally intelligent and fully orchestrated experiences.

Level 4: AI will begin to reflect emotional intelligence. It will detect tone and sentiment, respond with appropriate empathy, and even switch communication styles based on the customer’s preferences or language. This will enable systems to handle more complex, emotionally charged conversations like resolving a billing dispute or managing a delayed flight without losing the human touch.

Level 5: Universal orchestration. This is an aspirational frontier. AI will be adaptive and predictive, and capable of acting as a kind of personalized virtual concierge that understands individuals holistically across time and channels. For many industries, it is poised to become a competitive imperative.

The economic value of empathy

There’s no doubt that automation and augmentation drive real value. Businesses that implement AI-driven tools to handle routine customer interactions and provide real-time employee assistance often see meaningful improvements in efficiency, cost savings, and scalability, while also driving increases in employee engagement and customer satisfaction.

But the real prize lies beyond efficiency, in loyalty.

When businesses invest in empathetic AI that can personalize experiences, optimize journeys, and foster trust, they unlock a new level of potential economic impact. Consider a regional bank with a thousand customer service agents. By layering empathetic AI capabilities into its operations, it could not only reduce churn and improve employee retention but also create new top-line opportunities through more effective upselling, cross-selling, and long-term customer loyalty.

Empathy, in a very real way, can pay.

Empathy by design

Empathy is often thought of as a uniquely human trait. But in the context of AI, it becomes both a design challenge and a philosophical one.

Building emotionally intelligent systems requires training models to recognize more than just words. They must interpret tone, pace, hesitation, and sentiment. They must connect disparate data points to understand context, like why a customer is calling, how they’re feeling, and what they’ve experienced before, then adjust their response accordingly.

Some of the more advanced systems now match customers with agents based on emotional state and skill compatibility, offer proactive help before an issue escalates, and adjust tone in real time. They’re also capable of continuous learning, using journey data to refine interactions and ensure the experience gets better over time.

This is a new kind of intelligence. This is empathy by design. 

The human future of AI

As we move further into the experience economy—during times of macroeconomic tailwinds or headwinds—one thing is clear: Being human is a business advantage. In fact, a Forrester analysis shows that companies that improve CX can drive significant revenue growth. 

The most valuable experiences in life, and in business, are those that make us feel seen, understood, and valued. They help turn customers into loyalists, and brands into beacons. Empathy isn’t a feature. It’s the future. And AI, when built with that truth at its core, can help us deliver something truly powerful: technology that scales service and scales humanity.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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The U.S. trade deficit: It’s time to dump do-it-yourself economics and go back to basics

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Since President Trump’s inauguration on Jan. 20, it seems that many people—particularly the chattering classes—have suddenly become experts in international trade. Mr. Trump’s tariffs have spawned a litany of what economist David Henderson termed “do-it-yourself economics.” These are economic ideas that reflect the intuitive notions of laypeople and owe nothing to the ideas generated by trained economists and the economics profession. Not surprisingly, Henderson concluded that the gap between the notions of do-it-yourself economics and orthodox economics is widest in the sphere of international trade.

This gap is evident in the current brouhaha over trade and tariffs, particularly in the two opposing camps: those responsible for formulating the administration’s trade agenda (Mr. Trump and his cabinet) and those critiquing it (primarily commentators and journalists). The result of this dynamic is not only that the Trump administration has enacted wrongheaded trade policies, but also that the opposition to these policies is largely ineffective or irrelevant. Both camps are engaged in do-it-yourself economics.

The misconceptions emanating from both camps stem from one common oversight: Neither Mr. Trump nor his detractors have familiarized themselves with the savings-investment identity, a basic yet crucial mechanism that governs the magnitude of a country’s trade balance. Indeed, by definition, a country’s trade balance is governed entirely by the gap between its domestic saving and domestic investment. If a country’s domestic saving is greater than its domestic investment, like China’s, it will register a trade surplus. Likewise, if a country has a savings deficiency, like the United States, it will register a trade deficit. The United States’ negative trade balance, which the country has registered every year starting in 1975, is “made in the USA,” a result of its savings deficiency. To view the trade balance correctly, the focus should be on the domestic economy.

As it turns out, one of us, Hanke, analyzed the United States’ large and persistent trade deficits and found that they are primarily driven by its large and persistent fiscal deficits at the federal, state, and local government levels. In other words, in the aggregate, there is a savings deficiency in the United States, and this savings deficiency comes from the public sector—the U.S. private sector actually generates a savings surplus. This aggregate gap between savings and investment is filled by foreign imports of goods and services, resulting in an easy-to-finance capital inflow surplus and a trade deficit.

Armed with the basic truth of the savings-investment identity, we now turn to Mr. Trump’s camp. Mr. Trump and his advisors believe that the United States’ trade deficit is the result of foreigners ripping off and taking advantage of the United States. Indeed, Uncle Sam is characterized as being a victim of unfair trade practices. This characterization is clearly wrong on two counts. First, the trade deficit is not caused by foreigners; rather, it is homegrown, the result of choices made by Americans (in the aggregate) to invest beyond what they save.

Second, the trade deficit is not necessarily harmful. It instead appears to be a privilege extended to Americans by foreigners willing to invest in U.S. assets. This is a symbiotic relationship: Americans get cheap access to capital, while foreign governments and institutions get a safe place to park their money and earn a return.

When it comes to trade policy, the Trump administration’s detractors are just as lost as the White House. A recent high-profile article in the New York Times—Totally Silly.’ Trump’s Focus on Trade Deficit Bewilders Economists,” contains an indicative summary of what journalists and commentators have to say about trade deficits. There’s just one little problem with the article and its respondents: No one ever explicitly mentions the true source of the trade deficit, which is elucidated by one of the most basic identities in economics. The identity tells us that if savings are less than investment, the gap must be filled by a trade deficit.

Both Mr. Trump’s cabinet and those criticizing his policies have a fundamental misunderstanding of what drives the U.S. trade deficit. As a result, the trade debate has turned into a futile filibuster, highlighting the dangers of do-it-yourself economics. It’s time to go back to the basics.

Steve H. Hanke is a professor of applied economics at the Johns Hopkins University and the author, with Leland Yeager, of Capital, Interest, and Waiting. Caleb Hofmann is a research scholar at the Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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