AI vs. Tariffs: Goldman Sachs on US Manufacturing

AI and Automation: The Key to Reclaiming US Manufacturing Dominance, Analysts Say

as competition with China intensifies, a growing consensus among financial analysts suggests that tariffs alone will not revitalize American manufacturing. Instead, a strategic embrace of artificial intelligence and automation represents the moast viable path toward boosting productivity and regaining a competitive edge.

The pursuit of reshoring factory jobs through steep tariffs on rival nations,a key aspiration of President Donald Trump,is facing increasing scrutiny. While tariffs can offer some incentive, experts contend they are insufficient to overcome fundamental cost disparities. A recent analysis published Thursday indicates that manufacturers should prioritize investment in automation and increasingly accessible AI technologies to drive domestic production.

“A pickup in the pace of innovation-potentially from recent advances in robotics and generative AI-thus remains the catalyst most likely to reverse the long-run stagnation in manufacturing productivity,” stated analysts at goldman Sachs.

Mounting evidence points to a slowdown in U.S. manufacturing, even as China leverages automation and lower labour costs to expand its export market. Data from the U.S. Census Bureau reveals a 6.3% decrease in new orders for manufactured durable goods in April. The Institute of Supply Management Manufacturing Purchasing Managers’ Index (PMI) has also been declining since March, signaling a contraction in the sector.

The current challenges facing U.S. manufacturers are rooted in a broader, two-decade-long slowdown in productivity growth. This decline stems from reduced investment following the 2008 global financial crisis and a deceleration in the rapid technological advancements seen in the early 2000s, according to Goldman Sachs. While the President’s proposed tariff plans for China aim to recapture manufacturing opportunities, the bank argues they are not a comprehensive solution.

“Tariffs are unlikely to result in much reshoring because production costs in other countries are well below the U.S.’ for most products-even after accounting for tariffs-and China will likely continue to grow its exports on the back of cost advantages and industrial policy support,” the analysis concluded.

The Rise of Factory Automation

Instead of relying on trade policy, analysts emphasize the need for the U.S. to address its lagging adoption of factory automation. A recent report from the Boston Consulting Group (BCG) Henderson Institute highlights this disparity. The survey found that only 46% of U.S. manufacturers reported implementing multiple AI use cases in their plants, falling short of the 62% average and significantly behind China’s 77%.

“This is one of the key technologies that I think could drive productivity growth in a cost-competitive manner,” one analyst explained. “And we just haven’t seen that occur on a meaningful scale yet.” The initial reluctance to invest in factory automation was partially attributed to the financial repercussions of the 2008 crisis, but the growing affordability and accessibility of automation and AI now present a meaningful possibility for the U.S.

Companies are already beginning to adapt. MSP Manufacturing, an aviation precision parts-maker, recently integrated AI-powered software that reduced production time for a critical component from 90 minutes to just 22 minutes. “I was like, holy snap, this is going to be a game changer,” said Johnny Goode, president and chief operating officer of MSP Manufacturing, in an interview with Fortune. “Going from 90 minutes to 22 minutes is a big deal, and we’ve seen that get even better as we’ve learned to use the software more.”

Addressing the Global Manufacturing Slowdown

While automation offers the most considerable potential for growth in U.S. manufacturing productivity, Goldman Sachs analysts acknowledge it won’t single-handedly resolve the broader global slowdown. This slowdown is described as “historically unusual,” potentially linked to the maturation of the technology sector. A significant global resurgence in productivity will require widespread advancements and adoption of AI and robotics.

“The main thing that would drive a large pickup in manufacturing productivity and manufacturing growth would be a sharp increase in the pace of innovation,” one analyst stated. “And this type of inflection upwards and technological progress are very hard to predict.” Technological advancements could benefit domestic manufacturing by stimulating investment and improving the technology installed in factories. However, the precise future applications of AI and automation remain uncertain, making it difficult to definitively predict a reversal of the current slowdown.

“We just need to see it happen before we have a lot of confidence in that dynamic being a big driver,” the analyst concluded.

The Productivity Puzzle: Obstacles to AI and Automation adoption

The promise of artificial intelligence and automation in U.S. manufacturing is clear, as highlighted by Goldman Sachs and others. However, realizing this potential faces significant challenges beyond just initial investment. Several interconnected factors currently hinder the widespread adoption of these technologies, slowing the revitalization of American manufacturing. Understanding these obstacles is crucial to formulating effective strategies.

One primary hurdle is the skills gap within the manufacturing workforce. According to a 2024 report by Deloitte and The Manufacturing Institute, the manufacturing skills gap could leave 2.1 million jobs unfilled by 2030.This shortage encompasses various roles, from technicians to data scientists needed to operate, maintain, and optimize automated systems. Without a skilled workforce, investments in AI and automation may prove ineffective.

Another significant challenge is the upfront cost. While the price of automation technologies has decreased, integrating complex systems still requires substantial capital. This is particularly true for small and medium-sized enterprises (SMEs), which constitute a large portion of U.S. manufacturers. These businesses may lack the resources to procure, install, and maintain the necessary infrastructure, perhaps widening the gap between larger and smaller manufacturers.

Furthermore, data security and cybersecurity risks pose growing concerns. As manufacturing facilities become increasingly connected, they are also more vulnerable to cyberattacks. Breaches can disrupt production, compromise sensitive details, and erode trust. Implementing robust cybersecurity measures adds another layer of cost and complexity, potentially deterring adoption, especially for companies that lack the internal expertise to handle these challenges adequately.

Overcoming the Barriers: A Multifaceted Approach

Addressing these obstacles requires a comprehensive strategy involving government, industry, and educational institutions. Here are some key initiatives:

• Investing in Workforce development: Expanding vocational training programs, apprenticeships, and STEM education initiatives can create a pipeline of skilled workers. Public-private partnerships can play a key role in tailoring training to meet the specific demands of automation technologies. Ongoing training ensures workers stay up-to-date with these advancements.
• Providing Financial Incentives for Automation investments: Government programs, such as tax credits, grants, or low-interest loans, can encourage manufacturers, particularly SMEs, to adopt automation. This financial support can help mitigate the upfront cost barrier and make these technologies more accessible.
• Strengthening Cybersecurity Measures: developing and promoting cybersecurity best practices is vital. Offering resources and support to help manufacturers protect thier digital infrastructure. Cybersecurity insurance is also a beneficial option. Furthermore, government-led initiatives to establish cyber-threat intelligence sharing platforms could prove crucial.
• fostering Collaboration and Knowledge Sharing: Creating venues for manufacturers of all sizes to communicate and share their expertise. Industry associations will play an critically important part in these collaborations, facilitating the exchange of best practices and aiding in overcoming challenges.

What are the main reasons for the slow uptake of AI in US factories? Complex implementation costs and workforce skill gaps are the biggest obstacles to automation adoption. These challenges necessitate a collaborative approach between industry leaders,educators,and the government.

As seen at MSP Manufacturing, and as pointed out by various analysts, including those at Goldman Sachs, AI offers a massive path toward productivity gains. Its potential cannot be overemphasized; however, it requires a carefully considered approach to ensure successful implementation. By proactively addressing the barriers, the U.S. can create a more resilient and competitive manufacturing sector. It will also attract skilled workers and fuel a sustained period of economic growth.

Making the Transition: Actionable Tips for Manufacturers

Here are practical steps manufacturers can take to embrace AI and automation successfully:

• Start Small: Begin with pilot projects. Start small, and focus on areas where AI and automation can deliver immediate impact. This reduces risk and allows for a gradual learning curve before making larger investments.
• Prioritize Training and Upskilling: Invest in employee training to ensure workers have the skills required to operate and maintain these new technologies. Partner with educational institutions to develop customized training programs.
• Assess Cybersecurity risks: Conduct thorough cybersecurity audits.Implement strong security protocols and consider investing in cybersecurity insurance.
• Seek Expert Advice: Work with technology consultants and integrators to navigate the complexities of AI and automation. Leverage external expertise to ensure successful implementation and optimization.
• Foster a Culture of Data-Driven Decision-Making: Embrace data analytics to inform process improvements and optimize operations. use data to monitor performance and make informed decisions.

By combining a strategic vision with practical action, U.S. manufacturers can position themselves to reap the benefits of AI and automation and secure a competitive position within the global market.

What are the benefits of AI in manufacturing? AI can improve efficiency, optimize production, and enhance decision-making across the manufacturing process. In turn, this supports a more adaptable and competitive domestic manufacturing sector.