AdobeStock
After a turbulent start to the decade, the United States manufacturing industry has collectively refocused its priorities on regrowth and recovery. Manufacturers are investing in more technology than ever before, scaling smart manufacturing and digital solutions in order to streamline and improve operations in the wake of industry-wide disruptions. According to one 2025 survey, the majority (80 percent) of manufacturing executives plan to dedicate at least 20 percent of their improvement budgets to support smart manufacturing tools and technologies.
There is a clear desire to empower domestic manufacturing facilities with improved capacity and technologically enhanced employee productivity. The reality, however, is not as promising: While the employment market continues to fluctuate, U.S. manufacturing lost an estimated 103,000 jobs between January 2025 and January 2026, in large part due to factors like tariffs, soft demand, productivity constraints and economic uncertainty.
But while these factors can help us diagnose the challenge at hand, they don’t map out a cohesive, achievable path forward. Yes, figuring out how to revitalize and support the domestic manufacturing workforce is critical. But what kind of jobs are we creating?
The future of American manufacturing will not hinge on restoring the jobs of the past, but on building a workforce capable of doing more with the increasingly advanced tools they’re given. Manufacturers that pair investment in digital solutions with strengthening their workforce’s requisite skills will be the ones that ultimately succeed.
According to Deloitte, 92 percent of manufacturers believe that smart manufacturing will be the main driver of their competitiveness over the next three years, leading to an increase in strategic technology investments. This has manifested in the widespread integration of automation, artificial intelligence and smart factory technology into existing infrastructure, in an overarching effort to streamline processes and improve performance. A byproduct of this investment in AI and automation is that it will reduce reliance on purely manual manufacturing roles, while simultaneously increasing the demand for more connected, insight-driven work.
As traditional production roles decline, the demand for data-literate workers and AI-augmented maintenance, quality, and process workers grows. This is by no means random, as the potential benefits of manufacturing technologies are numerous and well-documented: Smart manufacturing adoption has led to 10-20 percent improvements in production output, 7-20 percent improvements in employee productivity, and 10-15 percent improvements in unlocked capacity for early adopters. But benefits like productivity gains, cost reductions and improved quality can only be realized if the workforce is able to keep pace with rapid innovation.
The effectiveness of digital solutions is not determined by the number of workers a facility has, but instead by the solution-specific skills each worker possesses. Maximizing the full value of growing investments in manufacturing technology will depend heavily on empowering workers and closing the growing digital skills gap.
To close this gap, manufacturers will first need to overcome structural workforce challenges. An aging workforce, earlier retirements and a shortage of qualified young talent are leading to persistent unfilled roles, further aggravating the impact of ongoing job losses. While it might seem prudent to automate these roles with the aid of new technologies, this is not yet a truly viable option.
Floor-level AI integrations are becoming more sophisticated and capable, but they are not yet fully suited to handle full-scale automation of all production tasks. Today’s AI solutions work best when a human is in the loop to monitor operations and deliver the strongest, most informed results. Instead, AI can augment the work of existing staff, helping reduce cognitive load and accelerate informed decision-making—provided workers have the skills to use them effectively.
To best support this form of AI integration, manufacturers need to evolve frontline roles rather than replace or eliminate them entirely. Workers will not only need to be trained in the technical operation of these tools and how their digital solutions work, but also on when they should or should not apply them throughout manufacturing processes. The core capabilities that upskilled workers will need to adopt include:
Workers will also need to be trained in solution-specific skills and processes to ensure they’re making the most effective use of the tools the business is investing in.
Building these skills in an existing workforce requires the manufacturer to take an intentional, strategic approach to upskilling. It is by no means a one-and-done process, though: Initial pre-deployment training can help teams get up to speed as they become more familiar with the solutions at their disposal, but regular post-deployment sessions are required to ensure that workers are caught up on the latest capabilities of all digital manufacturing solutions.
Teams should also attach continuous evaluation and upskilling initiatives to their key production performance indicators, and measure metrics like “time-to-proficiency” and “total adoption” as specific, intentional business outcomes. By refocusing on training and upskilling as core, measurable business goals, manufacturers can ensure prioritization, consistency and alignment across teams.
Strategic partnerships can also be a force multiplier in this area. Bridging the technological skills gap is an industry-wide challenge that will not be solved by any single manufacturer or university course. Working together and sharing knowledge will be the most effective path forward. By collaborating with partners, industry peers, universities, technical colleges and engineering programs, manufacturers can increase digital literacy across the industry, not just at one company.
As the manufacturing workforce becomes more data- and analytics-driven, the demand for new digital skillsets will only increase. Manufacturers need to start preparing their workforce for these changes now, rather than shooting from the hip and adopting new tools without the necessary training to match.
A core component of bringing smart technology to life on the factory floor will be making these solutions available and accessible through a connected, consistent industrial data infrastructure layer. Any successful deployment of these connected solutions will depend on how manufacturers equip their teams with the skills they need to operate alongside AI and other digital solutions. Those who invest early in data, analytics and AI-ready talent—not just data, analytics and AI solutions themselves—will be the most likely to increase productivity, resilience and sustainable growth.
Geopolitical conflict, trade disruption and policy whiplash have defined the first half of 2026. CEOs…
Tal Binder's bad outcome on a major liquidity event sent him deep into the tax…
The biggest opportunity is emerging before the search begins.
Know yourself, build teams for chemistry rather than individual star power, and use stories to…
M&A value creation is rarely linear, even with strong strategy and diligence. Success depends on…
After a July pullback that saw manufacturing CEOs’ year-ahead outlook slip to its lowest level…