Way out of the talent shortage: AI as a catalyst for a workforce surge

What you’ll learn:

Experienced workers are nearing retirement, and the younger workforce is tech-savvy but lacks hands-on manufacturing experience.
Assistive copilots, decisioning platforms, and enterprise solutions are already being used to capture expert decision-making processes, integrating past patterns into AI models.
Adoption still faces challenges. A lack of in-house AI expertise remains one of the top roadblocks, with 45% of manufacturers citing it as a major concern.

Manufacturers today face a labor crisis: By 2030, an estimated 2.1 million jobs will remain unfilled, leaving factories struggling to meet production demands. The challenge isn’t just about hiring new workers—it’s also about ensuring that critical industry knowledge isn’t lost when seasoned professionals retire.

As workforce shortages persist, manufacturers need intelligent tools to enhance agility, efficiency, and precision. AI is becoming essential for balancing labor gaps, optimizing production schedules, managing volatile supply chains, and maintaining quality standards.

Manufacturers face a major workforce shift. On one side, experienced workers are nearing retirement; on the other, a younger workforce is tech-savvy but lacks hands-on manufacturing experience. AI can bridge this gap by preserving institutional knowledge and embedding it into AI tools that can help guide new employees.

Assistive copilots, decisioning platforms, and enterprise solutions are already being used to capture expert decision-making processes, integrating past patterns into AI models. This means that as new hires step into roles, they have AI-driven insights at their fingertips—helping them navigate complex decisions in production, inventory management, and supply chain operations.

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Beyond knowledge transfer, AI is also reshaping factory floors. Voice-activated controls, touchless ERP interfaces, and predictive AI tools enable workers to work more efficiently, minimizing manual input and improving accuracy. Instead of searching through multiple systems, workers can rely on AI to surface the right information in real time.

With this shift, manufacturers aren’t just adopting new technology—they’re creating a continuity strategy that preserves institutional expertise and streamlines the workforce transition.

AI adoption is accelerating

Manufacturers are recognizing AI’s potential. The 2025 AI in Manufacturing Survey, conducted for Rootstock by Researchscape, found that 57% of manufacturers have implemented some form of AI-powered automation and 42% have forged ahead with predictive AI capabilities.

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AI is most used in production (31%) and inventory management (28%), but adoption is expanding in supply chain management, predictive maintenance, customer service, and quality control.

However, enthusiasm for AI varies across generations. Gen Z workers are the most eager adopters, with 56% expressing excitement about using AI in their jobs. Meanwhile, Gen X and baby boomers lag at 38%, and millennials fall somewhere in between at 48%.

This divide highlights the need to ensure AI tools are accessible and intuitive for all workers, not just those who are digital natives.

Bridging the skills gap with AI training

AI isn’t just assisting workers—it’s training them as well. As more skilled laborers are in need, more manufacturers (25%) are investing in AI solutions that can help train workers. Many companies are leveraging AI capabilities embedded in enterprise solutions, such as finance, ERP and HCM solutions, to provide workers with AI-driven guidance in their day-to-day tasks.

However, adoption still faces challenges. A lack of in-house AI expertise remains one of the top roadblocks, with 45% of manufacturers citing it as a major concern. As a result, 60% of manufacturers are prioritizing training and upskilling around AI, acknowledging that adoption will only be as effective as their workforce’s knowledge of how to use it.

Additional barriers to adoption

While AI adoption is expanding, skepticism still exists among workers themselves. Although many professionals see AI as a tool that enhances their work, some employees (17%) fear AI will take their jobs. This fear underscores the need for clear and transparent implementation strategies, ensuring workers understand how AI is meant to assist them, not replace them.

Another challenge is data. Manufacturers remain unsure whether the data sets that underpin their AI initiatives are accurate and up to date, with 61% expressing uncertainty around quality. If manufacturers hope to leverage AI effectively, they must audit and cleanse data to build confidence in AI-driven decisions.

AI agents and the future of manufacturing

Looking ahead, AI is set to play an even greater role in manufacturing operations. AI agents are fully autonomous, so they’re capable of making decisions and taking action without human intervention. These agents are emerging as a transformative force in the industry.

Unlike AI copilots, which assist workers, agents operate independently, managing complex workflows and executing tasks based on real-time data. These agents are being deployed in the following ways:

Automating inventory management: AI agents can monitor and predict demand fluctuations, reorder materials, and optimize warehouse space without human oversight.
Managing procurement and supplier interactions: Agents can negotiate pricing, evaluate supplier risks, and ensure just-in-time inventory replenishment.
Handling production scheduling: AI-driven scheduling agents can dynamically adjust manufacturing timelines to accommodate shifts in supply chain conditions or equipment availability.

For manufacturers facing workforce shortages, agents free up human workers for high-value, strategic roles while automating repetitive tasks. Skilled employees can focus on problem-solving, innovation, and process optimization—areas where human expertise is irreplaceable.

While AI agents are still in early adoption stages, manufacturers are preparing for their use by investing in data infrastructure and ensuring their solutions can support these autonomous tools.

The Great Enabler

Manufacturing workers are beginning to experience AI’s value. In the 2025 Researchscape survey, 41% of manufacturing professionals reported that AI made them more productive, while 40% said it allowed them to deliver more value in their roles.

For AI to truly benefit the industry, manufacturers must take proactive steps. They must modernize their enterprise solutions, embedding AI so they can impact operations at the level of everyday tasks. This strategy will incorporate AI learning at all levels of the organization. Clear internal messaging is essential in encouraging workforce adoption and alleviating concerns about job displacement.

The future of manufacturing depends on bridging the talent gap effectively. AI provides the means to do it—offering not just automation, but a pathway to smarter, more connected, and more resilient manufacturing operations.