The impact of artificial intelligence (AI) is being felt in nearly every industry, and front-line industrial workers are benefiting from its capabilities. In particular, front-line manufacturing floor workers are leveraging AI-based tools designed to help digitize and optimize training — based on data-driven insights — to suit individual employees’ needs. What once seemed like a futuristic concept has now become a tangible reality for the manufacturing sector.
There’s currently a scarcity of qualified candidates for many roles in today’s job market. As a result, manufacturers are struggling to find individuals with the specific skills and expertise needed to fill critical positions: According to the 2023 survey by UKG Workforce Institute, 76% of manufacturers are struggling to fill critical labor gaps. With the manufacturing industry grappling with skills gaps and the labor shortage, providing the right training, at the right time and to the right employee is critical to maintaining an adequate workforce.
As companies struggle to fill vacant roles, retaining employees can significantly alleviate retention challenges. Opportunities for growth and development correlate with increased engagement and retention rates. By using AI to deliver timely training tailored to individual employees, manufacturers can achieve multiple business objectives simultaneously.
AI in Manufacturing Training
By providing real-time support, skills development and on-the-job training, manufacturing companies can support their employees with easily accessible tools. AI can accelerate the onboarding process, reduce the time it takes for new hires to become productive, enhance worker productivity and operational efficiency. AI-powered connected front-line worker tools can address pain points by leveraging cutting-edge technology to streamline and enhance training processes, resulting in improved productivity and reduced costs for manufacturers.
On an AI-driven manufacturing floor, organizations can make learning an integral part of their front-line workers’ daily routines, effectively reducing the gap between knowledge and application. One practical way to do this is to operationalize learning, which means turning training and skills development into an ongoing process rather than a one-time event. Traditionally, workplace learning has involved occasional training sessions. While these have their place, they may not keep up with the fast-changing demands of today’s industries. AI and connected worker technology can provide a more dynamic alternative by embedding learning directly into everyday work.
At the heart of operationalizing learning is the idea of infusing training directly into the daily tasks and processes of front-line workers. Instead of segregating training as a separate entity, it can become an integral component of their work routine. AI can play a pivotal role in this transformation by providing personalized, real-time learning support that aligns with the specific needs and challenges encountered on the factory floor.
On-the-Job Learning With AI
Operationalizing learning means workers receive personalized, real-time learning support that matches their specific needs and challenges on the factory floor. Connected worker technology supplements this by offering on-the-job guidance and instructions through devices like mobile phones or tablets. This can allow workers to access training materials and acquire new skills as they work, blurring the line between learning and doing.
The advantages of operationalizing learning are clear. It can keep workers informed about best practices and improve their performance on the job. Continuous learning can empower them to adapt to changing situations and enhance their problem-solving skills, resulting in increased efficiency, fewer mistakes and higher productivity. In addition, by providing reskilling and upskilling opportunities, employers are able to engage and retain their workforce, mitigating the need to seek new employees to fill vacancies.
This approach can also foster a culture of continuous improvement within the organization. Workers are encouraged to share insights and best practices, creating a collaborative environment where collective knowledge keeps evolving. AI and connected worker technology cannot only bridge the gap between knowledge and action but also establish a cycle of perpetual learning and refinement. Upskilling and reskilling programs within manufacturing organizations go beyond their initial objectives of enhancing employee retention and boosting morale. They prove to be potent instruments for elevating product quality, amplifying productivity, improving efficiency and promoting adaptability in the midst of technological advancements.
Furthermore, AI can contribute to a supportive work environment by assisting with workload management. AI algorithms have the capability to analyze data that can offer insights into worker performance and capacity. This can aid managers with allocating tasks effectively, thus ensuring that workers are not overwhelmed by excessive workloads. Preventing burnout is another way manufacturers can engage and retain their front-line employees.
Looking Ahead With AI
Despite widespread public concerns about AI as a potential threat to jobs, many manufacturing workers have firsthand experience that this is not a one-size-fits-all reality. AI can enhance the quality of manufacturing employees’ work lives by augmenting their skills, lightening their workloads, increasing engagement and retention and bridging skills gaps and labor shortages. AI is truly reshaping the future of industrial work.
