From Factory Floor to AI Success: Why Frontline Workers Matter Most

93% of manufacturing professionals expect AI to be a pivotal tool, but how does this look in practice? In all the excitement and promise, people often overlook one critical factor: the relationship between AI and the humans doing the work.

Recently, I got to discuss this topic (and more) with Chris Luecke on the Manufacturing Happy Hour podcast. Since then, I’ve been thinking more deeply about how AI and humans can work together to transform manufacturing.

In this post, I'll explain what I mean by that and share steps to help you focus your AI tools on what matters most: supporting the frontline workers.

AI’s potential in manufacturing

Companies around the world are already beginning to see the benefits of AI. For example, General Motors implemented AI-powered production planning to analyze past production data. As a result, they reduced material waste by 30%. What’s so exciting is that we’re just at the very beginning of this paradigm shift.

So, how else could AI impact manufacturing and frontline workers?

Increased efficiency

One practical example is voice memo transcription. Instead of searching for a pen and paper or typing on a tablet, technicians in the field can record critical information by talking into their CMMS app. Their voice memo can then be automatically transcribed with AI so anyone can read it later.

Another example is AI-powered procedure generation. This tool helps you create Standard Operating Procedures (SOPs) faster—all you have to do is supply prompts with some basic information. You’ll spend much less time creating SOPs from scratch and free up time to focus on more critical tasks.

Predictive maintenance

With proper predictive maintenance, users can sharpen their preventive maintenance focus. MaintainX, for example, supports equipment condition monitoring, enabling you to shift from routine tasks to targeted maintenance work on the assets that need them most. However, predictive maintenance can be a challenging strategy to execute—we’ve found that only about 30% of facilities implement it. How does AI help here? Predictive maintenance relies on equipment monitoring and data analysis. By analyzing data from sensors and other sources, AI tools can predict when equipment is likely to fail.

Enhanced quality control

Quality control processes can be time-consuming for human inspectors. They can also be inconsistent. With the right AI tools, you can more easily identify defects and data anomalies, saving time and increasing output quality. For example, MaintainX’s anomaly detection feature helps you determine if data is likely to be inaccurate. If a user enters a value in a procedure or meter reading, the system checks it against historical and trend-based data. By doing this, the system can flag entries that look out of place and require closer attention.

How to include frontline workers for a successful implementation

Here’s the thing about those benefits: Each one requires frontline worker involvement. To save time with AI transcription, workers need to actually use the feature. And AI models can't predict failures if your workers aren’t collecting data for the systems to analyze.

Here’s how to make sure your frontline workers are fully on board with any AI initiatives.

Change management

Involving frontline workers throughout the planning and implementation stages is critical—a Gartner study found that employees who worried AI will replace their jobs are 27% less likely to stay with their employer.

Start by conducting surveys to understand specific pain points in their workflows. This helps ensure that you obtain AI solutions tailored to their actual needs. For example, ask where automation could help reduce repetitive tasks or eliminate errors. Work with team leaders and supervisors to foster a sense of inclusion, addressing concerns to prevent resistance to new tech. If workers feel these changes are implemented with consideration, they’re more likely to adopt them wholeheartedly.

Training and support

The transition to AI tools can feel overwhelming for workers who may be used to traditional methods. Comprehensive training is essential, not just at rollout, but as a continuous resource. Break down the training into digestible sessions with hands-on practice and real-world applications so workers can see exactly how AI helps with their specific tasks. Ensure workers can easily access help if they face difficulties. This doesn’t just improve adoption; it builds confidence in their roles and helps them see the potential for personal growth with AI.

Continuous improvement

Actively seek and value the insights and experiences of frontline workers, as they have a unique understanding of day-to-day operations. Create a feedback loop that encourages them to share insights on what’s working and where you can enhance or adjust the AI tools. This could be as simple as a suggestion box, regular team debriefs, or anonymous feedback forms. By showing that their input drives continuous improvement, you foster a culture where workers feel valued and invested in the digital transformation journey.

It starts on the frontlines

Success with AI in manufacturing isn't just about implementing the latest technology—it's about empowering the people who use it every day. When you prioritize frontline workers' needs, provide comprehensive training, and create feedback loops for continuous improvement, you transform AI from a mere tool into a true force multiplier. When frontline workers feel empowered and engaged, AI becomes a tool for not just efficiency, but for greater job satisfaction and overall success. It’s time to take these steps and make AI work where it matters most—right on the factory floor.

Over here at MaintainX, we’ve invested in a suite of AI features to drive efficiency and optimize your processes. We’ve done this because we know that AI is a game-changer, and its importance will only continue to grow.