Today’s manufacturers have been grappling with a significant problem: how to do more with less.
Growing part complexity, ongoing talent shortages, and persistent supply chain bottlenecks have left many searching for ways to remain competitive, even at a time when the demand for manufactured goods remains high. In 2023, construction spending in manufacturing hit $201 billion—a 70% increase from the year before. This growth was primarily driven by three major legislative acts: the Infrastructure Investment and Jobs Act, the CHIPS Act, and the Inflation Reduction Act. Those who find ways to improve their efficiency are the ones best positioned to capture the greatest share of this growth.
For many, the solutions to these challenges lie in AI and automation. From automated manufacturing processes to downtime reduction and better inventory management, manufacturers increasingly rely on these advanced technologies to succeed.
In many ways, it’s the biggest shift to hit the manufacturing industry since the days of the assembly line.
Here is what we’re seeing in the industry now and what’s on the horizon for manufacturers that want to stay competitive in the future.
While AI holds promise for almost all areas of production, three use cases have emerged as early standouts.
These “quick win” use cases have been easy entry points for manufacturers, as they offer clear ROI and readily available data. But as companies prove success in these areas, they're beginning to explore broader applications.
If the benefits are so clear, why isn't every manufacturer running AI at scale? The reality is that several stubborn challenges keep many stuck in pilot mode:
Lastly, organizational resistance can be a serious roadblock. Employees may distrust AI or fear it will replace them. Without clear communication and visible wins, adoption will remain slow. Manufacturers seeing the most success have realized that AI works best when humans remain firmly in control (what we call human in the loop). So, while AI might monitor equipment and flag issues, employees make the final calls. When this strategy is prioritized, and employees see AI as a tool that helps them do their jobs better, rather than replace them, the resistance often melts away.
One of the most significant shifts we’re seeing in 2025 is how manufacturers approach AI use. Now that many have proven AI’s value through pilot projects, they’re thinking bigger and moving toward connected, enterprise-level deployments. With about a quarter of manufacturers still testing the waters with pilot programs, nearly 30% have already scaled AI and machine learning across their facilities.
As this change unfolds, we're seeing companies finally breaking down data silos and build the infrastructure needed to make AI work at scale. They're linking equipment monitoring with maintenance systems, embedding quality checks directly into production workflows, and connecting previously isolated systems in ways that were never before possible. Instead of isolated AI experiments that never expand, these manufacturers are building intelligent systems that talk to each other and deliver results across the entire operation.
When implemented correctly, these connected AI systems are delivering on their promise. Manufacturers report a 10-20% increase in both production output and employee productivity, which helps smaller teams manage more.
The manufacturing industry is changing fast, and the question is no longer whether to adopt AI—it’s how quickly you can move from pilot projects to full production.
If you're ready to move beyond individual projects and see what AI can do for your operations, the path has never been clearer. It just takes the right approach and the right partner to help you navigate the challenges.
Want to explore what this could look like for your manufacturing operations? Let’s talk about building an AI strategy that delivers results.
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Josh Kohn, SVP Strategy & Operations
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