AI has the potential to revolutionize manufacturing.
It can increase efficiency, reduce human error, and drive better decision-making. But despite this promise, most manufacturers are struggling to move beyond the exploration phase.
While AI adoption is growing in other industries, only 8.2% of manufacturers are actively scaling it today (Amper’s 2025 AI in Manufacturing Survey).
The enthusiasm is there—nearly every leader recognizes AI’s importance—but the follow-through is missing.
So, what’s stopping the industry from taking the leap? And more importantly, how can manufacturers push past these barriers?
Manufacturers are stuck: They see AI’s potential, but they don’t trust it enough to invest in it meaningfully.
According to the 2025 AI in Manufacturing Survey, two-thirds of manufacturers believe AI can reduce human error and progress the manufacturing industry. Yet, only a quarter actually trust AI to make critical decisions.
This skepticism is understandable. Automation has always sparked concerns about replacing human expertise. But it’s also holding manufacturers back from optimizing their operations. The reality is: AI doesn’t have to replace human decision making. It actually enhances it by surfacing better data and insights.
Start small. Test AI in non-critical areas where the risk is low but the impact is measurable.
Share success stories. AI adoption increases when manufacturers see real-world proof from their peers.
Keep people in the loop. AI works best as an assistant, not a replacement. Implement systems that combine AI insights with human oversight.
AI requires data infrastructure, integration with existing systems, and workforce buy-in. Even if manufacturers wanted to adopt AI tomorrow, most aren’t prepared for the shift.
Over three quarters of respondents rated their AI readiness as a 3 or lower on a 5-point scale. Almost half dedicate less than 5% of their annual budget to AI, and the other half didn’t disclose an AI budget at all—suggesting that it’s not even a priority line item in their business.
Without investment and a clear strategy, AI adoption will stall before it even begins.
Build an AI roadmap. Identify specific areas where AI can drive results and create a step-by-step plan for integration.
Invest in foundational tech. AI thrives on data. Companies need systems that capture, store, and structure data effectively.
Allocate a real budget. AI won’t happen without dedicated funding. Companies that treat it as an afterthought will be left behind.
In addition to a lack of budget and infrastructure preparation, most companies aren’t preparing their workforce for AI either. Only 16.4% of manufacturers expect to adopt AI copilots in the next two years—presumably because only 6.1% reported their employees would be comfortable using them.
Yet even though the vast majority of respondents feel their employees are unprepared, over half (55.1%) estimate that less than 10% of their employees will need AI training in the next three years.
This underestimation is a huge problem. AI won’t just change technology; it will change how people work. Without proper training and upskilling, companies will struggle to integrate AI effectively—widening the gap between those who embrace the technology and those who fall behind.
Prioritize AI training. Make education part of the rollout plan so employees feel empowered, not threatened.
Demonstrate AI’s benefits. Show employees how AI can make their jobs easier instead of replacing them.
Adopt AI tools that are intuitive. The easier AI is to use, the faster employees will embrace it.
The barriers to AI adoption are real—but not insurmountable. Manufacturers who start with small, measurable AI initiatives, invest in the right infrastructure, and bring employees along for the journey will be the ones leading the industry forward.
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