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This article was originally written for and published by Forbes.
In my role as the CEO of a software company that works with the discrete manufacturing industry, I regularly consult with product companies and contract manufacturers, advising them on how to navigate today's market dynamics.
Many of these companies are operating under constant pressure from tariffs, supply chain disruptions, labor shortages and other external forces, all while competing in markets where speed and efficiency are critical.
In this environment, even a minor product delay could be detrimental to business. In my conversations with stakeholders, I've found that disruptions to existing processes tend to be ongoing and come in various forms, including increased material costs and operational inefficiencies, which lead to downtime and quickly cut into profits.
The first-mover advantage is real and can pay off with brand loyalty, helping to ice out future competitors.
Many stakeholders I speak with place a high value on innovation and quality, and have determined that if they want productivity gains, they need technology solutions that shift their companies from reactive responses to proactive automation, incorporating real-time decision-making. What is that technology? You guessed it: AI.
Many manufacturing executives have heard about the promises of AI transforming their businesses. But from my observations, many are questioning its real-world value. That questioning, I believe, tends to stem from manufacturing executives seeing the consumer benefits of generative AI, which arguably isn't the right type of AI for their business needs.
Instead, manufacturing executives should focus on agentic AI, which moves beyond prompt-based inquiries to operate within the parameters defined by existing software rules and configurations, in turn making tasks more efficient. It's more than simple automation; it’s autonomous problem-solving across complex workflows that enables manufacturers to anticipate and act before problems advance to damaging business delays.
A lot of executives I speak with are excited about agentic AI's potential to help them solve their business problems. But at the same time, many are setting a high bar for results (such as at least a 25% reduction in tasks). That high result can be achieved in two ways: by increasing your workforce's productivity through redeploying employees to higher-value tasks, or via reducing your workforce.
Delivering Quality, Supply Chain And Training Productivity
In our current climate, where product companies are regularly navigating unpredictability, such as tariffs and supply chain disruptions, AI agents can provide the ammunition needed to offset potential negative impacts.
For example, AI agents can conduct predictive inventory analysis, enabling companies to schedule component or part deliveries to arrive exactly when needed. In turn, this reduces costs and helps companies avoid out-of-stock scenarios. With automated triggers alerting product managers of cost overruns or predicted low supplies, workflows can stay on track. This proactive safety net addresses supply chain volatility. Teams can make quick adjustments to their cost structures as needed.
AI agents can also speed up data analysis. For instance, AI agents could analyze a large data set of quality complaints in seconds that would require hours of manual work. When a sudden spike in new complaints occurs, instead of waiting for a manager to identify the trend, AI agents can quickly review and determine the causes of those complaints and proactively recommend remedies before the complaints become numerous.
AI agents can also enable preemptive maintenance by analyzing historical product performance data to detect early signs of product failure. That way, companies can service their equipment before it breaks down.
Eliminating language barriers is another area where AI agents can have an impact. They could, for instance, quickly decipher hundreds of pages of instruction manuals across several languages and create region-appropriate training quizzes.
Agentic AI can rapidly complete tasks that would take people hours or days to tackle. But strategically leveraging agentic AI requires careful planning and execution—which should begin and end with a comprehensive and cohesive data foundation. By combining agentic automation with deep data analysis, manufacturing companies can drive real business differentiation.
Fully Integrated Data: The Foundation For Speed And Accuracy
The data layer that's needed should be comprehensive and collaborative—robust yet connected.
As business processes continue to become more complex with increased components, market and customer requirements and/or assimilating software, the amount of data generated within product companies substantially increases. This makes it essential for stakeholders to feed the right data into AI agents.
I recommend having all of your product lifecycle management (PLM), quality management (QMS), computer-aided design (CAD) files, enterprise resource planning (ERP) records and supplier inputs on hand. When AI agents have all that data on hand, they can parse through it and extract what's relevant. This type of enterprise-wide, end-to-end product connectivity is the nucleus for effective agents. With a highly defined data structure on top of a secure, rules-driven engine, agents can make real-time decisions within their existing environment. The more complete and organized your data, the more powerful and precise your AI agent output becomes, and the higher your productivity and efficiency gains across your business.
A Competitive Advantage That Scales
Faster process execution, reduced delays, fewer errors, quicker onboarding and more agile responses to changing market conditions can all add up to faster time to market and healthier margins for manufacturers. Agentic AI can enable manufacturers to maintain efficient operations, regardless of location or workforce composition.
In today’s market, any hesitation comes at a high cost. Agentic AI isn’t just another productivity tool; it’s a catalyst for manufacturers who value speed to market and can’t afford to wait for problems to surface before acting.
