Imagine a global enterprise managing multiple manufacturing and distribution facilities, each tasked with supplying diverse product lines to different regions. The complexity is staggering—determining which facility can produce a specific part, when it can be made, and which location is closest to the customer requires significant time and effort.
I recently spoke with a customer grappling with these very challenges. Their existing process was slow, manual, and costly. They asked: Can AI deliver these answers in real-time? The answer is a resounding yes.
Enter agentic AI. The rapid evolution of AI-driven efficiency is redefining operational paradigms, compressing what once took years into months. In a previous role, I implemented a generative AI solution that slashed a routine, high-frequency process from 20 hours to just 2 minutes—saving an astounding 285,000 hours of manual labor. But the real breakthrough wasn’t just time saved; it was time reinvested in innovation, strategy, and growth.
At Epicor, we now pose a different question to our customers: What could your workforce achieve with an extra eight hours each week?
The answer lies in agentic AI—an evolution beyond traditional automation that enables systems to reason, adapt, and act autonomously. This technology isn’t just about streamlining processes; it’s about unlocking new levels of agility and intelligence in decision-making. As AI reshapes manufacturing and supply chains, businesses that embrace agentic AI won’t just keep pace—they’ll set the standard for the future.
What Is Agentic AI?
Agentic AI is no ordinary automation tool. It’s a cutting-edge system that combines generative AI (like ChatGPT) with real-time, aggregated data from across an organization. Its mission? To enable dynamic, context-aware decision-making that keeps pace with the complexities of modern manufacturing. This technology doesn’t just make processes faster—it transforms them. From sales to supply chains and factory floors, agentic AI addresses some of the industry’s most pressing challenges.
In manufacturing, sales teams often struggle to process high volumes of quotes with limited resources. For a company with a 25 percent win rate on quotes, even a 10 percent increase in output could significantly boost revenue. Agentic AI makes this a reality. By analyzing historical data, customer preferences, and market trends, AI can generate precise, tailored quotes in seconds. It can automate follow-ups and revisions, freeing sales teams to focus on relationship-building and closing deals.
Traditional materials planning systems are like steering a ship with a delayed rudder. These rigid, rule-based frameworks often fail to adapt to real-time changes, such as a shift in customer demands or supply chain delays. The outcome? Inaccurate schedules, wasted resources, and missed deadlines.
Agentic AI integrates real-time data and continuously recalibrates schedules. For instance, if a customer changes an order at the last minute, the AI instantly updates production schedules to accommodate the change. It evaluates ripple effects on downstream processes, ensuring adjustments are seamless and disruptions minimal.
In this new world, what sets agentic AI apart is its ability to simplify complexity. Teams no longer sift through data or make educated guesses—they’re armed with actionable insights, delivered at the right time.
Supply Chain & Production Workflows
Supply chain management is often considered the backbone of manufacturing, ensuring the steady flow of materials. But it’s also one of the most intricate, time-consuming areas.
Take the process of sourcing a critical component.
Procurement teams must first identify potential suppliers, then carefully weigh factors such as cost, reliability, and delivery timelines. Once a supplier is chosen, negotiations begin, followed by the creation and approval of purchase orders. This process, with its layers of complexity, can stretch on for days or even weeks.
Agentic AI could streamline this workflow, automating and accelerating each step. It can also reach the factory floor.
In many factories, workers rely on a single expert to query ERP systems for critical data, creating bottlenecks as others wait for answers. With agentic AI, chatbots allow workers to access ERP data instantly by simply asking, “Where’s my stuff?” These bots, equipped to support multiple languages, empower diverse teams and streamline workflows, reducing downtime and increasing productivity.
Maintenance is another area ripe for transformation. Machines on the factory floor generate vast amounts of operational data, from temperature readings to vibration patterns. However, much of this data remains untapped, leading to missed opportunities for proactive maintenance and costly breakdowns.
Agentic AI can turn this data into actionable insights. It identifies patterns that signal potential equipment failures, allowing teams to address issues before they escalate. Beyond predictions, it prioritizes maintenance tasks, ensuring resources are allocated efficiently. Real-time insights enable schedules to align with production demands, minimizing disruptions and keeping the factory floor running smoothly.
Preparing for the Revolution
While the promise of agentic AI is immense, realizing its full potential requires preparation. Organizations must align strategies, refine processes, and foster a culture that embraces AI as a collaborative partner. Here’s how to get started:
- Pinpoint High-Impact Problems: Not every challenge requires an AI solution. Focus on inefficiencies that create significant bottlenecks or costs. For example, is production lagging due to scheduling issues? Are supply chain delays eroding margins? Targeting these areas ensures AI investments deliver measurable ROI.
- Build a Strong Data Foundation: Agentic AI relies on clean, integrated data. Many manufacturers operate with siloed systems—ERP, CRM, and supply chain tools that don’t communicate effectively. Consolidating and cleansing this data is essential. Think of it as laying the foundation for a skyscraper: without it, the structure won’t hold.
- Align Goals and Foster Collaboration: Implementing agentic AI isn’t just a technical upgrade; it’s a cultural shift. Leadership must set clear objectives and show how AI aligns with broader business strategies. Employees need to see AI as a tool that enhances their capabilities, not one that replaces them. Training, open communication, and demonstrations of AI’s value can help build trust and acceptance.
The road to agentic AI adoption may seem challenging, but it’s a journey manufacturing organizations can’t afford to ignore. Agentic AI isn’t just a tool—it’s a catalyst for innovation, ready to propel the manufacturing industry into its next era. If they focus on high-impact problems, prepare their data infrastructure, and align organizational goals, companies can unlock AI’s transformative potential.