Agentic AI Isn’t a Product – It’s an Integrated Business Strategy

Agentic AI Isn’t a Product – It’s an Integrated Business Strategy

Everyone’s talking about AI. From pilot projects and co-pilots to promising dashboards, artificial intelligence is cropping up left and right in manufacturing. What’s rare, however, are wide-scale implementations that deliver measurable results on the factory floor. In fact, IDC estimates that 88% of proof of concept (POC) projects fail to make it out of the pilot phase.

Why? The answer is simple: most organizations treat AI like a product. It’s treated as something you can buy, install and expect to work on its own.

The real opportunity isn’t in applying AI on the surface. It’s in embedding intelligence into an entire ecosystem – and this is where agentic AI shines. It isn’t a chatbot or a smarter search bar; it’s a system that observes, decides and acts autonomously and responsibly. It has to live in the flow of your operations, trusted by your teams and integrated into how your factory actually runs.

Agentic AI isn’t a product. It’s an integrated business strategy.

Defining Agentic AI

Any leader considering agentic AI should have a clear understanding of what it is (and what it’s not!), which can be difficult considering many organizations are using the term in different ways. To understand what makes the technology so transformative, I think it’s helpful to contract it with the tools many manufacturers are already familiar with.

Traditional AI – think large language models like ChatGPT – typically falls into one of three categories:

1. It analyzes data to uncover patterns.
2. It assists with tasks like scheduling or forecasting.
3. It recommends actions based on probabilities.

Those are valuable capabilities, but they still put the burden of decision-making and execution on people. Agentic AI goes further.

It observes what’s happening, identifies when something needs attention, decides on the best course of action based on context and constraints and takes action – all while keeping humans in the loop through escalation protocols or built-in boundaries.

Agentic AI doesn’t just help someone do a task. It owns that task, end-to-end, like a trusted digital teammate. If a traditional AI solution is like a dashboard, agentic AI is more like a co-worker who has deep operational knowledge, learns fast, doesn’t need a break and knows exactly when to ask for help.

This is also where misconceptions tend to creep in. Agentic AI isn’t a chatbot with a nicer interface that happens to use large language models, nor is it a one-size-fits-all product that slots in after implementation. It’s a purpose-built, action-oriented intelligence that lives inside your operations and evolves with them.

Why the Real Impact of Agentic AI Is Operational, Not Technical

In manufacturing, like any industry, it’s easy to get distracted by the bells and whistles of new technology. We’re drawn in by sleek dashboards and clever alerts that promise to fix all of our problems. Pilot projects get approved but, when the dust settles, the core work of running a factory often stays the same.

That’s because most AI tools sit on the sidelines. They observe, analyze, make suggestions and wait. Agentic AI is different because it operates within the work itself. The technology doesn’t simply point out a project on a dashboard; it identifies the issue, initiates the response and keeps the team moving. It’s also embedded in the natural rhythm of your operations, working as an active participant during shift changes, quality checks, line changes, etc.

When we talk about AI agents, the goal isn’t just to summarize information faster. It’s to shift from assistance to action. I like to frame this both aspirationally and practically: think of a personal agent that doesn’t just track your expenses, but builds your monthly budget, flags when your spending habits are off, recommends how to reallocate funds and even sets reminders to adjust based on life events. That’s agentic AI: it understands context, makes decisions and takes action.

Translating that to a factory environment, AI agents could optimize operations before a shift hand-off, proactively address compliance risks or even identify skill gaps on the team and recommend training. The key is that they’re not just assistants. They’re collaborators built to drive outcomes.

Agentic AI isn’t a futuristic technology, either. It’s here and gaining momentum fast. According to Capgemini, the number of organizations using AI agents has doubled in the past year, with production-scale deployments expected to reach 48% by 2025. The technology’s adoption trajectory is a sharp departure from traditional AI technologies.

That’s because when AI is embedded into your business, it doesn’t just help you work faster. It changes how the work gets done.

The Three Tenets of a True Agentic AI Strategy

If there’s one thing I’ve learned watching AI evolve in manufacturing, it’s that implementation alone doesn’t drive impact – strategy does. According to Bain & Co., environments that integrate AI with digital and lean tools can improve productivity by 30% to 50%. Despite that potential, only 23% of manufacturers have deployed AI in live plant-floor operations – and just 7% have scaled it across multiple sites, according to the Manufacturing Leadership Council. That’s not a technology gap. It’s a strategy gap.

To build a sustainable agentic AI strategy, I believe there are three tenets that must be in place:

1. Design for action, not observation.

AI that tells you what’s wrong isn’t enough. Insights only matter if they lead to resolution. Agentic systems should be designed to act. Whether it’s kicking off a corrective action workflow or rebalancing labor in response to a bottleneck, the goal is always resolution in real time, not reflection after the fact.

2. Put trust structures in place.

Autonomy doesn’t mean lack of oversight. Agentic AI needs boundaries, escalation paths and human validation points built in from day one. The goal isn’t to replace human decision-making, but to enhance it, empowering people to focus on the edge cases, judgment calls and high-impact work where they’re irreplaceable.

3. Embed AI into the pulse of operations.

Agentic AI has to live in the daily rhythm of the factory floor from shift handoffs and quality checks to maintenance windows and inventory cycles. Systems that sit on the side and require teams to go to them don’t get used. When intelligence is embedded into the tools and workflows your team already trusts, adoption happens naturally.

What Leaders Should Be Asking

Too often, conversations about AI start with the wrong question: What tool should we buy?

Agentic AI isn’t about selecting the right software. It’s about rethinking how your factory makes decisions and takes action. That shift requires a different set of questions:

• Where are decisions bottlenecked today?
• Where is action delayed because people are waiting for directions?
• Where are supervisors pulled into tasks that could be handled autonomously?
• Where could an intelligent agent serve as a teammate, not just a tool?

These questions aren’t just theoretical. They’re the foundation of an operational strategy that integrates AI where it matters most. If you start there, you’re already ahead.

The Future Isn’t AI Everywhere – It’s AI Embedded Where It Counts

Agentic AI isn’t a product on a roadmap or a line item in your tech budget. It’s a leadership decision to change how your organization works.

When done right, agentic AI doesn’t feel like a new system to learn or a dashboard to check. It disappears into the workflow. It flags the issue before it becomes a problem. It kicks off the resolution before you’ve even had your coffee. You don’t use agentic AI. You work with it.

That’s the future worth building toward. Not AI everywhere, but AI embedded where it counts.

About the author

This article was written by Blake Strickland, Vice President of Product Management at QAD | Redzone. As VP of Product Management at QAD | Redzone, Blake drives the strategy and execution of tools that boost frontline productivity and collaboration. Since joining in 2019, she’s led teams across Coaching, Solutions, and Product. Before that, she spent over a decade at General Mills in operations and CI roles, delivering results in safety, performance, and culture.