The truth is, AI isn’t here to take your job — it’s here to unlock your potential. By tackling inefficiencies and streamlining workflows, it’s helping manufacturers work smarter, faster, and more competitively. The real opportunity lies in treating AI not as a buzzword, but as a powerful business tool.

Gone are the days when business decisions were made based on gut instinct and spreadsheets alone. Imagine your forecasts adjusting in real time, your financial models flagging risks before you see them, your processes identifying bottlenecks before they cost you money. That’s not science fiction. That’s today’s AI — if you’re open to using it.

Right now, in manufacturing, no one’s pretending to have all the answers on how to perfectly integrate AI into your production floor. But that’s not where you should be starting anyway. The most immediate impact isn’t out in the plant — it’s in your office.

“Anything where you’re gathering a ton of information — forecasting, modeling, financial analysis — AI can help you streamline that now,” says Derek Wagoner, manufacturing advisor at Pinion.

Why Manufacturers Can’t Afford to Wait

Still think AI is just hype? Consider this:

In Q4 2024, 241 companies in the S&P 500 mentioned AI in their earnings calls. And the global AI market grew from $29.5 billion in 2019 to over $638 billion in 2024.

Your competitors aren’t just talking about it — they’re investing in it. And the ones experimenting now will be the ones leading next year.

“Some leaders are already experimenting with AI — figuring it out as they go. Others are waiting for it to be ‘perfect.’ Guess who’s going to be further ahead,” shares Justin Mentele, manufacturing advisor at Pinion.

Where AI Can Start Saving You Time

The most immediate and impactful opportunities to implement AI are in your back office — streamlining administrative, finance, and planning processes.

Business Function Fast-Win AI Use Cases Payoff
Financial Planning Financial modeling, forecasting, analyzing large data sets Better insight into costs, margins, and inventory needs
Supply Chain & Ops Feedstock quality prediction, process documentation, supply signals Smarter decisions around purchasing and lead times
Executive & Admin Meeting summaries, drafting internal reports, summarizing legislation Time savings and clarity for leadership communications
Legal & Compliance Reviewing contracts for risk, comparing policies/documents Fewer surprises and stronger compliance visibility

For example, manufacturers in the biofuels space are already testing AI for predictive maintenance, feedstock quality prediction, and even digital twin simulations. These aren’t high-theory use cases — they’re happening now, and they’re driving measurable gains.

“Stop waiting for AI to land in your plant. Use it in the back office first — meeting notes, inventory signals, then scale outward,” advises Wagoner.

What’s Really Holding You Back?

Right now, most of the hesitation we see comes down to unfamiliarity and uncertainty. For many manufacturers, it’s not just about whether a tool like AI works, it’s about navigating the unfamiliar. New technology brings unknowns, and that alone can be enough to stall progress.

Whether it’s concerns about implementation, disruption, or just not knowing where to start, that discomfort is real — and understandable. But staying stuck in what’s familiar could be more costly than exploring what’s possible.

Here are two common concerns we hear — and how to move past them.

Concern 1: “AI is going to replace me.”

AI isn’t replacing you — it’s augmenting you. Leaders who learn to use it will outperform those who ignore it.

“AI doesn’t threaten your value,” says Mentele. “It enhances it, if you’re willing to use it.”

Concern 2: “What about privacy?”

Be smart about sensitive data, but don’t let fear of imperfection become a reason for inaction.

  • Use secure tools or enterprise licenses for sensitive work.
  • Be intentional about what you upload and to where.
  • Most importantly: start learning what AI can actually do.

The tools are improving quickly. Learn what’s possible while managing the risk.

How to Start Small — With Less Risk

You don’t need a massive tech overhaul or a dedicated AI department to get started. What you do need is the willingness to experiment.

Here’s how other leaders are getting started:

  • Tackle simple, high-friction tasks, like documenting processes, taking meeting notes, or summarizing emails.
  • Treat it like a conversation starter: brainstorm ideas, draft content, then revise and refine.
  • Practice clear prompting — how you ask matters.
  • Stay critical — always question the results and dig deeper into the outputs.
  • Consider enterprise-grade tools — especially if privacy or compliance is a concern.

“You don’t have to overhaul your business. Just start exploring where AI can save you time or surface smarter insights — no heavy lifting required,” states Mentele.

The goal isn’t to master AI overnight. It’s to get familiar enough that you can spot opportunities when they show up — and recognize what’s worth pursuing.

Embrace It — or Step Aside

This isn’t about having all the answers. It’s about having a mindset to adapt. AI won’t wait for perfect conditions, and neither will your competition.

So, open your mind. Run the experiment— and let AI go to work.

AI may handle the small stuff, but big-picture success still depends on having the right strategy. Reach out to a Pinion manufacturing advisor for guidance on implementing AI into financial planning and business strategy.