The AI Conversation No One Is Having With Manufacturers
Post 1 of 4 · InsightsAI Series
ERP analytics is the missing piece in the AI conversation no one is having with manufacturers. It’s about large language models, autonomous agents, and the race to grab the next wave of enterprise productivity. The numbers behind it are real. NVIDIA’s 2026 State of AI report says 86% of companies are raising their AI budgets this year.
That conversation isn’t happening with you.
If you run a plant, a distribution operation, or a construction business, the AI conversation you’re actually having sounds different. It sounds like: we know we need to do something, we just don’t know where to start. Or: we’ve looked at some tools, and none of them fit how we really work.
That instinct is right. And there’s a good reason for it.
The Noise Is Real
Most of the AI market in 2026 is built for companies with data teams, cloud infrastructure, and engineers to plug in new tools and keep them running. The case studies, the conference sessions, the vendor demos all assume a starting point that mid-market operations teams just don’t have.
You’re starting somewhere else. You’re starting from an ERP system — Infor Visual, Infor CSI, or Acumatica — that holds years of operational data: production history, inventory movements, purchase orders, labor records, delivery numbers. That data is worth a lot. It’s also locked behind reports that need IT, custom queries, or the one person who knows how to get around the system.
When companies try to move on AI, the barrier that comes up most is always the same. They can’t get to their own data, and they aren’t sure they can trust it. The people inside these businesses see it clearly. The real question is whether they can get the budget to fix it before the gap gets wider.
What Your Peers Are Telling Us
Earlier this year we surveyed hundreds of manufacturing executives from our own customer base about where they’re investing over the next 12 to 18 months. Not an industry panel. Our customers. People running the same ERPs you run.
Here’s what they said.
are investing in business intelligence and live dashboards. More than a third of your peers are moving on visibility right now.
say reporting and analytics is where they most need a partner’s help. Not implementation. Not training. Analytics.
are planning AI investments this year, and they rate their own readiness at just 4 out of 10 on average.
put themselves at 3 out of 10 or lower on AI readiness.
Put the last two together. A quarter of these executives are budgeting for AI, and almost half don’t feel ready to use it. They’re spending toward something they’re not confident they can pull off. That isn’t a technology problem. It’s a clarity problem.
And then one of them told us this:
“Needed BI tools to make a visual picture of where parts are at. Material planning window only shows one part and there is no quick visuals to see when stock may be consumed.”
Manufacturing Executive · WM Synergy 2026 Voice of the Customer Report
That isn’t a request for some sophisticated AI rollout. It’s a request to see where the parts are. The data is already in the ERP. They just can’t reach it without filing a report request, waiting, and finding the person who knows which fields to pull.
A VP of Operations put it even more bluntly:
“Better reporting fields, easier ability to make custom reports without the need of gurus.”
Vice President, Operations · WM Synergy 2026 Voice of the Customer Report
Gurus. That one word says everything. The data exists. Getting to it takes someone with specialized knowledge, and everyone else waits in line behind them. Most teams have one or two of those people, and that’s the bottleneck.
What It’s Costing You
Staying put on analytics and AI feels like the safe, conservative call. It isn’t.
Here’s the research. 88% of companies now use AI in some form, but only 6% see real financial returns. The 6% aren’t bigger or better funded. They use the same tools differently. They started earlier, built visibility into how they make decisions, and every step after that got easier because the foundation was already there.
For a mid-market manufacturer or distributor, every quarter you spend pulling reports by hand is a quarter your competitors spend acting on data. Every time your team waits two days for an answer to a production question, that’s an answer that could have come back in seconds. The distance between those two ways of operating compounds. Once it’s set, it’s hard to close.
What Practical AI Looks Like for an ERP Customer
The AI that fits a mid-market ERP isn’t a general-purpose chatbot. It connects to the data already in your ERP — minimizing the need for additional data infrastructure, rather than requiring a parallel warehouse or ETL build to get started.
It lets an operations manager ask a question in plain English and get an answer from live ERP data in seconds, instead of a static report someone built two weeks ago. It warns your finance team when margin on a job slips below the line while the job is still open, not after it closes. The focus is guided decision support — putting better information in front of the people who need it, faster, so they can act.
Your ERP platform says the same thing. The best path to AI value for ERP customers is integrating with the workflows you already have, cutting manual work, speeding up decisions, and improving visibility. Not a second data infrastructure running next to the first. What you already own.
Where WM Synergy Fits
We’ve spent more than two decades implementing and supporting Infor Visual, CSI, Acumatica, and XA for manufacturers and distributors across North America. We’ve watched from the inside what the reporting gap costs: time, missed signals, and leaders who stop trusting numbers that are always a few days behind.
InsightsAI is our answer. Anyone on your team can ask the ERP a question in plain English and get an answer back in seconds — with the charts, KPIs, and detail already attached. Nothing to build. No analyst to wait on. It’s your ERP data, finally talking back.
You buy it by the seat. It’s built for mid-market ERP. It connects to the system you already run across manufacturing, costing, inventory, procurement, scheduling, sales, and finance. It watches for the things you’d otherwise catch too late — margin slips, cost overruns, inventory that doesn’t tie — and flags them early. The same WM Synergy team you already know delivers it.
We’re not here to add to the noise. We’re here to help you find the one move that matters most for your data, your team, and your operation today.
The Right First Question
The question isn’t “Should we be doing something with AI?” The question is: what’s the one visibility gap that, if closed, would make your leadership team’s decisions faster and more confident?
That question has an answer. It’s probably sitting inside your ERP right now. The 200+ operations leaders who responded to our survey told us where they are investing and where they feel stuck. We turned that into a research report — and we use it as the foundation for every conversation we have with our customer base about where to focus next.
Frequently Asked Questions
ERP analytics refers to the ability to query, visualize, and act on the data already stored in your ERP system — without exporting it to spreadsheets or waiting on a custom report. For mid-market manufacturers and distributors, it matters because the data already exists. Production history, delivery performance, labor actuals, inventory movements — all of it is in the system. The gap isn’t the data. It’s access. ERP analytics closes that gap.
New research finds that while 88% of companies now use AI in some form, only 6% report meaningful financial returns. The difference isn’t the tools — it’s the foundation. Organizations seeing returns built data visibility into how their teams make decisions before layering AI on top. Mid-market companies that skip that step end up pointing AI at data they can’t fully trust, which produces fast answers to the wrong questions.
InsightsAI is a seat-based analytics and AI platform built for mid-market ERP environments — Infor Visual, CSI/SyteLine, Acumatica, and XA. It lets any member of your team ask the ERP a question in plain English and get an answer in seconds. It delivers cross-module dashboards across Finance, Operations, and Inventory. And it monitors for anomalies — margin shifts, cost overruns, delivery trends — flagging them proactively rather than waiting for month-end. It supports guided decision-making: better information, faster, so your team can act with confidence.
For a standard environment, connecting InsightsAI to your ERP typically takes one to two weeks. Most implementations use an indirect connection model backed by a purpose-built data layer, though connection patterns can vary depending on your environment and configuration. Full go-live with dashboards and AI narratives active is typically four to six weeks. Deployment is handled by the same WM Synergy team that implemented your ERP.
Not entirely, but it matters more than most people realize. You can start getting answers from the data you already have. But the fastest way to find out what needs cleaning is to start looking at it. A good analytics layer will surface the trust gaps as it goes — showing you not just what the data says, but where it can’t be trusted. Think of data cleanup as a focused, ongoing process guided by what the analytics reveals, not a prerequisite you have to finish before you start.
Sources: WM Synergy 2026 Voice of the Customer Report · NVIDIA State of AI Report 2026 · Infor.com, Industry AI and Machine Learning · Diginomica, “Infor in the AI Age” (April 2026) · top10erp.org, “AI in ERP: The Next Wave” (2026)
By Synergy Resources
By Dorie Skaalerud