Right now, most manufacturers are only scratching the surface of what AI can do. Plenty of shop owners are feeding reports into AI engines to create summaries, but its power is far greater.
Instead of just producing a summary, AI can identify problems, suggest next steps and in many cases even carry those actions out without the need for human intervention. The shift from software being a data storage system to being an operator is happening quickly, whether companies are ready for it or not.
The catch is that none of this works without accurate, digitized data.
Drawing a Parallel Between AI and CNC Adoption
Those who wait won’t just miss out on growth, they will soon start to lose loyal customers to competitors who are able to deliver faster with better pricing. AI is increasing capacity without adding machines or people, allowing businesses to offer more competitive pricing and/or lead times.
The closest parallel for shop owners is the introduction of CNC machines in the 1960s. At the time, many companies hesitated to shift from manual mills and lathes because they worked and were familiar tools. Computers were new, expensive and unfamiliar technology. Yet companies that adopted CNC technology quickly gained advantages in speed and precision in a way that the world had not seen before.
We are at a similar turning point now. People saying “my ERP system works” don’t yet understand that we’re in a different world now. AI allows companies to make decisions faster and more accurately by using far more data than any human can process.
History has taught us that every technological advancement that allows for parts to be made faster, with a higher degree of accuracy, has always won out. This time will not be any different.
ERP is for Storage, AI is for Computation
It is true that for decades, ERP systems have been the foundation of manufacturing operations. They were developed to move information out of filing cabinets and into digital systems, making it easier to access and organize. That alone created a meaningful advantage. But ERP systems were never designed to act on data. They store orders, inventory, customer information and purchase orders, but they rely on people to interpret and act on that information.
In practice, ERP is a pull system. You need to ask for what you need. You run reports and extract insights and every piece of data has already been entered and seen by someone else. AI changes the dynamic. It introduces a push system. Instead of waiting for a request, it surfaces what matters. It can point out which jobs are late and what you should do about it. Or it shows you what jobs were unprofitable and why, how a schedule should be adjusted to increase throughput and, in many cases, it can even take the actions for you.
Emergent AI technology is already capable of more than many companies are comfortable with. Today, an AI system can take a drawing and instantly extract a bill of materials, auto-create the POs you’ll need from the most appropriate vendor, tell you the lead time to commit to, market-value for the part, your expected margin and win rate, auto-bubble the print and place it on the schedule in the most optimized slot, all in a matter of seconds without human intervention. Imagine the advantage this provides and compound that advantage by every quote received.
Most companies are not ready to hand over this level of control. The shift to fully trust AI may take another year. Even so, the capability is already here. So, what should manufacturers do now to prepare?
A Playbook for Utilizing AI
The first step is to digitize everything. Every part of the operation needs to be captured in a system where it can be accessed and used. This means eliminating paper travelers. The second is to connect that data so it is not siloed across different tools and departments. The third is to rethink how software gathers data.
I hear the same “garbage in garbage out” concern daily. Today, AI can collect exponentially more than what an ERP system was built to capture, while collecting it in a passive way. Data can be collected by tapping into video feeds in CNC machines, detecting employees working on jobs to auto-start/stop clocks using Bluetooth low energy beacons, extracting information and attachments from your email to auto-generate quotes. This elimination of manual data entry is a huge driving factor in increasing data integrity.
Like some of the examples above, there’s vast amounts of data that have historically never been seen as information to put into an ERP system and therefore don’t have a place where it can be stored. But in an AI-native world, being able to feed this data into a large language model for an AI engine to interpret will open completely new avenues of possibilities.
This shift is already underway. AI is not just another incremental improvement in manufacturing technology. It represents a fundamental change from storing data to using it in an intelligent and increasingly autonomous way.
The manufacturers who recognize this early and act on it will define the next phase of the industry. The rest may find themselves trying to catch up in a race that has already started.
Tyler Buxton is head of customer experience and sales at Fulcrum.
Tyler Buxton, Head of Customer Experience and Sales, FulcrumFulcrum
