For decades, one of manufacturing's biggest technology questions has been: what can we automate next?
Robots took on repetitive physical tasks. Automated production lines increased throughput. Sensors began capturing information directly from machines. Software digitised processes that once depended on paper, spreadsheets and manual reporting.
At PPMA Show UK 2026, however, another question is likely to be heard increasingly often:
What if technology could help people think faster, too?
Artificial intelligence will undoubtedly be one of the industry's biggest talking points this year. But beyond the headlines surrounding AI sits a much more interesting development for manufacturers.
We are beginning to move from technology that simply collects information to technology that can help people interrogate, interpret and act upon it.
And that could have significant implications for the factory floor.
Manufacturing doesn't have a shortage of data
Modern factories generate extraordinary amounts of information.
Production counts, downtime events, cycle times, quality records, maintenance information, operator inputs, shift performance and machine data can all contribute to understanding how an operation is performing.
The problem is that having information and being able to use it effectively are two very different things.
A production manager shouldn't need to spend hours manipulating spreadsheets to understand why yesterday's shift underperformed.
A site leader shouldn't have to navigate multiple reports to identify which line is creating the greatest opportunity for improvement.
And an operator shouldn't need to become a data analyst to understand what is affecting their line.
The next generation of manufacturing technology is beginning to tackle that gap.
The interface is changing
One of the most interesting developments in AI isn't necessarily what happens behind the technology.
It's how people interact with it.
For years, extracting insight from operational systems has largely meant dashboards, filters, reports and predefined metrics.
Generative AI introduces another interface entirely: conversation.
Instead of navigating through layers of information, imagine asking:
- Which production line experienced the most downtime this week?
- What were the three most common causes?
- Which shift performed best yesterday?
- Where should we focus if we want to improve OEE?
The significance isn't simply that a system can produce an answer.
It's that sophisticated operational information potentially becomes accessible to many more people, much more quickly.
That changes the role data can play inside a manufacturing business.
From dashboards to decisions
Dashboards aren't disappearing.
But the expectation placed on manufacturing software is changing.
For a long time, digitisation focused heavily on making information visible. The next stage is about making that information easier to understand and use.
This is where AI becomes particularly interesting.
Its potential isn't confined to producing another report. It can help teams explore relationships within their production information, surface patterns that deserve attention and reduce the time between recognising a question and finding an answer.
For manufacturing leaders, that could mean less time searching for information and more time deciding what to do about it.
For frontline teams, it could make operational intelligence far more approachable.
And for multi-site manufacturers, it could make comparing performance and sharing knowledge across facilities considerably easier.
But AI needs something to work with
There is an important reality behind all of this.
Artificial intelligence cannot magically fix poor information.
If production data is incomplete, inconsistent or inaccessible, adding AI doesn't suddenly create operational intelligence.
This is why some of the most important AI work manufacturers can undertake today may have very little to do with AI itself.
Connecting production information. Improving the consistency of downtime capture. Creating common definitions. Digitising manual processes. Building reliable operational datasets.
These foundations determine how valuable intelligent technology can ultimately become.
The conversation therefore shouldn't simply be, "How do we introduce AI into our factory?"
A better question might be:
"Do we have the operational information needed for AI to actually help us?"
The factory becomes more conversational
There is something compelling about where this ultimately leads.
Manufacturing technology has historically required people to learn the language of systems.
AI increasingly allows systems to learn the language of people.
That could make sophisticated manufacturing intelligence available beyond specialist analysts and technical teams, placing useful information directly into the hands of the operators, supervisors, engineers and managers making decisions every day.
The result isn't a factory without people.
Quite the opposite.
It's a factory where people are better equipped to understand what is happening around them.
And that may be one of the most important technology shifts to watch at PPMA Show UK 2026.
OFS will be exhibiting at PPMA Show UK 2026 on Stand A47, including live demonstrations of Mayvn AI alongside the OFS manufacturing intelligence platform.
Visit the team to ask Mayvn a question about the factory floor and see what a more conversational approach to manufacturing intelligence can look like.
%20(1).webp)
