Manufacturers and other legacy sectors are facing mounting pressure from economic volatility, labour shortages, and growing sustainability expectations.

According to Barclays, almost all (97.5%) of UK manufacturers agree that hiring and retaining skilled labour poses a significant challenge to their business, and over 80% say that digital skills are harder to acquire because of competition from other sectors.

With this, a major portion (91%) of manufacturers say that they are taking on more responsibility to train their workforce due to the scarcity of skilled labour.

So, how can digital technologies help close this skill gap, while at the same time push efficiencies, make manufacturers more cyber secure, and be sustainable at the same time?

According to Parm Sandhu, VP of enterprise 5G products and service at NTT Data, industries such as manufacturing often face these structural issues: a retiring workforce, demographic pressures, and the need to adapt business models in the face of rising costs and higher interest rates.

A recent partnership with the Roularta Media Group, a traditional printing manufacturer based in Austin, Texas, serves as a case in point. When NTT Data began working with the firm, it was still at an early stage of digital transformation, burdened by fragmented processes and a largely manual operating model.

“They had a lot of paper-based workflows,” Sandhu explains. “We started with a small proof of concept focused on basic connectivity and communications within the factory, then scaled from there.”

The initial improvements meant introducing private 5G connectivity and to allow for two-way communication among staff through push-to-talk devices.

“It was about giving workers tools they never had digitising rather than relying on clipboards and paper forms,” he adds.

The longer-term goal was more sophisticated: applying NTT Data’s lightweight edge AI platform, known as Ajax, to support real-time data capture, machine optimisation and predictive maintenance.

The system operates locally but is trained in the cloud, assisting faster inference and low latency.

Manufacturing with agentic AI

 

NTT data is now working on agentic AI specifically for manufacturing.

“We’re deploying AI agents for specific outcomes like predictive maintenance or process automation,” Sandhu says. The models are trained in the cloud, but the inference happens locally, in real time, he says.

“We’re running proof-of-concepts with clients now, especially in sectors where data collection and contextualisation are major challenges.”

Data sources can range from sensor-enabled legacy machinery to 5G-connected cameras. Ajax is modular, allowing companies to start small and scale as required.

Beyond technology, Sandhu says clients are increasingly seeking integration and simplicity. “Often, clients might start with app developers or hardware vendors who try to piece things together. But that can be difficult to manage,” he says.

“What [Roularta] valued in us was that we provided everything,” Sandhu says.

Recently, the company expanded its cybersecurity capabilities through a partnership with Palo Alto Networks, embedding security directly into the network architecture.

Security is no longer a bolt-on, Sandhu adds. “If your network goes down, your factory goes down. So, we start with secure architecture as the foundation.”

The Roularta engagement is now serving as a template for other industrial clients, particularly in chemical processing and integrated manufacturing: sectors where legacy systems are common and a swift return on investment is critical.

NTT Data is also exploring partnerships with companies such as SAP to combine its edge and AI offerings with established cloud platforms. “We’re looking at how we take what we’ve built and replicate it in other verticals,” says Sandhu. “Especially in sectors that are rich in outdated technology but low in digital integration.”

By training models in the cloud but running them locally, NTT Data argues it can deliver the benefits of AI without compromising on speed or control.

Sandhu believes this approach is particularly attractive to firms concerned about disruption. “We’re flexible: we don’t force clients to throw away what they already have. We integrate where possible.”

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