The rise in digital manufacturing investments overall is expected to continue in 2025. But there are specific areas where organizations might be pulling back on that trend.
In its "2025 Predictions: Smart Manufacturing and Mobility" report, Forrester Research predicted four areas where manufacturers will continue making investments and where current investment efforts could change.
The overriding trend is that connecting digital technologies to physical assets and processes will continue. But some areas are facing challenges, according to Paul Miller, an analyst at Forrester Research and co-author of the report.
"There's a recognition that digital drives a lot of opportunities and potential in manufacturing. But the traditional, physical vendors are struggling sometimes to make that shift and to bake digital deeply into what they do," Miller said.
Many manufacturers have been talking about and planning to move from making and selling physical products to developing digitally enabled services but doing this for real is difficult and requires significant change, he said.
"We've seen a number of organizations move in that direction and pull back a little bit as they realize it's harder than they thought it might be," Miller said. "There's still work to do there, but they're getting there."
Four digital manufacturing trends for 2025
Forrester's report identifies four trends that will affect digital manufacturing in 2025.
First, the report predicts that 25% of large last-mile service and delivery vans in Europe will move to electric vehicles (EVs). This runs counter to the overall sales growth of EVs, which is seeing a slowdown, especially in passenger EV sales, Miller said.
"With a large fleet, you can put in the infrastructure to charge in the depot, you can mitigate the cost over all of the miles those fleets are driving every day," Miller said.
However, the report also predicts that 50% of manufacturers will slow down plans to electrify operations and processes. Although manufacturers are interested in electrification to save on fuel and be more environmentally responsible, Miller said that grids in developed markets don't currently have the capacity to handle additional demand.
"Those grids are trying to put in more capacity and to cope with bidirectional power flows, but that investment is moving quite slowly," he said.
The introduction of humanoid robots into manufacturing has had a lot of hype, but the report predicts that fewer than 5% of manufacturing robots will be human in form. This is because the use cases for which humanoid robots are best suited aren't well understood or deployed at scale yet, Miller explained.
"Most of the automation use cases now are task-specific and designed around the machine," he said. "In those cases, a humanoid form factor isn't the best one. You want something that has a low center of gravity or is fixed or on a track because that gives it greater stability, greater strength and makes it more cost-effective."
Finally, Forrester Research predicts that a major car manufacturer will make significant cuts to its digital development team. All of the traditional car makers have invested in digital services to build software-defined vehicles and own the customer relationship, but these investments are not paying off yet, Miller said. For example, Volkswagen's Cariad and Toyota's Woven initiatives are losing money.
"The [move to digitization] makes sense, but traditional automotive manufacturers aren't quite managing to deliver a compelling digital proposition yet," he said. "We'll see some repositioning over the next year or so as they change their investments, perhaps bringing in more partners and focusing on the areas where they can deliver demonstrable value."
Steady but slow progress
The digital transformation of manufacturing is ongoing, but it's still a work in progress, according to the recent "2024 State of Manufacturing Survey: North America" from Parsec Automation Corp., a provider of manufacturing execution system software.
The second annual survey asked manufacturing practitioners from the shop floor to executive levels about the current issues they face and are developing strategies to address.
The digitization of manufacturing is a challenge because it requires reimagined workflows and employees who are trained on new tools such as AI and data-first thinking, according to the report.
Progress on digitization initiatives is split, with half of survey respondents reporting that they have either completed (32%) or are well into (18%) the implementation process. However, 32% of respondents are in the early stages of implementation, 15% are in the planning stages and 3% are researching options.
AI is one of the top technologies in digital manufacturing initiatives. While there's increasing interest in AI for manufacturers, deployments are not widespread, according to the report.
There's a recognition that digital drives a lot of opportunities and potential in manufacturing. But the traditional, physical vendors are struggling sometimes to make that shift and to bake digital deeply into what they do.
Paul MillerAnalyst, Forrester Research
"CEOs, COOs and CFOs are talking passionately about AI and its adoption and there's a very high interest level in AI within manufacturing," said Eddy Azad, CEO at Parsec. "But then you need to execute it, and the majority of manufacturers are not positioned to meaningfully use it."
Generative AI, which has dominated much of the discussion around AI in the last two years, is not suited for the needs of manufacturers, he said. Generative AI is essential for processes around content creation. But manufacturing is better suited for the data analysis and predictive uses of AI.
"Many companies have come out with algorithms that are very mission-specific and are looking at pattern recognition to be able to predict what is going to happen," Azad said. "There's also a motion to be able to train AI agents very specifically to your operations. What are you looking for? What are you trying to prevent? What are you trying to predict?"
Almost half of survey respondents (47%) named technical readiness the biggest AI implementation challenge, followed by data accessibility and quality (44%). However, the survey indicated that most manufacturers are either ready for AI or are getting there despite the challenges and concerns. A majority of respondents (65%) claim to be somewhat prepared to adopt and effectively use AI, with another 15% indicating they are very prepared.
Manufacturers will need to educate users about how to use AI and what to use it for to fully take advantage of it, Azad said.
"On the shop floor, you're looking at how something affects your output, the schedules you have to meet, the quality metrics you have to meet and the issues you're having," he said. "You're not asking general questions of the AI like you would with a ChatGPT."
Jim O'Donnell is a senior news writer for TechTarget Editorial who covers ERP and other enterprise applications.
