
Manufacturers are under pressure. Customers across all industries want their products designed, customised and manufactured at speed to meet the individual needs of end consumers. This is forcing manufacturers to find innovative ways to accelerate development cycles, while maintaining quality and producing goods that are cost-efficient.
These demands are being compounded by global headwinds. Supply chain disruptions caused by geopolitical issues and climate change are common. Fluctuating consumer demands are causing forecasting and inventory management issues. And labour shortages and skill gaps must be addressed as the industry undergoes rapid digital transformation.
From startups to industry giants, AI is helping manufacturers tackle challenges and transform the way they work. Insights from the CohnReznick Manufacturing Checkup study revealed that 75% of manufacturers are currently investing in and applying AI across almost all business functions. A separate study by Lucidworks published in 2024 also found that half of the manufacturers surveyed had already reported cost savings from AI adoption. The UK Government is also investing heavily in advanced manufacturing innovation, committing £4.3bn – including up to £2.8bn in R&D programmes over the next five years – to accelerate automation, digitisation and technology adoption.
The manufacturing marketplace
Digital platforms are accelerating manufacturing’s AI-driven transformation. Xometry is an AI-powered digital marketplace that helps businesses quickly source and manufacture custom-made parts by connecting them with a network of vetted suppliers. It enables designers and engineers to upload designs onto the platform and use an instant quoting engine to determine manufacturing feasibility, costs and lead times in seconds. It also allows manufacturers to browse curated listings of profitable, potential jobs from buyers.
In fact, over 70,000 engineers and procurement leaders already use Xometry to source their manufactured parts. Xometry’s regional director of sales for Europe, Ole Marx, says this end-to-end solution helps to solve several big problems with traditional manufacturing. “Previously, designers and engineers needed to carry out a manual process to establish manufacturing feasibility,” he says. “They would need to connect with various manufacturers to get feedback on costs, lead times and materials and ultimately find the right manufacturing partner. It was a lengthy and costly procurement process.”
The instant Design for Manufacturability (DFM) feedback provided by Xometry’s AI tech enables the rapid iteration of designs, meaning clients ranging from start-ups to global brands such as Bosch can quickly move from design to production and meet the needs of their end customers. Quality control is another tangible benefit. Marx says, “Our platform now has a marketplace of more than 10,000 suppliers across the UK, Europe, the US and Asia. Each one is vetted for capability, quality assurance and prior performance, which enables Xometry to match buyers’ projects with the right manufacturing partner.”
Manufacturing is entering a new era where agility and scalability matter as much as efficiency
AI-optimised supply chains
But even the right manufacturing partner can be blindsided by supply chain problems. In recent years climate change, the Russia-Ukraine war and the Covid-19 pandemic have all damaged the ability of manufacturers to source raw materials, find new suppliers and meet fluctuating demands for parts and products. The result is a relentless pressure to meet the needs of customers, while keeping operational costs down and turning a profit.
All of this means that supply chain agility has never been more critical. According to Xometry’s 2026 Manufacturing Outlook Report, 56% of leaders say their AI investment focus has been targeted at their supply chains. For some, reshoring – the process of moving manufacturing facilities or working with suppliers closer to their end consumers – is proving popular. 45% of global executives are actively working to reshore facilities and 29% have already done so. Xometry’s platform enables organisations to de-risk their supply chains and boost resilience by using its algorithm to find suppliers on demand.
Visibility is another imperative. Sharp fluctuations in demand for materials can result in sudden increases in costs, which can impact margins and make certain products financially unviable. But AI can help leaders to predict costs ahead of time. “The cost of materials can vary massively month to month,” says Marx. “We can use our customer base to look into the future and see what the likely cost will be in November or December, for example, if businesses are looking to manufacture a product for the festive period.”
Visibility could also help leaders to meet sustainability targets. Procurement teams must now have real-time insights into their entire supply chains to minimise their carbon footprint. This enables procurement teams to assess the environmental impact of their sourcing decisions, facilitating the measurement and management of Scope 3 emissions.
The UK government expects manufacturers to play a central role in achieving net zero by cutting industrial emissions, improving energy efficiency and reporting transparently on Scope 1, 2 and material Scope 3 emissions. Suppliers to public contracts are also required to publish carbon reduction plans, making supply-chain visibility critical not just for compliance but for competitiveness.
Talent gaps and the future of AI
AI may be crucial in resolving some of the major industry challenges. According to the latest Office for National Statistics (ONS) figures, there were 35,100 manufacturing job vacancies in the UK, in the three months up until August 2025. Procurement talent is in particularly short supply. According to research by Hays, 58% of UK hiring managers struggled to find the right procurement talent over the past year. Only 9% of secondary vocational students focus on engineering, manufacturing, or construction, versus a 32% average, revealing the ongoing challenge of nurturing future technical talent.
Digital skills shortages and competition from other sectors were cited as two key issues in identifying the right talent. Marx says AI could fill the gap. “Sometimes we work with customers that don’t even have a procurement department,” he says. “So then we talk to an engineer who has to order parts and we act as their longer procurement arm.” But even large organisations with vast procurement teams can struggle to scale manufacturing capacity in the event of issues with their existing suppliers. Here, Xometry can integrate with existing e-procurement platforms such as SAP, Coupa or Ivalua to streamline procurement processes and seamlessly push orders into their existing systems, eliminating traditionally manual time-intensive tasks.
In the future, AI is likely to play an increasingly transformative role in manufacturing. AI innovation is expected to add up to £47bn a year in productivity gains for the UK over the next decade, signalling the huge economic potential of AI-powered manufacturing platforms. “Larger organisations have procurement teams and suppliers in different countries, but procurement departments are often siloed,” says Marx. “Our platform could evolve to become a bridge between these silos and different countries and enable more strategic sourcing.” Project management is another potential use case. “Some clients use Xometry to produce 10% of their project, others 50%.” For complex projects with multiple components, AI could be embedded more extensively to help manage and synchronise all moving processes
It’s clear that manufacturing is entering a new era where agility and scalability matter as much as efficiency. Bridging gaps in talent through AI-powered platforms like Xometry can empower businesses to access expertise when and where it’s needed and generate insights and cost savings pre-production, enabling them to manufacture with speed and confidence. Leaders that embrace a more flexible, resilient and AI-driven model of manufacturing will be well-positioned to thrive in a world of rapid change.
5 ways to unlock ROI with AI
AI is no longer a futuristic concept. It’s a practical tool that can accelerate efficiency, reduce costs, and improve decision making in manufacturing. Marx shares insights on how leaders can leverage AI to generate real returns.
Before integrating AI, leaders should define their goals and metrics. A good starting point is to identify the processes where AI can have the most immediate impact, such as procurement, quoting or quality control. “You should start with a pilot project,” says Marx. “Here you can create firm KPIs to test AI. Tracking specific metrics from the start allows companies to measure ROI effectively.”
AI can process vast amounts of data far more quickly than humans, providing actionable insights. “By using Xometry’s AI-powered instant quoting engine, leaders can get immediate feedback on manufacturing feasibility or predict product build costs in seconds,” says Marx. The result is that designers, engineers and buyers can avoid wasting time and vast sums of money on pursuing projects that aren’t commercially viable and rapidly reiterate designs for parts that could be used to drive revenue and ROI.
AI can reveal hidden potential savings and optimise resource allocation. From selecting the right material to choosing the most efficient production method, AI supports smarter decisions that protect margins. With AI, customers can pinpoint cost-saving adjustments, unlocking both material savings and wider operational efficiencies.
Before production, AI evaluates uploaded designs to identify technical issues, such as incorrect thickness or unsuitable materials. “This ensures that problems are caught early, reducing the risk of producing defective parts,” says Marx. With over 10,000 suppliers globally, Xometry also uses its AI platform to standardise processes, ensuring that quality expectations are met across different providers.
For many companies, the challenge isn’t just adopting new technology – it’s having the expertise to use it effectively. AI empowers smaller manufacturers and startups to compete with larger players by bridging skill gaps and offering guidance in procurement, engineering, and production. “We serve as their extended procurement arm,” says Marx. Beyond driving cost savings and faster operations, AI enables strategic sourcing, fosters cross-department collaboration, and provides project-level insights, laying the foundation for sustained growth and innovation.

Manufacturers are under pressure. Customers across all industries want their products designed, customised and manufactured at speed to meet the individual needs of end consumers. This is forcing manufacturers to find innovative ways to accelerate development cycles, while maintaining quality and producing goods that are cost-efficient.
These demands are being compounded by global headwinds. Supply chain disruptions caused by geopolitical issues and climate change are common. Fluctuating consumer demands are causing forecasting and inventory management issues. And labour shortages and skill gaps must be addressed as the industry undergoes rapid digital transformation.
From startups to industry giants, AI is helping manufacturers tackle challenges and transform the way they work. Insights from the CohnReznick Manufacturing Checkup study revealed that 75% of manufacturers are currently investing in and applying AI across almost all business functions. A separate study by Lucidworks published in 2024 also found that half of the manufacturers surveyed had already reported cost savings from AI adoption. The UK Government is also investing heavily in advanced manufacturing innovation, committing £4.3bn – including up to £2.8bn in R&D programmes over the next five years – to accelerate automation, digitisation and technology adoption.