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Artificial Intelligence (AI) is transforming the manufacturing industry by enhancing efficiency, precision, and adaptability in various production processes. The application of AI technologies, such as machine learning, computer vision, and natural language processing (NLP), enhances various aspects of production processes. AI has the capability to analyse large volumes of data from sensors, equipment, and production lines to optimise efficiency, improve quality, and reduce downtime.
Since the Industrial Revolution and the Industry 2.0 and 3.0 waves that added factory lines, computer-driven automation, and more precision fabrication technologies, automation has stood at the forefront of the manufacturing industry to assemble and manufacture products. AI is adding to this automation formula by adding aspects of intelligence that make these automated manufacturing processes more accurate and adaptable.
Deloitte’s analysis of S&P Global data reveals that while 2024 began with the manufacturing purchasing managers’ index (PMI) moving into expansion for the first time since April 2023 and continuing for the first half of the year, weaker demand nudged the PMI back into contraction in July 2024. Additionally, the November 2024 PMI report identified an ongoing combination of failing orders and rising customer inventories, which could signal the need for manufacturers to further cut production in the coming months.
While the rate of inflation has diminished, manufacturers continue to face higher costs: the producer price index for input materials and components seems to have stabilised but remains high, while total compensation, which includes wages and benefits, has continued its upward climb. In addition, although the labour market stabilised through 2024, talent challenges persist. Even as labour markets have loosened, nearly 60% of manufacturers in the National Association of Manufacturers (NAM) outlook survey for the third quarter of 2024 cited the inability to attract and retain employees as their top challenge.
However, the problems faced by the manufacturing industry extend beyond the US as manufacturers in the UK find themselves struggling too. Here are five key challenges UK manufacturers face in current times:
In 2025, the UK manufacturing industry will face a state of stunted growth should manufacturers fail to address the now critical skills gap to meet demand. There is an overwhelming consensus among manufacturers about the severity of the skills gap. In research by The Manufacturer and Barclays Corporate Banking, it was found that 75% of manufacturing professionals identified the lack of skills as the biggest barrier to growth, yet 97% agree that hiring and retaining skilled labour presents a challenge to the growth of their business.
This can be attributed to different reasons, and one of them is the difficulty in retaining young talent. In the next year, Gen Z are expected to make up one-third of the UK workforce, who expect more flexibility and a better work-life balance but also work that is meaningful and fulfilling. The Manufacturer report finds that several manufacturers highlighted this issue, citing concerns over their mindset, expectations, and commitment levels. However, others noted that young workers often enter manufacturing by chance rather than with a clear career focus. Another report highlights that 41% of SMEs reported losing apprentices to job or career changes, with many seeking better opportunities elsewhere, underscoring the difficulty in retaining young talent who may not see manufacturing as a long-term career path.
In addition, UK manufacturers find themselves facing stiff competition from other industries. The sector is often overlooked by young people, who frequently gravitate towards opportunities in other industries, such as tech or finance.
The drive toward supply chain localisation has gathered in recent years, spurred by a series of seismic global disruptions: the pandemic, geopolitical unrest, and escalating environmental pressures. This is not new territory for UK manufacturers. Brexit reshaped trading relationships overnight, pushing many EU customers to source goods closer to home.
Similarly, this is also reflected in the UK, as reshoring and nearshoring are now gaining real traction as manufacturers grapple with rising costs and fragile global supply chains. For UK manufacturers, the business case is increasingly clear – rising costs, supply chain instability, and the need for tighter operational security are driving firms to bring production closer to home.
Data reveals that 58% of UK manufacturers are already reshoring, with 90% reporting benefits such as greater supply chain resilience and cost efficiency. One manufacturer, cited by the BBC, experienced an £800,000 surge in orders, with up to 43% linked to reshoring efforts.
Beyond cost savings, reshoring is also a response to shifting market dynamics. As product cycles shrink and consumer demands accelerate, proximity to production offers UK firms the flexibility to innovate and adapt. This closeness fosters seamless collaboration between design and production teams, enabling faster adjustments to products and processes. Meanwhile, the “Amazon effect” has raised expectations for swift delivery times, making localisation a competitive necessity.
Despite the clear benefits of advanced technology, UK manufacturers have held back over doubts of adopting new tech and innovation. The reluctance stems from entrenched ways of working and uncertainty about the cost, complexity, and potential risks of a digital transformation. The fear of disrupting long-established systems outweighs the promise of increased productivity. Employees worry about job losses, while leaders hesitate to invest without guaranteed returns.
The UK’s adoption of advanced manufacturing technologies is moving forward, but the pace is uneven; aerospace and automotive giants are blazing the trail, but SMEs remain stuck, held back by financial hurdles and a lack of digital expertise.
Rising operational costs are reshaping the landscape, squeezing margins, and forcing tough decisions across the board. Recent data from Make UK reveals a stark reality: 70% of UK manufacturers have experienced cost increases of up to 20% over the past year, with 8% reporting increases of up to 50%.
The continued grapple with labour market challenges, from persistent skills shortages to rising employment costs, is weighing on manufacturers. Vacancy levels have stabilised, but wages are climbing as businesses compete for skilled talent in a tightening labour pool. This escalating cost of labour places a strain on manufacturers.
AI can be pivotal throughout many stages of the manufacturing process:
AI-powered robots can make a substantial impact in the manufacturing industry. Non-intelligent robots are programmed to do specific tasks and automate them; collaborative robots that are AI-driven are being used to automate repetitive tasks, such as assembly or welding, or even materials handling.
AI-powered computer vision solutions are also commonly applied to assist with quality control and inspection. Computer vision systems are being deployed to help spot defects in products throughout the manufacturing process. These systems are designed to detect the smallest of imperfections throughout the process so that defective products can be removed from the production line or get fixed or scrapped before they get into customer’s hands.
AI in Manufacturing is helping move the industry closer to the idea of the smart factory and the concept of Industry 4.0, in which machines, sensors, and systems are interconnected and communicate with each other. These interconnected systems collect data in real time to optimise production processes, enhance decision-making, and enable predictive maintenance.
These fully automated and intelligent systems can be operated with minimal human intervention, allowing the idea of the “lights out factory” in which manufacturing systems can happen even while the lights are off.
AI is helping to make manufacturing processes more reliable, efficient, cost-effective, and repeatable, giving factories more uptime, driving down the cost of goods, and reducing issues relating to labour shortages and staffing challenges.
AI analyses data from sensors embedded in machinery to predict when equipment is likely to fail. This allows maintenance to be performed only when necessary, reducing equipment downtime and maintenance costs. This also decreases the chances of the production line grinding to a halt.
AI is capable of analysing all equipment data to know in advance when a machine might be heading towards failure. In anticipation of future potential failure, those machines may be taken offline at a convenient time to perform predictive maintenance.
AI is also helping to keep manufacturing processes running by optimising supply chain management through predicting demand, optimising inventory levels, and improving logistics. Companies use AI to analyse vast amounts of data from suppliers, weather patterns, and market trends to enhance supply chain efficiency. With the help of AI, organisations can predict demand more effectively and optimise inventory levels, as well as improve overall logistics.
Moreover, AI can optimise production schedules by analysing data, including order volumes, machine availability, and workforce capacity. This helps manufacturers maximise efficiency and minimise bottlenecks.
To keep energy-intensive production costs low, AI is also being used to monitor and optimise energy consumption in manufacturing facilities. AI systems analyse data from energy meters and production equipment to identify inefficiencies and suggest ways to reduce energy usage, leading to cost savings and a more efficient and environmentally friendly use of energy.
Whether it is the design of a product or packaging, or improving overall product effectiveness, usability, reliability, or efficiency, AI is being used increasingly to accelerate product design and prototyping. AI systems can analyse thousands of different alternatives and options and identify desirable characteristics, factoring in cost, manufacturability, supply availability, energy usage, and other considerations.
These AI systems consider many different options with millions of different parameters and considerations, and help manufacturing firms design more efficiently, and more effectively deliver products to market.
As part of this process, organisations are employing AI to improve demand forecasting accuracy by analysing historical sales data, market trends, and external factors such as economic indicators. This helps manufacturers better plan their production and inventory, reducing the risk of overproduction or stock-outs. These AI-powered forecasting systems can help anticipate demand and avoid supply chain or inventory disruptions that cause significant problems across the economy.
A key innovation is the AI Agent powered by Microsoft Copilot Studio which automates tasks and streamlines workflows, securely grounded on data sourced from various systems by using Microsoft Dataverse as a central hub.
Read more about Embracing the Agentic Era here.
Microsoft Fabric enhances analytics, helping businesses turn data into insights. For customisation, Microsoft Power Platform offers low-code tools to build apps and automate processes, while Microsoft AppSource provides industry-specific solutions from Microsoft Partners.
Additionally, to stay ahead of their competitors, manufacturers need to optimise operations by reducing costs, minimising downtime, improving agility, and ensuring efficient production. This requires data-driven decision-making that takes advantage of the industrial Internet of Things (IoT), AI-driven automation, integrated data clouds, and edge-to-cloud architectures to enable real-time insights, predictive maintenance, and quality control.
Microsoft Dynamics 365 includes applications to manage finance, supply chain, sales, and customer relationships, designed to unify business data, improve efficiency, and simplify decision-making. The applications work seamlessly with Microsoft 365, which enhances productivity and collaboration with leading applications like Word, Excel, and Microsoft Teams, while Azure provides cloud infrastructure and IoT capabilities.
As AI grows to be more prominent in the manufacturing industry to cope with the rising staff shortages and increasing operational costs, many manufacturers will look to incorporate the technology into their systems. That’s where we come in: our deep expertise in your industry means we can adapt our AI solutions to meet your unique needs, maximising the benefits of Copilot and other Microsoft AI resources.
We are a Microsoft Partner, accredited with the Solutions Partner for Data and AI designation. Our comprehensive understanding of the Microsoft ecosystem allows us to empower your organisation to maximise the potential of AI.
We have also worked with many manufacturing clients to implement Copilot into their businesses and build custom Copilot functionality that addresses the specific challenges inherent in the industry. Beyond that, we support the implementation of best practices, stringent security measures, and effective governance.
With our Partner status, we bring our customers access to exclusive Microsoft funding opportunities. We are here to help businesses like yours leverage these funds to accelerate growth, adopt cutting-edge technologies, and transform your operations. Our Copilot and AI funding is available through Vision & Value workshops and Proof of Value workshops for eligible companies.
To find out if your organisation is eligible for funding, read about Microsoft Funding here.
