Key takeaways

Streamlining tasks, predictive maintenance, and customer support showcase active AI integration.
Machine learning optimises decisions, marketing, and efficiency, transforming businesses amid data explosion.
Digital transformation is imperative, as global spending reaches $2.16 trillion, with European firms exhibiting cautious but continuous investment.

In the first of a series of articles, RSM experts from across Europe share what they’re seeing as businesses adopt and adapt to new technology. 

The clock is ticking. It’s nearly a decade since the former executive chairman and CEO of Cisco Systems sounded the death knell for companies that didn't move with changing technology. His oft-quoted prediction in 2015 was that 40 per cent of all Fortune 500 businesses would fail over the coming ten years if they did not radically change to accommodate new technologies. 

Whether the intervening years have vindicated that prediction or not, few now doubt the business case for digital transformation. Spending on the technologies and services underpinning digital transformation is estimated to reach $2.16 trillion in 2023. That’s despite rising economic uncertainty; RSM research in the UK last year showed almost half (49%) continuing their investment in digital technologies and a further quarter (24%) scaling them up. This is an ongoing trend, albeit European businesses being more cautious than in the US. 

By contrast, in October 2023, RSM in the US recently reported “77% of surveyed executives said they plan to increase their IT budgets in 2024, and 74% stated digital transformation was the most important area or among the most important areas of investment for their companies.” 

But where will this investment go? Even by the standards of buzzwords, “digital transformation” is peculiarly broad. It encompasses a wide range of technologies with strikingly different applications between industries and even in the businesses within them – some more transformative than others. As MIT Sloan School of Management lecturer George Westerman has put it, “When digital transformation is done right, it’s like a caterpillar turning into a butterfly, but when done wrong, all you have is a really fast caterpillar.” 

So, are efforts helping businesses break out and fly or just crawl more quickly? To find out, we asked RSM experts from across Europe how they’ve seen the middle market adopting digital technologies in their businesses. 

How is the use of AI driving digital transformation across Europe? 

Really fast caterpillars 

In truth, the line between acceleration and transformation isn’t always clear. Much of the benefit to date from digital transformation has come from streamlining existing processes. Among the most common uses of technology to date has been the use of automation often supported by artificial intelligence (AI). 

“AI-driven automation is streamlining repetitive tasks, such as invoice processing, inventory management, and HR administration, leading to increased efficiency and cost savings,” notes Simone Segnalini, partner for Digital, Risk & Transformation at RSM Italy. “For example, AI-driven HR solutions are being employed by some companies to automate tasks like payroll processing, onboarding, and leave management, freeing HR professionals to focus on strategic efforts.” 

Businesses are actively seeking to integrate Industry 4.0 solutions. AI-powered technologies, like predictive maintenance and demand forecasting, enhance manufacturing processes and supply chains, resulting in reduced downtime and lower excess inventory expenses. 

Furthermore, AI is not only expediting operations but also reinforcing customer support. A similar trend can be observed in France as well. “ChatGPT and other AI-powered conversational interfaces are enhancing customer support and offering personalised recommendations, content and overall experiences to customers” says Lilian Boyer, IT and Risk Advisory manager at RSM France. 

In the UK, a recent RSM survey of 411 middle market businesses about their views on generative AI, 32% thought the technology would improve the business to a ‘great extent’, and 45% to ‘some extent’. Only 17% said ‘very little’.” 

In Sweden, specific industries are leading the way, according to IT manager Daniel Hasslund: "Take building maintenance, for example. With the implementation of smart sensors, technicians can receive signals alerting them to potential issues, such as a light bulb about to go out, before it becomes a problem. This seamless process requires the device to send out a signal, which is then received by the system, triggering the generation of a service order. The result is efficient and proactive maintenance, minimising downtime and improving overall operational effectiveness." 

More sophisticated applications are not always widespread, however. Hasslund also notes that while digital technologies are promoting efficiencies, adoption of AI by middle market businesses is largely in the “early stages”. 

“Many businesses recognise the importance of incorporating AI to foster development and stay competitive. However, the practical application of AI, including identifying suitable use cases and implementing them effectively, continues to pose challenges.” 

Companies often lack the in-house expertise to develop AI strategies and identify potential use cases and therefore face challenges in building or recruiting the required knowledge. Financial constraints often hinder firms from investing in tailored AI solutions, which could provide a competitive edge. Consequently, they turn to public AI solutions like ChatGPT, which come with data privacy limitations. 

While enterprise versions like ChatGPT for enterprise and Copilot aim to address some of these concerns, the capacity to develop custom solutions remains an issue. Looking ahead, public solution pricing can pose challenges, as exemplified by Copilot's initial $30 per user cost, which, once ingrained, may be difficult to transition from. Companies that do not embrace AI technology risk adopting costly and inefficient models, while well-resourced large enterprises gain an advantage. 

Will data transformation revolutionise future business strategies?  

Preparing for take-off 

"Organisations are increasingly open to new technologies, viewing them as fundamental to their evolution. It's widely anticipated that AI will be a game-changer in the foreseeable future," says José Pedro Gonçalves, Partner at RSM Portugal. 

Where technology cannot replace human resources, it can still enhance them, drawing on the massive expansion of available data in recent years – not least through the increase in smart devices and the Internet of things. The latter, as Boyer points out, is being used in a myriad of ways, such as improving asset tracking, optimising energy management and enhancing workplace safety. 

For many, however, the greatest value from the explosion in data is the intelligence that can be drawn from it. Businesses are increasingly employing machine learning to analyse large datasets and extract valuable insights, says Boyer. “Businesses are using these insights to make data-driven decisions, identify trends, and predict customer behaviours,” she says. The use of data analytics is helping businesses to optimise both their commercial product offerings and marketing strategies, as well as delivering efficiencies in supply chains and inventories. 

As businesses explore these new technologies, the truth is that adoption and applications are growing and developing at the same time. That may mean the transformation they bring looks less like the emergence of a butterfly from a chrysalis and more of a gradual evolution of the species. But the end result may be no less impressive.