The proliferation of AI-powered tools in the workplace has accelerated in the past 12 months, and the pace of adoption is only set to continue. According to 2025 IDC research commissioned by Lenovo, business leaders and IT decision-makers (ITDMs) based in EMEA expect to increase spending on AI by 104% this year, and in the UK alone, spending on AI has increased by 84% since 2024.
Lenovo’s global survey reveals that leaders in EMEA are the most satisfied compared to their counterparts in other regions, and report the highest success rate in implementing AI projects. Some 94% of AI projects undertaken in the past 12 months at least met expectations, with nearly a third (31%) exceeding the original aims. The region is also the most optimistic around AI, with 55% of management teams feeling positive about its potential.
“We’re starting to see organisations achieve AI success and maturity compared to 18 months ago,” says Greg Smith, executive director and general manager for EMEA at Lenovo Solutions and Services Group.
Smith says the most successful businesses are achieving significant increases in efficiency, reducing time to market and creating more innovative products. Typically, those businesses that are reporting the highest satisfaction have taken a systematic and structured approach to their AI rollouts.
“Generally, when I talk to customers, their success is based on them starting small,” says Smith. “They don’t try to solve every problem in one rollout. They focus on one problem, and then look at incremental improvements.”
Lenovo’s research suggests AI will comprise nearly 20% of all IT budgets in 2025, while 42% of organisations expect to focus on implementing generative AI use cases, up from 11% in 2024. With budgets set to increase this year, ill-defined goals and overly ambitious rollouts could scupper AI plans before they even get going.
“I talk to a lot of CIOs who started early and didn’t necessarily have the intended outcomes defined,” says Smith.
“And really, generative AI was the shiny new thing in the marketplace. In that period of hypergrowth, a lot of people jumped in without starting with the basics. You need to make a clear assessment. What is the goal? What is the desired outcome for the business? Otherwise, a lot of time, energy and money can be wasted.”
According to Lenovo’s research, the most common stumbling blocks for AI projects that failed to meet expectations were challenges around scaling, uptake and data quality. Looking at the data more specifically, many EMEA businesses reported issues around sovereignty and compliance and access to quality data as limiting factors.
Smith says Lenovo helps customers parse and process information using its hybrid AI model, structuring data from internal sources and exterior sources to ensure success. Its Hybrid AI Advantage platform brings together the Lenovo AI Library of proven AI use cases with a full-stack of portfolio AI devices, infrastructure, and services, along with industry partners to help organisations achieve outcomes from AI at scale.
Customers can test and prove the use case is actually going to work, and that return on investment can be demonstrated at a small scale
He says that a key aspect of deploying AI at scale resides in the data itself, including “how you ingest it, how you prepare it, how you govern it and how you manage it going forward.”
From there, businesses can model new AI programmes, testing how new processes can augment existing protocols, creating efficiencies and hopefully scaling up during rollout.
“Part of our services model is trying to help customers spin up proofs-of-concept in between 30 to 60 days, which is considered fast in the market,” says Smith. “Customers can test and prove the use case is actually going to work, and that return on investment can be demonstrated at a small scale.”
ITDMs may still struggle to convince senior leadership of return on investment. Lenovo’s research shows a third of businesses that have yet to adopt AI are concerned about financial risk. Smith says the surge in interest in AI-powered solutions has, in some ways, made ITDMs’ jobs easier.
However, as budgets tighten due to macroeconomic headwinds, the pressure on them to demonstrate clear returns is increasing.
“The driver of AI is often the most senior leadership,” he says. “I’ve heard stories of CEOs arriving in the office and telling their CIO: ‘We need to move on AI. Our competitors are ahead of us.’” This sets AI apart from other areas of innovation, where leaders may struggle to get the ear of the CEO. “There’s quite a lot of fear in the market, which can be advantageous, as you’ve immediately got senior leadership buy-in,” says Smith.
However, he points out that budgets aren’t limitless. “Maybe 18 months ago it was easier for ITDMs to prototype something. Now there’s a lot more scrutiny on costs and outcomes. ITDMs need to be more than technology experts. They need to understand how all of this touches and affects the organisation at every level.”
This inevitably leads to the question of whether a business has enough in-house expertise to drive successful projects. Again, a third of the respondents to Lenovo’s survey that haven’t adopted AI cited a shortage of skills as a key challenge. Smith acknowledges that many of the most successful adopters have leaned on the expertise of outside talent to address the skills gap within their organisation, but that doesn’t address the issue of how new processes will be accepted by existing staff.
“AI deployments live or die by the quality of the people on the project,” says Smith. “There’s a couple of aspects to that. First of all, do you have the required skills internally? Do you need to look externally for talent? The second aspect is more of a soft area. Who is going to be involved with the product and actually have to use it?”
Empowering workers to achieve their maximum potential through AI will therefore require ITDMs to work closely with other senior leaders to ensure uptake throughout the organisation. Smith says chief people officers as well as chief operating officers will be needed to implement change programmes which allay any fears and put forward the positive case for AI and the greater efficiencies it will bring. It is promising to see these changes already taking place, with 65% of UK ITDMs planning or piloting AI-powered PCs in some way, and 15% extensively using them already.
“This is about change management in an organisation. It’s about winning the hearts and minds of the people who are actually going to be using the tools in the end, because everyone thinks ‘the machines are coming for our jobs’. And that’s as far away from the truth as it can possibly be,” says Smith.
The role of the ITDM has fundamentally changed. Rather than having a purely technical role, tech leaders are now enablers of human potential, with oversight of culture, recruitment, and learning and development – future-proofing their organisations and helping the entire business thrive.
“Think about how the ITDM’s role has evolved over the years,” says Smith. “They’re like a conductor in an orchestra. Before, they just made and played individual instruments. Now, they’re actually the person who stands at the front there and directs the orchestra. How are we going to get value out of all these pieces?”
Q&A: the support tech leaders need to drive AI success
Valerio Rizzo, EMEA AI lead at Lenovo, talks about why AI strategy is a shared responsibility – and the skills, collaboration and governance ITDMs need to make it happen
ITDMs will be responsible for driving change and AI adoption. How can senior leadership and the C-suite support that transition?
Senior leadership and the C-suite need to be involved early on to ensure AI adoption is a success. Success cannot purely be measured in technical metrics – IT and business leaders must work together to focus on real business benefits and measurable KPIs. For example, AI project success should be measured in terms of its impact on business process efficiency, customer experience and financial performance. To do this effectively, senior leadership needs to be closely involved to evaluate both project success and ongoing performance.
What are the key skills ITDMs will need to develop to drive this change?
AI starts with data, so skills around data management will be extremely important to any AI project. Lenovo’s research found that 33% of organisations are prioritising the development of data management, and data analytics is at the top of the list for tech investments in the coming year.
ITDMs should work closely with HR to build skills development programmes around data management. ITDMs must also promote multidisciplinary collaboration to boost AI skills development across the organisation, and also work to establish processes to measure ROI when it comes to in-house skills training.
Today, the top challenge preventing organisations from adopting AI technologies is the uncertainty around how to train staff. It’s key to move quickly to deal with this uncertainty: developing internal expertise is critical to AI success, and to scaling the technology rapidly.
What skills will ITDMs need to recruit for?
Data science and business intelligence will be the top investment priority for organisations in 2025, and those skills will be in high demand and a recruitment focus. Skills around data management, governance and cybersecurity will be crucial to any AI project, so ITDMs will have to recruit, and also work closely with professional services partners with proven AI expertise to bridge any gaps in the early stages.
When addressing this skills gap, ITDMs can also work with strategic partners with proven AI expertise like Lenovo for matters such as E2E AI advisory and deployment management services.
How can ITDMs enable line managers to facilitate greater uptake?
ITDMs should ensure that line managers are involved in decision-making and that they also have the support they need. Our research found that access to partners with strong AI capabilities, like the Lenovo AI Innovators Program, is one of the most important factors in successful AI implementation.
ITDMs should also focus on implementing AI in areas where it has a proven business impact, such as customer experience. AI can have a rapid and measurable effect by providing personalised interactions, offering instant responses to customers and even predicting customer needs based on previous data.
In particular, how can ITDMs ensure governance, risk and compliance (GRC) is seen as a key driver of success?
A culture of risk awareness and accountability is key to ensuring that GRC is seen as a driver of AI success. From biased hiring to privacy violations, AI’s pitfalls are well-documented, making governance essential. Organisations must manage bias, protect privacy, and ensure AI is accountable, reliable and transparent.
GRC isn’t optional – half of organisations in our research had established policies around AI systems’ accountability and reliability, establishing comprehensive ethical AI frameworks. It’s why, in the UK alone, improving regulatory compliance is the number one business priority this year, according to our research. Challenges remain around implementing AI GRC policies in EMEA, however, due to the complex regulatory landscape.
Despite signs of success, a number of ITDMs report some AI scepticism within their organisations. Where does the responsibility for addressing these concerns sit?
In many organisations, there is a significant divide between IT professionals and business users, with 37% of management sceptical or having reservations about AI. At the same time, nine out of 10 AI-adopting respondents said the technology had met their expectations. It’s key for ITDMs to work closely with the C-suite to establish trust in the technology. ITDMs should prioritise ‘quick win’ projects where they can demonstrate a rapid, measurable return to win over AI sceptics.
How can ITDMs lean on third-party providers to ensure AI success?
To ensure the success of AI projects, it helps to work closely with professional services partners and also strategic partners to deliver ready-made expertise and advice around AI adoption issues. Professional services partners and strategic partners often have long experience (and even sector- specific experience) in ensuring AI projects deliver results.
Strategic partners who offer ready-to-use data and technology foundations for AI services can help modernise aspects such as data management, and provide AI expertise on tap. Likewise, support from professional services can be vital. Across EMEA, 79% of organisations are either using AI professional services or planning to do so, relying on these partners for support in AI expertise, data management, security and privacy.
For more information please visit lenovo.com
The proliferation of AI-powered tools in the workplace has accelerated in the past 12 months, and the pace of adoption is only set to continue. According to 2025 IDC research commissioned by Lenovo, business leaders and IT decision-makers (ITDMs) based in EMEA expect to increase spending on AI by 104% this year, and in the UK alone, spending on AI has increased by 84% since 2024.
Lenovo’s global survey reveals that leaders in EMEA are the most satisfied compared to their counterparts in other regions, and report the highest success rate in implementing AI projects. Some 94% of AI projects undertaken in the past 12 months at least met expectations, with nearly a third (31%) exceeding the original aims. The region is also the most optimistic around AI, with 55% of management teams feeling positive about its potential.
“We’re starting to see organisations achieve AI success and maturity compared to 18 months ago,” says Greg Smith, executive director and general manager for EMEA at Lenovo Solutions and Services Group.
