UK businesses stand at a major crossroads in the accelerating race toward enterprise AI transformation. With sweeping optimism about the potential of artificial intelligence to redefine productivity, competition, and work itself, British organisations are largely unified in their intent to embed AI tools and agents into their everyday operations. Yet, beneath this tide of ambition, a new Microsoft-commissioned study has surfaced a striking disconnect: despite their enthusiasm, most companies are not investing with the urgency required to upgrade ageing device infrastructure, jeopardizing their ability to fully capitalize on the AI opportunity.
This finding forms the crux of Microsoft’s "Built for Impact" research report, released as part of the 2025 Work Trend Index, which drills into the readiness of UK workplaces to adapt for AI at scale. The data, drawn from recent surveys of UK business IT decision-makers (ITDMs) and enterprise employees, reveals not only the scale of the challenge but also the steps that organisations must take to avoid losing ground at one of the most pivotal moments in digital transformation.
The 2025 Work Trend Index could hardly paint a clearer picture of intent: 82% of UK business leaders now recognize the next 12 to 18 months as a "pivotal year" for AI adoption, and more than 8 out of 10 expect to have advanced AI agents and tools embedded within critical business processes by the end of 2026. It is a vision shared across geography, industry, and function, with almost every sector—from financial services to healthcare—betting big on machine learning, natural language processing, and automated insights to elevate both productivity and customer experience.
Yet, as the report warns, ambition alone is no substitute for action. More than half of IT leaders (58%) surveyed are actively calling on their organisations to invest in new devices that can enable seamless access to AI tools, but only 46% are currently taking AI-readiness into account when making hardware decisions. This gap is not simply theoretical: it is already manifesting in day-to-day frustrations for employees and measurable impacts on business agility.
This is borne out by survey data: a majority of UK IT leaders (54%) say that employee productivity and performance is now the top driver in hardware refresh cycles, eclipsing traditional factors like cost minimization. Yet ironically, 53% of UK employees state their current devices aren’t even fully equipped to support hybrid working, let alone the next wave of AI-driven workflows. It’s a recipe for frustration, inefficiency, and lost opportunity.
Perhaps more tellingly, a quarter (24%) of ITDMs admit that opting for cheaper, lower-spec hardware in the past caused higher long-term costs through device failures, inefficiencies, or costly workarounds. By contrast, 40% report that investing in premium, AI-ready devices has led to directly improved business outcomes, including measurable gains in agility, innovation, and data security.
This disconnect raises two high-stakes questions: how can UK organisations close the gap—and what are the risks if they don’t?
The risk of inaction, the report suggests, is not just missing out on technological innovation but permanently ceding ground to more agile, better-equipped competitors—both at home and internationally.
It also means rigorous vendor selection, with clear criteria for device longevity, upgrade paths, and compatibility with leading AI platforms—Microsoft Copilot, OpenAI-powered tools, or sector-specific solutions. Industry analysis from Gartner and Forrester supports Microsoft’s stance: organisations that delay these investments are likely to face compounding costs down the line, including productivity slowdowns, increased security risks, and a diminished ability to deploy cutting-edge software.
To stay close to the innovation curve, the report advocates for flexible procurement via staggered upgrades, leasing, or device-as-a-service (DaaS) models. Such approaches let organisations incrementally refresh at-risk device stock while retaining capital flexibility—a crucial consideration with economic headwinds and budget constraints top-of-mind for many UK CIOs.
This thinking is increasingly echoed throughout the tech industry, as echoed by recent HP and Dell channel studies showing a growing shift toward hybrid refresh cycles and device subscription models—particularly in scale-up and enterprise environments where AI-readiness cannot be compromised.
Measurement is essential—not only to demonstrate return on investment but to guide future procurement and skills development. Ongoing analytics, feedback loops, and visible, trackable progress ensure that AI transformation becomes a repeatable, scalable capability, not just a one-off project.
Microsoft’s research, supported by independent analyses from market research leaders such as YouGov and Gartner, is clear—in the coming AI revolution, device readiness will be as fundamental as cloud strategy or cybersecurity posture. The urgency is matched only by the potential upside: energised, secure, and AI-enabled workforces, positioned to thrive in a radically transformed competitive landscape.
The principles are widely applicable. Whether through direct investment in AI-optimized laptops, tablets, and workstations, adoption of DaaS models, or accelerating skills and culture initiatives, the window for action is now. As Alan Slothower puts it, “AI is here and organisations across the UK are investing in its potential. These strategies must include hardware… It’s important IT leaders act now to ensure their organisations are set up for success.”
For IT leaders, procurement professionals, and business strategists, the lesson is clear: the time to act is now, not later. Those who do will gain outsized returns—faster productivity, greater resilience, sharper security, and a culture primed for ongoing digital disruption. Those who don’t risk falling permanently behind, struggling to run next-generation workloads on last-generation devices.
In the AI-powered future, device investment is not just an IT question—but a core element of strategic leadership, talent management, and innovation. UK businesses, and their global peers, have a rare window to define the next decade of work. The onus, and opportunity, is theirs to seize.
Source: Microsoft AI momentum at risk as UK businesses overlook device readiness, research reveals - Source EMEA
This finding forms the crux of Microsoft’s "Built for Impact" research report, released as part of the 2025 Work Trend Index, which drills into the readiness of UK workplaces to adapt for AI at scale. The data, drawn from recent surveys of UK business IT decision-makers (ITDMs) and enterprise employees, reveals not only the scale of the challenge but also the steps that organisations must take to avoid losing ground at one of the most pivotal moments in digital transformation.
The AI Opportunity: Vision, Hype, and the Reality Check
The 2025 Work Trend Index could hardly paint a clearer picture of intent: 82% of UK business leaders now recognize the next 12 to 18 months as a "pivotal year" for AI adoption, and more than 8 out of 10 expect to have advanced AI agents and tools embedded within critical business processes by the end of 2026. It is a vision shared across geography, industry, and function, with almost every sector—from financial services to healthcare—betting big on machine learning, natural language processing, and automated insights to elevate both productivity and customer experience.Yet, as the report warns, ambition alone is no substitute for action. More than half of IT leaders (58%) surveyed are actively calling on their organisations to invest in new devices that can enable seamless access to AI tools, but only 46% are currently taking AI-readiness into account when making hardware decisions. This gap is not simply theoretical: it is already manifesting in day-to-day frustrations for employees and measurable impacts on business agility.
Devices in the AI Era: Why Hardware Matters More Than Ever
One of the clearest lessons from the study is that the right device infrastructure forms the essential platform for any credible AI strategy. AI workloads are demanding; natural language models, computer vision algorithms, and real-time analytics often require significant on-device processing power, secure silicon, and optimized connectivity. Relying on legacy hardware, especially devices lacking modern neural processing units (NPUs) or advanced security from chip to cloud, represents a serious competitive risk.This is borne out by survey data: a majority of UK IT leaders (54%) say that employee productivity and performance is now the top driver in hardware refresh cycles, eclipsing traditional factors like cost minimization. Yet ironically, 53% of UK employees state their current devices aren’t even fully equipped to support hybrid working, let alone the next wave of AI-driven workflows. It’s a recipe for frustration, inefficiency, and lost opportunity.
Perhaps more tellingly, a quarter (24%) of ITDMs admit that opting for cheaper, lower-spec hardware in the past caused higher long-term costs through device failures, inefficiencies, or costly workarounds. By contrast, 40% report that investing in premium, AI-ready devices has led to directly improved business outcomes, including measurable gains in agility, innovation, and data security.
A Growing "Ambition-Action" Gap
What the report reveals is a classic ambition-action gap. Business leaders and IT strategists are nearly unanimous in their belief that AI-enabled tools are now core to competitive advantage. In fact, 56% of ITDMs surveyed say AI is essential to future organizational success, with 57% highlighting its key role in boosting employee productivity. However, the inertia of slow hardware refresh cycles, inflexible procurement models, and limited organisational bandwidth threatens to stall these ambitions.This disconnect raises two high-stakes questions: how can UK organisations close the gap—and what are the risks if they don’t?
From Can We Afford To Upgrade To Can We Afford Not To?
According to Alan Slothower, Head of Surface Commercial at Microsoft UK, the dilemma is as much cultural and leadership-focused as it is technological. “While many organisations see the opportunity, too few are moving fast enough to equip their people with devices built for the era of on-device AI. If they haven’t already, enterprise hardware conversations must shift from ‘can we afford to upgrade?’ to ‘can we afford not to?’” This reflects a growing realisation that future-proofing is no longer an option, but a basic necessity for survival in an AI-first landscape.The risk of inaction, the report suggests, is not just missing out on technological innovation but permanently ceding ground to more agile, better-equipped competitors—both at home and internationally.
Critical Recommendations: Turning Ambition Into Action
The research outlines three essential priorities for UK IT decision-makers looking to bridge the gap between AI ambition and tangible results:1. Select AI-Optimised Hardware
The first step is clear: equip teams with devices that are purpose-built for contemporary AI workloads. This means prioritising machines with built-in NPUs (neural processing units), advanced silicon-to-cloud security, and clear update and support trajectories. The shift here is from incremental upgrades to transformational procurement—choosing platforms designed from the ground up for secure, high-performance AI, not merely retrofitted to support add-on features.It also means rigorous vendor selection, with clear criteria for device longevity, upgrade paths, and compatibility with leading AI platforms—Microsoft Copilot, OpenAI-powered tools, or sector-specific solutions. Industry analysis from Gartner and Forrester supports Microsoft’s stance: organisations that delay these investments are likely to face compounding costs down the line, including productivity slowdowns, increased security risks, and a diminished ability to deploy cutting-edge software.
2. Rethink Device Refresh Cycles
The velocity of AI innovation leaves little room for the multi-year hardware replacement strategies of the past. As Ben Coley, Senior Surface Global Black Belt at Microsoft UK, notes, “IT leaders should ground conversations about hardware procurement in tangible outcomes…AI-enabled devices lower total cost of ownership, energise a diverse, innovation-ready workforce, and protect enterprise data.”To stay close to the innovation curve, the report advocates for flexible procurement via staggered upgrades, leasing, or device-as-a-service (DaaS) models. Such approaches let organisations incrementally refresh at-risk device stock while retaining capital flexibility—a crucial consideration with economic headwinds and budget constraints top-of-mind for many UK CIOs.
This thinking is increasingly echoed throughout the tech industry, as echoed by recent HP and Dell channel studies showing a growing shift toward hybrid refresh cycles and device subscription models—particularly in scale-up and enterprise environments where AI-readiness cannot be compromised.
3. Invest in Skills and Measured Insights
Purchasing AI-ready hardware is only the beginning. To unlock real value, organisations must invest in the skills, training, and cultural frameworks that encourage employees to adopt, experiment with, and scale new AI-powered workflows. This includes role-specific AI education, accessibility support, and a process for tracking usage to identify early successes and potential bottlenecks.Measurement is essential—not only to demonstrate return on investment but to guide future procurement and skills development. Ongoing analytics, feedback loops, and visible, trackable progress ensure that AI transformation becomes a repeatable, scalable capability, not just a one-off project.
Risks of Falling Behind: The Productivity and Competitiveness Imperative
The implications of failing to close the device-readiness gap are unambiguous. As the report highlights, organisations running advanced AI workloads on legacy or underpowered hardware are likely to experience:- Reduced productivity, as employees grapple with slow or incompatible devices, preventing seamless use of generative AI, automation toolchains, or collaboration software.
- Elevated security risks, as legacy hardware often lacks the low-level protection demanded by modern threat landscapes.
- Increased long-term costs, as breakdowns, inefficiencies, and costly workarounds outweigh the “savings” achieved through deferred investment.
- Erosion of competitive edge, as faster-moving competitors can unlock innovation at scale, capitalizing on AI’s network effects and ecosystem benefits.
Best Practice: Putting It All Together
Translating these findings into practical action, the report recommends that UK ITDMs and business leaders:- Conduct device audits focused specifically on AI-readiness, not just age or cost.
- Set minimum hardware standards for new device procurement, anchored in the requirements of the most critical AI workloads.
- Embrace modular, flexible refresh strategies tailored to each department’s AI ambitions and risk profile.
- Establish comprehensive AI upskilling programmes, with progress tracked by both employee engagement and tangible business outcomes.
- Make data-driven decisions, using device and AI usage analytics to inform future cycles and maximise ROI.
Looking Ahead: Seizing the AI Moment in the UK
The call to action is stark but loaded with opportunity. With average hardware refresh cycles meaning that many of the devices bought in 2025 will remain on desks into 2029, organisations face an immediate, non-deferrable choice: invest in an infrastructure ready for the AI era, or risk being left behind as a next-generation digital workforce emerges.Microsoft’s research, supported by independent analyses from market research leaders such as YouGov and Gartner, is clear—in the coming AI revolution, device readiness will be as fundamental as cloud strategy or cybersecurity posture. The urgency is matched only by the potential upside: energised, secure, and AI-enabled workforces, positioned to thrive in a radically transformed competitive landscape.
The principles are widely applicable. Whether through direct investment in AI-optimized laptops, tablets, and workstations, adoption of DaaS models, or accelerating skills and culture initiatives, the window for action is now. As Alan Slothower puts it, “AI is here and organisations across the UK are investing in its potential. These strategies must include hardware… It’s important IT leaders act now to ensure their organisations are set up for success.”
Final Thoughts: Beyond Hype, Toward Sustainable AI Success
The ambition for AI transformation in UK business is genuine, far-reaching, and fast-moving. But the research is an unambiguous warning: bold intentions must be matched by decisive investment in the physical tools that make digital innovation feasible. Device readiness is not a "nice-to-have"—it is the indispensable foundation of all that the AI era promises.For IT leaders, procurement professionals, and business strategists, the lesson is clear: the time to act is now, not later. Those who do will gain outsized returns—faster productivity, greater resilience, sharper security, and a culture primed for ongoing digital disruption. Those who don’t risk falling permanently behind, struggling to run next-generation workloads on last-generation devices.
In the AI-powered future, device investment is not just an IT question—but a core element of strategic leadership, talent management, and innovation. UK businesses, and their global peers, have a rare window to define the next decade of work. The onus, and opportunity, is theirs to seize.
Source: Microsoft AI momentum at risk as UK businesses overlook device readiness, research reveals - Source EMEA
