When organisations begin planning for AI-enabled workflows, one question is overlooked far too often.
Are employee devices capable of handling the volume, quality and speed of data that modern, AI-driven tools depend on?
Cutting corners on PC specifications can appear like a simple way to protect a capital budget. In practice, especially in data-intensive and AI-accelerated environments, the low-cost device becomes the most expensive choice available.
At Rio, we see the same pattern across our clients.
Businesses that define and enforce a minimum PC standard, supported by disciplined refresh cycles, manage their data more effectively, experience fewer failures, deliver stronger securityand are far better prepared to adopt AI at scale.
What counts as an AI-ready minimum standard PC?
Setting a minimum standard does not mean investing in premium hardware. It means establishing a consistent baseline that ensures every device can handle the data load created by your applications, workflows and AI tools.
This ensures each employee has a device capable of processing, storing and transmitting the data their role depends on.
An AI-ready minimum standard PC typically includes:
- A current-generation CPU capable of supporting data-intensive AI applications
- Enough RAM and SSD capacity to support 3 to 4 years of growth in software and AI feature demand
- Business-grade warranty and support which reduces risk during periods of rapid AI adoption
- Hardware-level security features that protect data at the device level
- The ability to run modern OS builds required for AI copilots, automated patching and EDR tools
No employee should be blocked halfway through the lifecycle of their device by underpowered hardware or storage limitations that disrupt data flow and performance.
Intel’s TCO analysis of more than 90,000 PCs found that the optimal refresh point is around 3.5 years. This reflects failures, support overhead and downtime in addition to purchase price.
As devices age, their ability to handle data reliably begins to drop. Out-of-warranty repairs increase sharply year on year.
In AI-enabled organisations, where every workflow generates more data and requires more processing capability, under-specified devices hit these limits even faster.
Why cheaper PCs erode ROI in an AI world
Cheaper or consumer-grade PCs erode ROI in three main ways, each magnified by increasing AI-driven data demand.
Downtime and disruption
Downtime becomes extremely costly because every interruption affects data movement, data access and the AI tools that depend on them.
Research from Databarracks shows the average cost of an IT downtime incident for UK SMEs is £212,000, with some organisations losing up to £300,000 per hour. New Relic’s 2025 findings show outages for UK and Irish firms now reaching 1 to 3 million pounds per hour.
A low-cost laptop that fails twice in a year can create more financial damage in one incident than the entire cost difference of a well-specified business-grade device.
As AI workflows expand, automation, copilots and real-time analytics all rely on uninterrupted data processing. Every disruption becomes more costly.
Security exposure at the endpoint
AI increases the volume and movement of data across systems. This raises the stakes on securing that data.
IBM puts the average UK data breach cost at £3.58 million, with costs increasing each year.
In 2025, one third of UK and US small businesses still relied on free consumer-grade security, and 23 percent had no endpoint protection at all.
Minimum standard PCs make it possible to enforce:
- Full disk encryption
- Modern OS builds
- Hardware-backed security such as Trusted Platform Modules and secure boot
- Reliable patching
- Enterprise-grade EDR tools
A mix of older and consumer devices cannot deliver consistent data protection. As AI systems broaden the attack surface, the device standard you set becomes a core part of your data governance model.
Hidden productivity loss
Intel’s study of mobile and wireless PCs found that devices with stronger specifications delivered more than 5 percent savings per week, equivalent to around £3,200 of value per employee over three years.
Devices that fall below minimum standards create significant productivity loss in data-intensive teams, especially when AI is involved. This can look like:
- Sales teams waiting for AI-assisted CRM data to load
- Analysts facing freezes when models or spreadsheets get large
- Developers losing hours to patch failures and reboot loops
- Employees abandoning AI tools because their device is struggling to cope
These losses do not appear on the P&L. Yet they erode performance, margins and morale at the exact moment the organisation is trying to harness data to improve outcomes.
Why cutting corners costs more
From a board perspective, the question is not whether to buy cheaper PCs. It is what ongoing cost and operational risk they introduce as AI workloads increase.
Minimum standard, AI-ready PCs protect ROI because they:
- Reduce unplanned downtime in high-value roles
- Lower lifetime support and engineering effort
- Enable consistent security controls required for insurers and regulators
- Keep employees productive through the full refresh cycle
- Ensure the organisation can use AI tools without data or hardware bottlenecks
The cost difference between a bargain device and a well-specified business PC is tens of pounds per user per month. The downside of outages, breaches or productivity loss can reach hundreds of thousands to millions.
With a long-term view, investing in minimum spec, AI-ready devices is an obvious decision.
The takeaway for business leaders
If AI is on your agenda, its foundation matters. AI relies on fast, clean, secure data. Without devices that manage that data well, the organisation cannot realise the benefits.
We recommend all leaders:
- Set and enforce a minimum PC standard
- Align it to a 3-to-4-year refresh model
- Measure total cost of ownership, not unit price
- Ensure your estate can support the AI tools you intend to deploy
The cheapest way to run your devices is rarely the cheapest device.
This becomes even more true as organisations become more data-driven and rely more heavily on AI to drive efficiency and growth.
Invest in infrastructure that supports your business goals today and tomorrow, rather than devices that simply appear to reduce cost in the short term.
To learn more about Rio’s data-first approach to infrastructure, and how we help organisations better monitor, manage and choose devices, click here.