Across the UK, there’s growing optimism about AI. According to new research from IDC, commissioned by Expereo, 88% of UK business leaders say AI will be necessary to fulfil business priorities over the next 12 months.
That optimism is encouraging, but it also comes with a warning. AI is moving fast, and most infrastructures aren’t keeping up. The ambition is real, but so is the risk of overreach. As CIOs, we must close the widening gap between AI ambition and operational readiness.
The pressure is growing, but so is the gap
Nearly 40% of UK tech leaders say their boards expect too much from AI, too quickly, and it’s not hard to see why. AI dominates headlines and everyone wants in. But AI isn’t magic, it requires data, clarity, cross-functional alignment, and, critically, a network foundation that can support it.
This is where most efforts stall. Moving from pilot to platform requires more than enthusiasm. It demands robust infrastructure and scalable design, combined with realistic timelines and long-term thinking.
The overlooked layer: network infrastructure
We talk about data and obsess over algorithms, but we don’t speak enough about connectivity, the invisible layer that makes or breaks real-time AI.
AI relies on processing vast volumes of data quickly, something that requires networks that are agile, secure, and globally reliable. However, 47% of UK organisations say their current network can’t support new tech like AI pointing to a fundamental barrier to progress. Without modern infrastructure, even the most promising tools cannot be deployed at scale.
49% of organisations say network performance is directly limiting their ability to roll out data-intensive or AI-led initiatives. These limitations are not just about speed — they impact the viability of use cases like predictive analytics, automation, and real-time decision-making.
Over 90% of firms with underperforming networks report experiencing direct financial losses. These may stem from outages, degraded performance, or failed deployments, all of which can have knock-on effects across the business.
This isn’t just a tech problem, it’s a strategic business bottleneck with long-term implications.
People are part of the equation
Technology alone won’t solve this issue. AI transformations are as much about people as they are about platforms.
41% of UK organisations are concerned about AI ethics and governance with many unsure how to structure accountability, ensure transparency, or manage compliance in a fast-moving field.
Additionally, 30% cite employee resistance as one of the main problems. That resistance often stems from fear, lack of clarity, or exclusion from the process and people ultimately worry about being replaced, misunderstood, or left behind.
CIOs must lead with empathy and transparency. That means honest communication, early engagement, and upskilling programmes that empower, not replace, teams. When people feel part of the journey, adoption accelerates throughout a business
Skills and partnerships: a dual challenge
Many organisations lack the internal capability to implement AI at scale. 29% say their partners aren’t equipped either. That double gap puts pressure on both leadership and procurement to rethink who they work with — and how.
As AI becomes more embedded into day-to-day business operations, companies are shifting from tool acquisition to strategic partnerships. The right combination of partners brings technical depth, a long-term mindset, and the ability to operate in complex hybrid environments.
This shift is critical. We’re co-creating AI-capable, resilient, and future-proof infrastructure. That takes more than procurement — it takes trust, collaboration, and shared accountability.
The new spotlight on CIOs
There is good news. AI is elevating the role of the CIO.
76% of UK CIOs now have a more substantial presence at board level. This visibility reflects the growing recognition that technology is not a support function — it is central to strategy, performance, and innovation.
That visibility comes with responsibility. We must ground expectations in reality by clearly communicating what AI can and cannot do in the short term. We must highlight the infrastructure gaps that will limit delivery if left unaddressed. And we must advocate for foundational investments, especially in network readiness, which is too often overlooked in transformation plans.
And most importantly, we must guide our organisations from AI experimentation to operationalisation — at scale, with intent, and with resilience.
Final thoughts: it starts with the basics
AI will transform how we run our businesses. But success requires more than strategy decks and pilot projects. It demands action.
That means investing in modern networks — not just fast ones, but secure, scalable and adaptable to growing demands. It means having clear execution plans that go beyond experimentation and it means building alignment across teams, ensuring people are engaged and supported at every stage.
The ambition is there. But without the right foundations — especially in infrastructure — AI remains an expensive idea, not a competitive advantage.
The job of the CIO now is to bridge that gap. Because without solid ground to build on, even the most brilliant AI won’t stand.
The 2025 Enterprise Horizons report are findings from an IDC InfoBrief, commissioned by Expereo*
