AI Drives UK Cloud Strategy: 88% Prioritise Adoption, 81% Skills Gap, 98% Plan More Cloud Spend

AI Is Steering UK Cloud Strategy - And Exposing the Top Skills Gap

New data from Red Hat shows a decisive shift: 88% of UK IT leaders are prioritising AI readiness in the next 18 months. This focus sits alongside cloud-native development and evolving cloud strategy, cited by 89% of respondents. The bet is clear: AI will be the next source of value in cloud.

At the same time, 98% of UK IT managers see clear advantages in enterprise-supported open-source AI, led by faster innovation and cost efficiency. The market wants flexibility without losing control.

What Executives Need to Know Now

• 88% of UK firms rank AI adoption as a top priority for the next 18 months.
• 80% prioritise centralised cloud management; 78% focus on security, compliance and sovereignty.
• 96% say siloed teams slow cloud adoption - a direct risk to AI delivery.
• 81% report an urgent skills gap in AI, data science, LLMs and generative AI.
• 98% favour enterprise-supported open-source AI for transparency, speed and cost control.

Why AI Readiness Tops the Cloud Agenda

Centralising management (80%) and tightening security (78%) are viewed as essential. But the need to prepare for AI is now a top driver at 77%, nearly matching the 88% who have already prioritised it in their roadmap.

Hans Roth, Senior Vice President and General Manager EMEA at Red Hat, emphasises transparency and explainability for enterprise-ready AI. Open source is seen as a practical path to achieve both speed and governance.

The Execution Risk: Silos and Governance

Organisational silos are the most cited obstacle: 96% say fragmented teams hinder cloud adoption. That creates inconsistent controls, duplicated costs and slow delivery.

Leaders are pushing for transparent, auditable models and clear oversight. The goal: ship AI use cases without losing visibility or control.

The 81% Skills Gap - And What to Do About It

The skills gap is widening: 81% report shortages in AI, data science, LLMs and generative AI, up from 72% last year. Cybersecurity is flagged by 75%, and 68% see a shortage in strategic thinking to translate tech into business results.

Only 25% believe they have the right platforms and skills to fully use AI today. 40% say they have scalable platforms but lack talent. Another 35% need new platforms, 22% of whom are already seeking to acquire them.

• Run a 30-day skills audit across data, ML engineering, MLOps, cybersecurity and product leadership.
• Define 2-3 high-value use cases tied to revenue, cost or risk; assign clear owners.
• Stand up a central enablement model: platform engineering, security, data, and model ops as shared services.
• Launch targeted upskilling and certification paths; supplement with partners where gaps persist.
• Set quarterly metrics: time-to-deploy, model performance, compliance findings, and value delivered.

To speed up capability building, explore role-based programs and certifications. See AI courses by job and popular AI certifications.

Why Enterprise Open Source Is Winning

Enterprise-supported open-source AI is gaining traction: 53% say it accelerates innovation, 50% cite cost efficiency, and 43% value trust and transparency. Leaders want choice without losing support.

• Transparent, modifiable models with explainable sources: 89%
• Proven performance and reliability: 85%
• Model indemnification: 84%
• Compliance with data privacy and security standards: 83%
• Accessibility across teams: 83%
• Cost-effectiveness: 82%
• Preference for domain-specific models over generic LLMs: 79%

Jo Hodgson, UK Country Manager at Red Hat, highlights the need for choice, flexibility and collaboration across tools, vendors and clouds. The open-source community provides momentum, while enterprise support de-risks adoption.

Investment Outlook for 2025

Cloud remains non-negotiable: 98% of UK IT managers prioritise cloud investment for 2025. Half plan a balanced approach between new tech and enhancements; 26% will lean into innovation; 14% will focus on essentials.

Yet silos bring real costs. Among affected firms, 54% report inconsistent security and compliance across providers, 47% see increased costs, and 42% lack control and visibility over resources.

Action Checklist for CIOs and CTOs

• Establish a single cloud platform strategy with centralised policy, identity and observability.
• Adopt an enterprise-supported open-source AI stack for transparency, portability and support.
• Create a model governance framework: data lineage, risk assessment, approvals, and monitoring.
• Prioritise domain-specific models where context matters; avoid one-size-fits-all LLMs for critical workflows.
• Close the skills gap with targeted training, partnerships and selective hiring tied to defined use cases.
• Tie AI programs to P&L: measure impact on growth, margins and risk reduction every quarter.

Method at a Glance

Survey of 609 IT managers across the UK, France, Germany, Italy, Spain and the UAE. Respondents work in organisations with 500+ employees. Fieldwork ran 15-23 August 2024 and followed the Market Research Society's code of conduct.

For reference, see the MRS Code of Conduct.