New research from Akamai Technologies reveals that businesses across Europe are facing rising cloud infrastructure costs and are struggling to realise value from AI investments, with a ‘significant disconnect’ between cloud and AI spending and the ability to measure tangible returns.
It also shows that businesses are making cuts to their AI, cybersecurity, and IT staffing budgets to accommodate growing cloud costs.
According to Akamai’s findings in the Opinium report, polling 750 IT decision makers in the UK, France and Germany responsible for cloud software & infrastructure and/or AI applications, only 35% of EMEA businesses stay with their current cloud provider because they are satisfied and see no need to explore alternatives.
Research also found that 67% expect cloud costs to rise over the next year, with 42% anticipating increases of more than 10%. Cloud storage, analytics (39%), and AI-related services (37%) were the top factors behind the increased spending.
Despite the anticipated cost rises, two in five say that the cost and complexity of migrating data and applications outweigh the potential benefits of switching providers.
Over two-thirds (68%) of businesses are finding that increasing cloud costs are translating into less budget for other areas. As cloud spending accelerates due to the growing demands of AI, businesses are under pressure to reduce costs in other areas, with new AI projects (26%), cybersecurity (26%), and IT staff costs (24%) among the most frequently cited cutbacks. These trade-offs prompted one in five businesses to brand their cloud computing costs as “unmanageable.”
James Kretchmar, Global CTO, Cloud Technology at Akamai Technologies (pictured) said: “Cloud spending is growing fast and it’s holding businesses back from investing in growth and innovation, especially with AI, where businesses are struggling to squeeze ROI out of their investments.
“Against this backdrop, cloud hyperscalers continue with contract lock-in and egress pricing, which means keeping cloud costs under control is impossible for many.”
AI ambition is high, with 65% of businesses expecting to increase AI investment in the next 12 months. However, nearly 85% have not implemented a strategy for tracking return on investment (ROI) for their AI projects, with only 11% reporting their AI projects self-sustaining through cost or productivity gains.
And just a quarter report having budgets that fully support their desired AI initiatives.
Kretchmar continued: “Leaders need to take a hard look at where they’re spending and what outcomes they expect. Companies must prioritise the quality of outcomes, looking beyond the legacy cloud providers to those architected for performance-sensitive applications like inference.”
AI inference plays a critical role in automation, real-time decision-making and predictive analytics across a range of industries and applies this learning to new data in real time.
Running AI inference at the edge reduces latency and enables scalable, efficient execution avoiding dependence on centralised cloud platforms, and it is essential to shift computing workloads from the cloud to the edge.
Akamai is supporting organisations in moving beyond traditional cloud models and achieving greater efficiency and value from their AI strategies.