Akamai research finds rising cloud costs putting brakes on AI innovation

Businesses across Europe are encountering escalating cloud infrastructure costs, complicating efforts to realize value from their AI investments. According to new research from Akamai Technologies, this disparity is evident in the gap between spending on cloud and AI, and the measurable returns from such investments.

Data shows that only 35% of EMEA businesses remain loyal to their current cloud providers due to satisfaction, without exploring alternatives. However, a notable 67% expect cloud costs to climb over the next year, with 42% projecting increases exceeding 10%. The top drivers for this increased expenditure include cloud storage, analytics (39%), and AI-related services (37%).

Over two-thirds (68%) of businesses face the impact of rising cloud costs, forcing them to reduce budgets in other critical areas. As cloud spending stemming from AI grows, cost-saving measures see cutbacks in new AI projects (26%), cybersecurity (26%), and IT staffing (24%). A fifth of businesses label their cloud expenses as "unmanageable."

James Kretchmar, Akamai's Global CTO for Cloud Technology, noted how explosive cloud spending hampers businesses from investing in potential growth areas, particularly AI, where deriving ROI remains a challenge. He highlighted issues such as contract lock-in and pricing strategies by cloud hyperscalers that exacerbate cost management difficulties.

The AI landscape continues to grow with 65% expecting increased AI expenditure over the coming year. Unfortunately, effective execution lags, with the majority investing without a defined strategy or ROI framework. A staggering 82% lack a tracking strategy for AI ROI, and only 11% find their AI projects self-sustaining. Additionally, 25% report inadequate budgets to support AI initiatives.

AI inference emerges as the fastest-expanding facet of artificial intelligence, playing a pivotal role in automation and real-time analytics. Businesses are now adopting distributed, edge-native architectures to handle computing demands efficiently and circumvent reliance on centralized cloud platforms. Running AI inference at the edge optimizes outcomes, aligning technology investments with operational objectives.

Shifting computing workloads from the cloud to the edge is crucial. Akamai's expansive cloud infrastructure aids organizations in transcending traditional cloud models, achieving enhanced efficiency and value.

Key insights

• Only 14% are delving into advanced AI applications or believe they've fully embraced AI business-wide.
• Due to geopolitical tensions, 67% seek cloud providers with robust data sovereignty.
• EU AI Act considerations prompt 57% to prioritize AI governance and compliance investments.