DE-CIX Research Reveals Cloud Connectivity Issues Are Slowing AI Adoption
Nearly all enterprises believe their networks are AI-ready. New DE-CIX research tells a different story: IT teams average 11.5 hours a week resolving cloud connectivity issues, and 61% of enterprises have already turned to private connectivity to clouds. The article covers the findings and what direct interconnection through Cloud and AI Exchanges changes for latency, resilience, and security. Read it to see where connectivity is slowing AI work, and talk to us about your environment.
Why are cloud connectivity issues slowing down AI adoption?
On paper, most enterprises feel prepared for AI, but the network reality looks different.
According to DE-CIX research across 400 IT and infrastructure decision makers in the US and UK, 96% of respondents are confident their networks can support future cloud and AI initiatives. Yet, IT teams still spend an average of 11.5 hours every week resolving cloud connectivity problems. Nearly half (49%) spend more than 10 hours per week troubleshooting.
The main issues getting in the way of AI adoption are:
- Downtime and reliability problems (cited by 26% of respondents)
- Latency and slow performance between cloud environments (28%)
- Security vulnerabilities and DDoS attacks (27%)
As organizations move to complex multi-cloud setups, they need data to move quickly and predictably between users, applications, clouds, and AI infrastructure. When connectivity is unreliable or slow, AI workloads underperform, projects stall, and IT teams are pulled away from strategic work to firefight network issues.
In short, businesses are investing heavily in GPUs, data centers, and AI platforms, but many have not yet fully addressed the network layer that ties all of this together. That gap is what slows AI adoption in practice.
What are the biggest cloud connectivity challenges for enterprises today?
Enterprises are dealing with a mix of technical, regulatory, and operational connectivity challenges as they scale cloud and AI.
From the DE-CIX study, the most significant issues include:
- Data sovereignty and geopolitics: Almost 23% of respondents see this as their top cloud connectivity challenge for the next 12 months. As regulations evolve and geopolitical risks rise, organizations need tighter control over where data is stored, processed, and moved.
- Downtime and reliability: 26% cite outages and reliability issues as a key concern, which directly impacts application availability and user experience.
- Latency between cloud environments: 28% struggle with slow performance between clouds, which is especially problematic for distributed AI workloads and data-intensive applications.
- Security and DDoS risks: 27% highlight security vulnerabilities and DDoS attacks as major connectivity challenges.
- Cost, skills, and visibility: Respondents also point to the cost of connectivity, limited staff expertise, and lack of visibility and control over data flows in multi-cloud environments.
The operational impact is significant. On average, IT teams spend 11.5 hours per week resolving connectivity issues, and more than a third of organizations report spending between 11 and 20 hours weekly. Just under one in ten spend between 21 and 40 hours per week on these problems.
Every hour spent troubleshooting is an hour not spent on higher-value work such as AI enablement, cloud modernization, security hardening, or improving user experience. This is particularly challenging for smaller and mid-sized enterprises, which often have leaner teams but face similar levels of complexity.
How can private interconnection and Cloud & AI Exchanges help?
Private interconnection is becoming a key way for enterprises to reimagine how they connect to cloud and AI services.
Instead of sending traffic over the public Internet, private interconnection lets you connect directly to cloud providers over dedicated infrastructure. The DE-CIX research shows that:
- 61% of companies already use private cloud connectivity
- Another 31% are actively considering deploying it
- 71% of large enterprises (1,000+ employees) use private connectivity, compared with only 31% of medium-sized firms (100–249 employees)
This shift is driven by the need for:
- Lower latency and more predictable performance for AI and data-intensive workloads
- Greater resilience and reduced downtime risk
- Enhanced security by reducing exposure to the public Internet
- Better control over data flows, locations, and compliance requirements
Cloud and AI Exchanges, such as those operated by DE-CIX, help enterprises:
- Centralize connectivity to multiple cloud and network partners from a single platform
- Reduce reliance on best-effort Internet paths by using direct, private routes
- Gain visibility through service monitoring and traffic insights
- Simplify multi-cloud management and cloud-to-cloud connectivity
DE-CIX’s Cloud Exchange, for example, offers private connectivity to all major global cloud providers plus many regional and specialist ones. In practical terms, this helps IT teams spend less time diagnosing fragmented routes and unpredictable performance, and more time ensuring AI and cloud workloads behave as the business expects.
For many organizations, especially those investing heavily in AI and data center infrastructure, optimizing interconnection is becoming a core part of their cloud and AI architecture—and a way to reduce the operational burden on IT teams.

DE-CIX Research Reveals Cloud Connectivity Issues Are Slowing AI Adoption
published by Westwood Associates Ltd
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