Cloud Dominates AI Deployment as Developers Leverage Scalable Environments
A new analysis from the Evans Data Corporation’s Worldwide
Developer Population & Demographic Study 24.2 reveals that cloud
infrastructure is the most commonly used environment for AI and machine
learning (ML) projects, with nearly 9.7 million developers worldwide deploying
their AI workloads in the Cloud. This makes cloud computing the top choice for
AI development, surpassing on-premises servers, data centers, and edge
computing.
"The cloud has become the backbone of AI development,
offering the scalability and processing power necessary for complex machine
learning models," said James Owen, Director of Research at Evans Data
Corporation. "However, strong adoption of on-premises and data center
solutions highlights that developers continue to weigh factors like security,
latency, and infrastructure control in their deployment decisions."
Asia-Pacific (APAC) are strong adopters of AI and this
extends to AI cloud adoption. Roughly twice as many developers in APAC run
projects in the Cloud compared Europe, the Middle East, and Africa (EMEA),
although APAC's developers are also more likely than those in EMEA to develop
AI projects, in general. APAC and EMEA demonstrate strong cloud adoption,
though on-premises servers and data centers remain highly utilized in these
regions. North America and Latin America each show strong cloud AI adoption as
a proportion of their total developer populations with more than half of the AI
developers in each region leveraging the Cloud for their AI workloads.
As AI adoption continues to accelerate, understanding where
developers are running their projects is crucial for cloud providers,
enterprises, and technology decision-makers looking to align their
infrastructure strategies with industry trends.
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