Risk management is planned for 73% of future edge AI implementations.

60% report moderate budget increases of up to 25% in Edge AI.

High operational and maintenance costs of Edge AI are a challenge for 40%.

Multimodal AI is the most commonly deployed AI model at the edge (60%).

Most organizations (54%) report that edge AI complements their cloud AI strategy for a hybrid approach

30% are reporting significant budget increases of 25% or more in Edge AI.

77% of CIOs with deployed edge AI solutions focus on risk management applications.

97% of CIOs have Edge AI either already deployed or on their roadmap.

34% of organizations are testing with plans to deploy AI at the edge within the next 24 months.

30% of organizations have fully deployed AI at the edge.

In retail, CIOs reported higher adoption of multimodal AI (68%).

Finding the right technology vendors and partners of Edge AI is a challenge for 37%.

Larger businesses (500+ employees) are more aggressive, with 39% reporting significant budget increases in Edge AI compared to 23% of mid-sized organizations (250-500 employees).

Multimodal AI is widely deployed in the cloud (59%).

LLMs see somewhat less adoption at the edge (47%).

In retail, CIOs reported lower interest in edge-deployed LLMs (32%).

Security risks and data protection concerns represent the biggest Edge AI implementation challenge (42%).

Only 3% of CIOs report no current plans to implement Edge AI.

22% of organizations are actively in production with limited deployment of AI at the edge.

Large Language Models (LLMs) are widely deployed in the cloud (59%).