Akamai’s new research report, The State of AI Inference, identifies a critical infrastructure gap where 50% of production AI deployments struggle to maintain latency at scale. The study reveals that while AI inference has moved into business-critical use cases, centralized cloud architectures have created a latency wall that prevents organizations from scaling effectively. Read the report to learn more.
- Learn about the latency wall: 64% of organizations require sub-250 ms response times for their top use cases, yet centralized systems remain a primary bottleneck to performance.
- Discover proximity requirements: 60% of practitioners acknowledge that running inference closer to end users is critical for production success, though 46% remain tethered to single-cloud regions.
- Navigate scaling challenges: 50% of teams cite latency at peak load as their top scaling constraint, forcing a move toward automated traffic steering and distributed compute.
Download the full report for more details about the infrastructure challenges AI practitioners are facing today.