Delivering Faster, Smarter AI Without Vendor Lock-In - 19 de marzo de 2026 - TecnoWebinars.com

As AI moves from experimentation to production-scale inference, many organisations are hitting a wall. Inference now accounts for nearly half of AI spend, yet most IT leaders struggle to control costs or deliver real-time performance at scale. Hyperscalers may dominate model training, but their centralised architectures are increasingly a bottleneck for global, latency-sensitive inference - locking teams into rising costs, limited flexibility, and unpredictable performance. In this webinar, James Brown (Akamai) and Bryan Glick (Computer Weekly) explore how organisations are shifting AI inference to a distributed edge to regain control over performance, cost, and strategic freedom. You’ll learn: - Why inference is driving AI cost and complexity - How edge-based inference improves speed, resilience, and user experience - Where hyperscaler architectures create hidden costs and lock-in - How to scale AI globally without sacrificing ROI or flexibility Who should attend: - CIOs and CTOs shaping AI infrastructure strategy - IT leaders running AI in production - Cloud and platform architects planning next-generation deployments - Anyone responsible for scaling AI efficiently Register now to learn how leading enterprises are delivering faster, smarter AI — without vendor lock-in. Get First Access Powerful GPUs, ready when you are, on Akamai Cloud. Experience the next generation of AI inference and be among the first to harness NVIDIA™ RTX PRO 6000 Blackwell for AI and media workflows in the cloud. Join the GPU Waitlist https://www.akamai.com/lp/gpu-waitlist