As AI spreads across cloud, edge, applications, and devices, infrastructure has a new job: coordinating not just applications and data, but models, agents, workloads, and decisions. Deloitte's "The next tech infrastructure advantage is intelligence orchestration" explores the concept of an enterprise control plane that can govern how intelligence operates across distributed systems, including model selection, workload routing, identity, cost, latency, security, and regulatory requirements. Read the article ➡️

AI adoption is entering a more disciplined phase. After moving quickly to deploy new tools, some organizations are confronting errors, low-quality output, security concerns and unexpected demands on employees. The Guardian article explores why some employers are reassessing how AI is introduced, governed and measured across the organization. Read the article the connect with Digital6 Technologies to discuss how these trends may influence your organization's technology strategy. 🔗

AI at scale rarely fails because of the technology alone. 🤖. The article "AI at Scale Is an Operating Model Problem, Not a Technology One" highlights how gaps in governance and alignment slow progress. Read the article to see what it takes to scale AI across the business. 🚀.

AI is changing how enterprises think about cloud architecture. Growing compute demands, cost pressures and data sovereignty requirements are driving renewed interest in hybrid approaches spanning public, private, edge, colocation and sovereign environments. CIO Dive's "AI Pushes Enterprises Back to the Drawing Board on Cloud" examines why enterprises are revisiting cloud plans to better support AI. Read the article ➡️