AI at Scale: Rethinking Data Center Strategy for a Digital Industrial Future
AI is transforming every sector, from manufacturing to energy to logistics. But the true enabler isn’t just the model or the algorithm, but it’s the infrastructure behind it. As workloads grow more complex, power-hungry, and unpredictable, yesterday’s data centers are reaching their limits.
Scaling AI is no longer about adding more racks or more GPUs. It’s about rethinking the data center itself, such as designing intelligent, adaptive environments that can sense, respond, and optimize in real time. This exclusive HiveMQ whitepaper uncovers the strategies and architectural shifts needed to power AI at scale.
What You’ll Discover Inside
Laying the Foundation for AI at Scale
The AI Infrastructure Gap: Data Centers Define the Next Industrial Era
Demand Surge and How AI Workloads Change Everything
Rethinking Data Center Strategy for a Digital Industrial Future
The Hidden Challenge of Visibility and Instrumentation at Scale
Treating Infrastructure as a Data Problem
Case in Point: Alberta’s AI Infrastructure Bet
AI Ready Infrastructure for Real-Time Intelligence as a Competitive Edge
Who Should Read This White Paper?
Industrial leaders preparing for AI-powered transformation
Cloud and data center architects tasked with scaling infrastructure
Operations and IT executives seeking efficiency, resilience, and performance
Why HiveMQ for Data Centers?
HiveMQ IoT Data Streaming platform, built on MQTT, powers the connective tissue of AI infrastructure, thus enabling secure, reliable, and real-time data movement from edge to core to cloud. With HiveMQ, organizations move from spaghetti architecture to strategic advantage, unlocking the full potential of AI workloads.
Get the insights you need to transform your infrastructure from a bottleneck into a catalyst for AI success.
