Agentic AI: An exciting future or an architectural headache?
Agentic AI is more than a buzzword. Agents plan and act independently, but this places entirely new demands on cost control, security and monitoring.
Five mistakes when organizations run AI in the cloud
Many organizations make the same mistakes when running AI in the cloud. Here are the five most common traps – and how to avoid them.
AI in manufacturing: the pilot projects are over
Fictiv and MISUMI’s new report shows that AI adoption in manufacturing has jumped from 87% to 93%. But the pilot projects are over – now it’s all about infrastructure and data control.
Pentagon invests $13.4 billion in AI – more than autonomous weapons
The US Department of Defense is investing $13.4 billion in AI. Read what the investment means and why it goes beyond military applications.
AiQu: the infrastructure that takes AI from promising pilot to actual production
Scaling AI is more about infrastructure than algorithms. AiQu doesn’t lock you to one vendor – supporting NVIDIA, AMD, Intel and edge.
The 6 most common MLOps bottlenecks – and how to solve them before 2026
The 6 most common bottlenecks in MLOps projects – from “it worked on my machine” to data sovereignty. How to solve them with AiQu before 2026.
Is the NVIDIA monopoly about to be broken? AMD and Nutanix challenge the playing field
AMD and Nutanix challenge NVIDIA’s dominance with open AI infrastructure. Three key insights into the future of AI operations that every decision maker should know.
Data Sovereignty: From freedom of choice to an absolute requirement
August 2, 2026 will be a watershed when the EU AI Act fully applies. The difference between ‘data residency’ and ‘data sovereignty’ will determine which companies can keep their AI systems.
Sovereign AI: From fancy buzzword to rock-solid purchasing requirement
When AI pilots go into production, the tough questions arise: who owns the data, where do the calculations run, and what happens when they are locked in? Sovereign AI is no longer a buzzword – it’s a concrete purchase requirement.
When the AI emergency becomes bigger than the vision – are you aware of the inference paradox?
When AI operations become the organization’s biggest expense – not the training, but life itself in production. We call it the inference paradox.
