19/05/2026
We talk a lot about AI models.
Not enough about the infrastructure required to run them.
That was probably my biggest takeaway from Google Cloud Next ’26.
For years, the tech industry has mostly been thinking in terms of software:
👉Applications
👉Cloud
👉Automation
👉Data
👉Generative AI
But with agentic AI, the paradigm is changing.
An AI agent does not behave like a human user.
✔️It observes.
✔️Analyzes.
✔️Triggers actions.
✔️Queries systems.
✔️Makes decisions.
And most importantly:
It generates massively more requests.
Which means the real battle may no longer be only about models…
…but about the invisible layers behind them:
→ Energy
→ Datacenters
→ Specialized chips
→ Inference capacity
→ Infrastructure acceptability
At Google Cloud Next, one sentence particularly stayed with me:
“There is not enough infrastructure in the world to run what we want to deploy in AI.”
📖 In this article, you’ll discover why agentic AI is already reshaping operational models (including frontline operations) and why infrastructure is becoming the real bottleneck.
AI doesn’t have a model problem. It has an infrastructure problem.