The inference bill is coming due
Training got the headlines. Running models at scale is where the money now goes, and most enterprise budgets were never built for it.
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Analysis, research and reporting on the AI economy
Banks and insurers want systems they can audit line by line. That changes which models get bought.
Interviews"The model was fine. Our permissions were not." What one security team learned the hard way.
InfrastructureTraining got the headlines. Running models at scale is where the money now goes, and most enterprise budgets were never built for it.
Documentation time is the metric that finally convinced clinical leadership.
The pattern keeps repeating: models ship, then stall on the same broken pipelines.
Native partner content, clearly labelled, designed to match the page so it performs without looking cheap.
Four tests any team can run before trusting a RAG system with real customers.
Why industrial buyers care less about model size and more about uptime.
New questionnaires ask what your models can touch, not just what they do.
If the models are converging, the advantage moves to data, distribution and trust.
Deep dives, data and frameworks from The AI Journal's research desk. Some free with your email, some for subscribers.
How agentic AI is reshaping decision-making, workflows and orchestration.
The infrastructure driving the digital economy, and where it strains.
Readiness, ROI and smarter build-versus-buy decisions.
An interview series with the people deciding how AI runs inside companies.
Agents, orchestration and autonomy at work.
Strategy, adoption and return on investment.
Compute, data centres, power and pipelines.
The rules shaping how AI is built and sold.
Papers, benchmarks and what they mean.
Clinical AI, safety and operations.
AI in banking, insurance and markets.
Who is building, and who is backing them.