Enterprise AI

AI is becoming cheaper by the token while becoming more expensive to operate. Agentic systems are turning consumption into a new enterprise cost discipline.

AI spending is becoming harder to see and even harder to value. Licences, embedded features, agents and consumption charges are fragmenting the enterprise bill.

Having several AI suppliers does not guarantee freedom to switch. Real resilience depends on knowing which dependencies would prevent the business from moving

Enterprise AI investment is rising quickly, but value depends on something harder to buy: making business knowledge, ownership and outcomes explicit.

Entry-level work has always been where tomorrow’s experts learn. As machines absorb routine junior tasks, businesses need another way to build experience and judgement.

Bigger models do not automatically create greater enterprise value. The advantage lies in matching capability, data, infrastructure and cost to the task.

One confident model answer can hide uncertainty. Using different models and agents can expose disagreement, challenge assumptions and strengthen consequential decisions

The best workplace AI does not replace expertise. It removes routine work so people can spend more time applying judgement, empathy and experience.

AI pilots can prove that technology works without proving the business is ready. Moving into production demands far more than a successful demonstration