Buying an agent from every system of record recreates SaaS sprawl one layer up. How CIOs should choose, and which controls must stay central.
AI spend is moving from central IT to business lines. That ties cost to outcomes but breaks controls built for an IT-held purse. The model that works.
Enterprise search failed for twenty years. Now the permission-aware index behind every AI assistant is the control point, and its owner wins.
The model layer is commoditizing faster than any software layer before it. The margin is moving to scarce inputs and to whoever owns the workflow.
Running one workload across two clouds rarely pays for itself. A second cloud's real value is leverage and exit evidence. Which workloads need what.
Deflection counts every chat that never reached a human, including the customer who gave up. What to measure instead, and what to ask vendors.
Embedded lending is a credit business with a software channel, not a software business with a credit feature. The models differ by who eats the loss.
Observability was sold as a product and is being re-architected as a data pipeline. That is what breaks the pricing model, not the customer anger.
Interchange is not being abolished, it is being unbundled. The losers are not the networks. They are issuers whose products are funded by a fee going soft.
The best vertical AI companies stopped selling assistants beside the suite. They are taking over the record itself, and the record owns the renewal.
Training data went from free scrape to priced asset in three years. Who sets the price, who captures the value, and why enterprises are giving theirs away.
Models are commodities. The accumulated context a vendor holds about your organization is not, and it is becoming the stickiest layer in the AI stack.
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