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.
Inference is a real, usage-scaling cost of goods sold. It is pulling software gross margins toward infrastructure territory, and buyers pay for it either way.
Stablecoins were supposed to disintermediate the card networks. Instead Visa and Mastercard are running an incumbent defense: co-opt, contain, collect.
Agent interop standards are not neutral plumbing. Whoever owns the protocol layer between agents and enterprise systems owns the distribution chokepoint.
AI capacity is consolidating into a utility with three chokepoints. The strategic question is no longer which model to use, it is who controls your inference.
AI build versus buy is not one decision but six, one per stack layer. A decision matrix with defaults, override conditions, and traps for each.
Deep analysis across the systems, strategies, and economics that shape modern technology.
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