After the AI Pilot, Standards Become the Product
The practices that survive the experimental phase are less glamorous than model demos: identity, permissions, evaluation, escalation and repeatable evidence.
Business, technology and what comes next.
NextNow / Archive
The practices that survive the experimental phase are less glamorous than model demos: identity, permissions, evaluation, escalation and repeatable evidence.
As software begins to discover, compare and purchase on a customer’s behalf, value is shifting toward the protocols, identity systems and payment rails between agents.
The security model for enterprise AI is shifting from controlling a tool to governing software actors that can choose and execute actions.
Companies want the reasoning power of frontier models without surrendering control of proprietary context, permissions and institutional memory.
A polished demonstration can prove possibility. It cannot establish whether an AI system will be dependable inside a living organization.
Layered generation, design agents and code on the canvas are multiplying the number of viable directions a team can evaluate.
Second-quarter revenue rose 93% as U.S. commercial customers expanded deployments, offering one of the clearest signals yet that some enterprise AI budgets are moving into operational systems.
New EU requirements govern disclosure when people interact with AI and the machine-readable marking of generated or manipulated content.
Amazon raised its 2026 capital-spending plan by $20 billion as AWS growth accelerated, illustrating how the AI race is being fought through power, chips and long-lived physical assets.
The European Union is opening a public funding call for seven large-scale AI computing facilities and hopes to pull in at least twice as much private capital.