Business, technology and what comes next.
NextNow / Contributor
Reporting and analysis
The multibillion-dollar agreement will add European computing capacity and allow Mistral models to run across cloud, customer-controlled and disconnected environments.
Why the value of enterprise agents will depend less on autonomy and more on how deliberately the work is designed
Automation works smoothly until a workflow encounters ambiguity, risk or failure. The companies that design strong human handoffs will resolve exceptions faster, protect accountability and produce more durable returns from automation.
Google Cloud is consolidating its enterprise AI development tools around agents that can run longer, use multiple systems and remain visible to IT.
Enterprise teams are moving from accumulating applications to defining which systems truly deserve budget and operational dependence.
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.
Software buyers are beginning to evaluate whether a system can serve agents as reliably as it serves people.
A polished demonstration can prove possibility. It cannot establish whether an AI system will be dependable inside a living organization.
