Big companies aren't treating AI like a toy anymore: they're folding it into everyday work. ServiceNow took a big step by choosing Claude as the default model for Build Agent and as the preferred model on its AI Platform.
And why should you or your company care? Because this is about automating critical workflows with enterprise controls, not just getting nice answers in a chat.
What ServiceNow announced and why it matters
ServiceNow named Claude as the default model powering ServiceNow Build Agent, the tool that lets both developers and less technical users create apps and automations using natural language.
On top of that, Claude and Claude Code will be rolled out internally to more than 29,000 ServiceNow employees for tasks like preparing sales meetings and speeding up code writing. ServiceNow runs more than 80 billion workflows a year; now they say many of those flows can lean on Claude’s reasoning and coding abilities, with the governance and monitoring layers a large company requires.
How they'll use it inside and outside the company
For customers
- Powerear el desarrollo de apps: Build Agent con Claude permite a equipos técnicos y a 'citizen developers' crear aplicaciones con prompts en lenguaje natural. ServiceNow espera que el uso de Build Agent se cuadriplique en 12 meses.
- Acelerar adopción y despliegue: el objetivo es reducir en 50% el tiempo para implementar productos ServiceNow, pasando más rápido de la venta a la puesta en marcha.
- Soluciones por industria: para sectores como salud y ciencias de la vida, Claude ayudará en análisis de investigación, autorización de reclamos y tareas que requieren mayor razonamiento, todo dentro de la plataforma gobernada de ServiceNow.
For employees
- Sales made more efficient: sellers use a Claude-powered tool connected to internal data and web search to prepare meetings. In internal tests, preparation dropped by up to 95%, according to ServiceNow.
- Faster engineering: Claude Code helps write, review, and debug code, automate repetitive tasks, and speed the path from idea to implementation.
Measurable impacts and expectations
The numbers ServiceNow shares are striking: 95% less prep time for sellers and 50% less implementation time for customers. They also expect strong growth in Build Agent usage.
If these figures hold up in real deployments, the effect could be noticeable: fewer manual tasks, shorter product cycles, and more nontechnical people able to build solutions. But achieving that requires ongoing monitoring of costs, security, and response quality.
Risks and questions worth watching
- Governance and compliance: integrating AI at scale means clear policies on data access, usage logs, and auditing.
- Quality and errors: how will they catch incorrect or biased responses in critical processes like medical authorizations?
- Vendor dependency: using Claude as the default model means organizations should evaluate backup strategies and portability.
- Internal training: for time reductions to be real, teams need training and best practices.
Integrating AI isn't just plugging in a model; it's redesigning how work gets done. ServiceNow and Anthropic are betting that deep integration is the practical way to get real value today.