TLDR: ServiceNow and Nvidia have announced a significant collaboration at Knowledge 2025, introducing the Apriel Nemotron 15B reasoning model. This new AI is designed to enhance decision-making and workflow management across enterprises, leveraging Nvidia’s NeMo platform and ServiceNow’s Workflow Data Fabric. The partnership aims to accelerate AI performance, reduce operational costs, and foster a new era of human-AI collaboration in the UK and globally.
ServiceNow and Nvidia are spearheading a new era of enterprise AI transformation, marked by the unveiling of their high-performance Apriel Nemotron 15B reasoning model at ServiceNow’s annual Knowledge 2025 event. This strategic collaboration, highlighted in the October 2025 issue of AI Magazine, is set to revolutionize how businesses operate by embedding advanced AI capabilities directly into core workflows.
The Apriel Nemotron 15B model, developed in partnership with Nvidia using its NeMo platform and ServiceNow-provided data, is designed to improve AI agents’ decision-making and workflow management within enterprises. It is trained on Nvidia DGX Cloud, hosted by Amazon Web Services (AWS), and is engineered to offer sophisticated reasoning in a more compact and efficient size, optimizing performance on Nvidia GPU infrastructure. Early benchmarks suggest promising results for scaling AI workflows.
Beyond the reasoning model, the collaboration includes integrating Nvidia NeMo microservices into the ServiceNow Workflow Data Fabric. This integration is expected to create a ‘closed-loop data flywheel process,’ continuously refining and optimizing reasoning models to improve the accuracy and personalization of AI agents.
ServiceNow CEO Bill McDermott articulated a grand vision for ‘enterprise AI nirvana’ at Knowledge 2025, describing an AI platform that supports any AI model, any agent, any type of data, any workflow, any cloud, and any system for any industry. He emphasized that AI is ‘civilization’s greatest opportunity of the century’ and ‘bigger than the internet, mobile and cloud computing combined,’ predicting a $22 trillion economic impact by 2030, including $4 trillion in opex reduction.
Key technological advancements supporting this vision include the AI Control Tower, which enables unified management, governance, and security of AI models from any source, whether on-cloud or on-premises. The Workflow Data Fabric is crucial for connecting diverse data sources, facilitating seamless interaction between proprietary and third-party agents and systems. Additionally, RaptorDB, a high-speed database, addresses data management challenges, answering critical questions about data handling for the platform.
Real-world applications already demonstrate significant impact. Siemens has reportedly saved 1 million work hours by leveraging the ServiceNow AI platform. Pharmaceutical giant AstraZeneca has seen a reduction in supply request times from 20-30 minutes to mere seconds, translating to 90,000 saved work hours annually for 60,000 such requests. A demo at the conference illustrated an AI agent autonomously detecting and resolving a device error, confirming warranty, and ordering a replacement.
ServiceNow is also expanding its ambitions into the CRM market, with COO and Chief Product Officer Amit Zavery stating that ‘Traditional CRM is broken.’ This move signals a direct challenge to incumbent players like Salesforce, aiming to disrupt the market with a workflow-centered approach powered by agentic AI.
Nvidia CEO Jensen Huang, a long-standing partner of ServiceNow, expressed his belief that ‘ServiceNow is destined to be the best platform — the operating system of AI agents.’ This sentiment underscores the deep integration and shared vision between the two technology leaders.
Damien Davis, Senior Director in ServiceNow’s Customer Excellence Group, highlighted the company’s ‘AI native, not AI added on’ philosophy. This means AI is built directly into workflows, not as a separate add-on, ensuring seamless integration and enhanced user experience. ServiceNow measures AI success not with new, complex metrics, but with traditional business outcomes: reduced costs, increased productivity, faster time to value, and improved employee and customer experiences. Davis emphasizes that successful organizations ‘start small, scale fast,’ focusing on business-critical use cases and investing in governance and change management from day one.
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The broader context of this collaboration aligns with the ‘Tech Prosperity Deal,’ a landmark US$38.7 billion technology agreement between the US and the UK. This deal establishes a framework for enhanced collaboration in AI research and development, with major commitments from key players like Microsoft, Nvidia, Google, and CoreWeave, further solidifying the UK’s role in the global AI landscape.
