ServiceNow announced a major Now Platform expansion with the Now Assist family of solutions.
Available in the Now Platform Vancouver release, Now Assist for IT Service Management (ITSM), Customer Service Management (CSM), HR Service Delivery (HRSD), and Creator embed the power of generative AI across all workflows on the Now Platform to help accelerate productivity, improve experiences, and increase agility for customers. To power new features within Now Assist, we are releasing a domain‑specific ServiceNow large language model (Now LLM), built for the enterprise and optimized for productivity and data privacy.
“Organizations are seeking a trusted partner to help them navigate this dynamic and fast‑moving era of intelligence,” said CJ Desai, president and chief operating officer, ServiceNow. “ServiceNow has thousands of customers already using the Now Platform to digitize and streamline processes across the enterprise. With our Vancouver release, we’re combining the power of the Now Platform with new generative AI features to bring AI‑driven intelligence to every corner of the business, creating a catalyst for productivity and better enterprise experiences."
The Now Platform operationalizes generative AI to drive growth and help reduce costs for every customer across every business function with enterprise‑grade AI designed for high levels of digital trust and privacy. Now Assist is woven into all processes and workflows to help optimize performance and is compliant with ServiceNow controls for ethical and responsible development and use.
Now Assist incorporates generative AI features such as case, incident, and agent chat summarization, virtual agent, and search capabilities that can be applied to a broad range of scenarios and functions, so every persona from employees to agents to developers can harness the power of generative AI. This foundational approach allows enterprises to bring the power of generative AI to any department and expand to other parts of the business quickly and easily.
- Now Assist for ITSM empowers enterprise IT leaders to take control of their IT experience, dramatically improving agent productivity and the employee experience with faster resolutions. Summaries of incident history and live Virtual Agent interactions deliver complete answers instead of search results so agents can resolve issues and requests faster without needing to ask users to repeat themselves. Now Assist for ITSM can also create contextual summaries of incidents and resolution notes, which help organizations implement incident management best practices and resolve more incidents in less time.
- Now Assist for CSM streamlines the customer service process from beginning to end, leading to higher agent productivity, potential cost savings, and improved customer experience. By rapidly generating summaries for cases and chats, Now Assist for CSM reduces manual work and allows agents to resolve customer issues faster. Customers also benefit from an improved self‑service experience, with access to resources that help them find answers fast, leading to higher case deflection and cost reduction.
- Now Assist for HRSD helps HR leaders drive productivity and operational efficiency, reduces redundant, manual tasks for HR teams, and gets employees the answers they need quickly with little disruption to their day. HR managers can handle issues from payroll discrepancies to paperwork changes without needing to sift through loads of information by reviewing instant summaries of case topics, previous history from live chat and Virtual Agent interactions, as well as previous resolutions and actions taken. This gives HR teams the context they need to solve problems quickly and confidently.
- Now Assist for Creator helps development teams create and scale apps more quickly on the Now Platform. Trained on code from ServiceNow engineering, results are designed to be higher quality and more scalable, and the data processed on the platform is more secure than with any other code generation technology. Now Assist for Creator includes the general availability of text‑to‑code, which converts natural language text into high‑quality code suggestions, and in some cases complete code. Text‑to‑code helps ensure every corner of the enterprise can create seamless coding experiences that can deliver fast development and increased productivity.
ServiceNow’s generative AI strategy provides customers with broad and secure LLM support, through either general purpose LLMs or ServiceNow‑developed models. General‑purpose LLMs provide customer flexibility and currently include access to Microsoft Azure OpenAI Service LLM and OpenAI API. Built into the Now platform, domain‑specific LLMs are designed specifically for ServiceNow’s workflows, use cases, and processes, and are tailored to agents, employees, customers, and IT administrators who use ServiceNow. This allows for an excellent end‑user experience, unprecedented time‑to‑market, and high levels of transparency and governance.
For example, features within Now Assist for Search are powered by a ServiceNow fine‑tuned LLM based on the NVIDIA NeMo framework and served using NVIDIA Triton Inference Server software, both part of the NVIDIA AI Enterprise software platform. These features bring to market new capabilities built from the ServiceNow and NVIDIA partnership announced in May.
All generative AI innovations are part of ServiceNow’s Now Platform Vancouver release and will be generally available on Sept. 29 to all customers.
The Latest
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...
The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...
Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...
If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...