ServiceNow’s first wave of Knowledge 2026 announcements centered on its security and AI governance push, including Autonomous Security and Risk, AI Control Tower, and Action Fabric. The other side of that story is how ServiceNow wants that governance layer to reach everyday work, through a new front door for employees, AI specialists embedded across functions, and partner-facing tools that make agentic execution easier to package, deploy, and sell.
The next message out of Knowledge 2026 is aimed at everyday execution, not just central governance. The company is trying to make enterprise agents useful for the operators, service teams, managers, and employees still working through portals, tickets, approvals, documents, and system handoffs.
CRN’s partner interviews framed this as a shift in ServiceNow’s market position, with Jon Reynolds, co-founder and CEO of ServiceNow partner Naitiv, saying the expanded capabilities could bring AI “down to the lowest-level operators and users in the platform” and foster wider acceptance.
Otto Is the Front Door for Enterprise Work
A visible piece of that strategy is ServiceNow Otto, the new AI experience that unifies Now Assist, Moveworks, and ServiceNow’s existing AI Experience into a single conversational entry point. Nenshad Bardoliwalla, ServiceNow’s group vice president of AI, described Otto as the company’s new AI experience that “turns intent into enterprise work for every person and across every workflow.”
The product is designed to reduce the burden on employees who still need to know which portal, workflow, or department owns a request. Otto can handle natural-language requests; search across enterprise knowledge sources such as documents, wikis, databases, and SharePoint; support voice requests in multiple languages; and let users query enterprise data in plain language. Any actions taken through Otto are governed by AI Control Tower and grounded in a customer’s data, policies, approval chains, and organizational structure.
The Moveworks acquisition is important here because it gives ServiceNow a stronger conversational layer. Partners told CRN that customers needed clarity on how Moveworks and Now Assist would work together. Jason Rosenfeld, chief growth and alliances officer at NewRocket, said the front door appears to be Moveworks, while Now Assist does the work in the background and feeds Moveworks agents. That distinction is useful for ERP and workflow leaders evaluating the architecture. Otto is not being positioned as another chatbot. ServiceNow is pitching it as a user interface for completing work across systems.
Early traction is coming through EmployeeWorks, which uses Otto’s conversational capabilities. ServiceNow said EmployeeWorks closed six deals, each exceeding $1 million in net new annual contract value, within its first month, a result it attributed to Otto’s ability to complete work rather than simply field requests. For now, Otto is available through EmployeeWorks and AI Control Tower, with plans to extend it across the broader product portfolio through the rest of the year.
Analysis
What this means: The enterprise AI front door is becoming a workflow battleground. Otto shows ServiceNow moving beyond back-end orchestration into the interface where employees, customers, and support teams ask for work to get done. For ERP vendors and enterprise architects, that raises a practical question of whether the user experience of enterprise work will be owned by the system of record, the productivity layer, or the workflow platform that can route intent into action.
Partners See a UI and Adoption Shift
For ServiceNow partners, Otto also changes the implementation conversation. Jarred Pippy, COO of Everforth GlideFast, told CRN that Moveworks lets users stay in one place while searching and acting across systems such as Salesforce, ServiceNow, Coupa, or Fieldglass. Many enterprise AI deployments still break down at the user experience layer. The assistant may generate an answer, but employees still have to leave the workflow, open another system, and complete the action themselves.
Reynolds framed Otto as a broader user experience modernization. He described claims processing as an example, where an operator may have eight to 10 tabs open, and sometimes up to 20, while moving between portals, documents, and communications. With Otto, that same operator could work from a conversational interface that sends customer communications, receives files, uploads them to portals, and performs analysis without leaving the chat screen.
ServiceNow is betting the future user experience will be less about navigating application menus and more about routing intent into governed workflows. That puts it in the same broad conversation as SAP Joule, Microsoft Copilot, Salesforce Agentforce, and other enterprise assistants, but ServiceNow’s advantage is that much of the approval and workflow execution already sits inside its platform.
The Australia Release Packages the Architecture
The broader product container for these announcements is the Australia release of the Now Platform. CRN described it as building on innovations ServiceNow introduced earlier in 2026, including Autonomous Workforce, Moveworks integration, Context Engine, and Build Agent skills that let developers build agents with preferred development tools and deploy and govern them through ServiceNow. Bardoliwalla said the company had bundled these capabilities with a new commercial model to make clear that “the era of sidecar AI is over.”
Aelum Consulting’s Knowledge 2026 summary described the Australia release as ServiceNow’s first platform release under a new country-based naming convention and as the platform blueprint for the agentic era. The release included AI Agent Advisor, AI Agent Evaluator, Knowledge Center, Dynamic Guidance, Intelligent Approvals, and AI Control Tower as connected components. These capabilities are intended to identify automation opportunities, test agent accuracy and completion rates before production, improve enterprise knowledge, provide real-time voice assistance inside the platform interface, and turn policy documents into live approval logic.
That set of features shows where ServiceNow is trying to differentiate. The company is not only showing end-user assistants. It is building administrative, evaluation, knowledge, and approval capabilities around them. For enterprise buyers, that matters because successful agentic workflows depend on readiness work: clean knowledge, testable behavior, policy-aware approvals, and a way to measure whether agents perform reliably before they reach production.
Analysis
What this means: Agent readiness now includes knowledge, policy, and evaluation infrastructure. ServiceNow’s Australia release emphasizes AI Agent Advisor, AI Agent Evaluator, Knowledge Center, Intelligent Approvals, and Data Catalog rather than only end-user assistants. That points to a more mature adoption model in which enterprises must prepare knowledge bases, approval logic, data quality, and testing processes before agents can move from demonstration to dependable execution.
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Autonomous Workforce, Agent Specialists Expand the Labor Argument
ServiceNow also continued to push its Autonomous Workforce concept. Aelum’s summary noted the company expanded AI specialists across IT, CRM, employee services, and security, designed to execute complete workflows alongside humans. It cited ServiceNow examples including 99% faster IT case resolution with the L1 Service Desk AI Specialist, more than 90% of employee IT requests handled autonomously, and 91% of employee cases resolved without reassignment.
Those figures should be read as product and customer-claim signals rather than a guarantee of outcome. Still, they explain why ServiceNow’s positioning is resonating with partners. The company is not simply selling automation as task deflection. It is packaging AI specialists as operational capacity in IT, HR, CRM, security, and employee services, with AI Control Tower serving as the governance layer behind that work.
This is the workforce argument underneath Knowledge 2026. Enterprises face pressure to increase service speed and reduce manual operational load, but they cannot let agents act without controls. ServiceNow’s answer is to make autonomous execution part of the platform rather than a separate automation layer. For ERP providers and systems integrators, that shifts the adoption question from “Which AI assistant should we deploy?” to “Which platform will govern and execute the work?”
Project Arc and Autonomous CRM Broaden the Surface Area
Two other announcements widen ServiceNow’s ambitions beyond traditional workflow surfaces. ServiceNow and NVIDIA introduced Project Arc, an autonomous desktop agent built on ServiceNow Action Fabric, secured by NVIDIA OpenShell, and governed through AI Control Tower. Project Arc is described as executing complex, multi-step work from the desktop while running actions in a sandboxed runtime with visibility into files accessed, commands executed, APIs called, and policies enforced. The partnership also introduced NOWAI-Bench, an open benchmarking framework for evaluating enterprise AI agents across real-world workflows.
ServiceNow also introduced Autonomous CRM for Sales, Autonomous CRM for Service, and CPQ capabilities intended to move customer operations from quote to fulfillment without manual handoffs. The cited scale figures were more than 7 million CPQ transactions monthly, more than 100 million customer service cases resolved monthly, and more than 16 million orders orchestrated each month across the platform.
The CRM and desktop-agent announcements show ServiceNow extending its workflow thesis into areas where ERP, CRM, productivity, and service operations increasingly overlap. Project Arc pushes toward desktop-level execution. Autonomous CRM pushes toward customer operations. Otto pushes toward conversational entry. Action Fabric opens execution to external agents. Together, these moves make ServiceNow harder to categorize as only ITSM, workflow, or employee service.
Analysis
What this means: ServiceNow is expanding from workflow automation into operational capacity. Autonomous Workforce, Otto, Project Arc, and Autonomous CRM all push the same idea: ServiceNow wants agents to execute work across functions, not only summarize information or deflect tickets. For systems integrators and ERP transformation leaders, that could change delivery models by turning ServiceNow into a governed execution layer that sits across ERP, CRM, HR, finance, security, and service operations.
Data and Knowledge Remain the Hard Part
The headlines also highlight a practical constraint. Agentic execution depends on data, knowledge, and workflow context that many enterprises still do not have in usable shape.
ServiceNow launched a new Data Catalog with native metadata management and governance across the data lifecycle, along with Autonomous Data Governance to monitor the data estate and flag quality violations in real time. Context Engine is positioned as the layer that unifies organizational knowledge and supplies AI with context at the point of decision.
That connects directly to Otto and Autonomous Workforce. A conversational front door is only useful if the underlying knowledge, policies, approvals, and workflows are accurate enough to act on. ServiceNow’s platform story is that it can combine enterprise data, workflow history, operational context, and governance in one place. The harder test will be whether customers can clean and maintain enough of their knowledge and process logic for agents to operate reliably across functions.
