Can Now Assist become the industry standard for AI-native workflow automation across verticals?

ServiceNow, Inc. (NYSE: NOW) is seeking to redefine how global enterprises deploy artificial intelligence at scale through its Now Assist platform, launched as a flagship capability within the ServiceNow AI Platform in 2024. Built to automate and accelerate workflows across IT, human resources, customer service, and other critical business functions, Now Assist integrates generative AI directly into the operating core of organizations. With new functionalities unveiled at the Knowledge 2025 event and thousands of agents deployed across enterprise clients globally, institutional investors are closely watching whether ServiceNow’s AI-native approach can become the industry benchmark in workflow automation.

Founded in 2004 by Fred Luddy, ServiceNow transitioned from a help-desk automation firm to one of the largest enterprise SaaS platforms in the world. Its recent pivot toward generative AI—anchored by Now Assist, AI Agent Fabric, and the AI Control Tower—has positioned the California-based software company to directly challenge incumbents like Microsoft and Salesforce in the race to automate enterprise labor.

How does Now Assist differ from Microsoft Copilot and Salesforce Agentforce in multi-department AI deployment across enterprise workflows?

Unlike productivity-oriented tools such as Microsoft Copilot, which mainly assists users within Office 365 and Dynamics workflows, or Salesforce Agentforce, which focuses on CRM and sales operations, Now Assist is built to operate at the process layer of enterprise systems. ServiceNow’s AI-native architecture integrates directly with backend workflows and decision logic, enabling the deployment of specialized AI agents across IT service management, employee case handling, field support, finance approvals, and cross-system orchestration.

Where Microsoft and Salesforce operate through GUI-based interaction layers—supporting content generation or customer response recommendations—Now Assist embeds agent capabilities within the underlying workflow itself. For example, in IT operations, Now Assist can summarize incidents, recommend resolutions based on knowledge graphs, and even trigger automated remediation. In HR scenarios, agents handle leave approvals, policy escalations, and internal onboarding with generative explanations. The ServiceNow AI Control Tower offers unified oversight of all deployed agents, enhancing governance, scalability, and cross-functional visibility.

By supporting integration with third-party large language models from OpenAI, Google Gemini, and Azure AI, while also running its proprietary Now LLM, ServiceNow enables customers to mix foundational models while retaining control over data privacy and use-case tuning. This modular, multi-model, multi-domain architecture makes Now Assist functionally distinct from its horizontal competitors.

What productivity improvements and cost reductions are being observed in real-world deployments of Now Assist across enterprise clients?

According to enterprise briefings and public statements made by ServiceNow leadership at Knowledge 2025, customers have deployed more than 7,000 unique AI agents across departments to automate repetitive work. Early pilot studies cited by Business Insider in March 2025 suggest labor cost reductions of 15 to 25 percent in case resolution teams and productivity gains exceeding 30 percent in IT help desk operations. One global telecom client reportedly reduced ticket resolution times by 50 percent, while another North American insurance firm attributed $325 million in annualized value to its Now Assist–led automation program.

These productivity gains stem not only from faster execution but from enhanced throughput without proportional increases in headcount. The ability of Now Assist to function across departmental silos—while tailoring workflows to contextual data—offers an efficiency advantage over AI tools that operate in isolation within document or CRM environments. ServiceNow’s AI Runtime Governance stack ensures that these agents operate within safe, trackable, and policy-compliant boundaries, supporting large-scale enterprise deployment with confidence.

How flexible is Now Assist for building domain-specific AI agents, and does it support verticalized customization by industry?

Now Assist enables administrators to build custom AI agents through a no-code interface embedded in the ServiceNow Platform. Using workflows defined in Flow Designer or App Engine Studio, business users and developers can generate domain-specific skills—such as contract summarization for legal teams, regulatory checks for finance departments, or multilingual support in customer service centers. These agents can be tuned with internal data, rulesets, and behavioral constraints using Now LLM or integrated external models.

Industries that demand high workflow specificity—such as telecommunications, life sciences, and the public sector—are now target markets for ServiceNow’s AI-first deployments. At Knowledge 2025, the company launched updated solutions for telecom service management, clinical trial compliance, and government onboarding automation—each pre-configured with Now Assist capabilities. This verticalized agent strategy enables ServiceNow to compete not just on breadth but on tailored deployment speed and compliance alignment.

Competitors like Microsoft Copilot and Salesforce Agentforce have started to launch industry bundles, but their tools often rely on extending general-purpose models rather than integrating automation directly into workflow backends. Now Assist’s position within a robust workflow engine gives it a competitive edge in regulated or process-intensive industries where generic productivity layers are insufficient.

How does ServiceNow’s multi-cloud AI governance architecture support safe, scalable deployment of Now Assist?

ServiceNow’s AI Control Tower provides centralized visibility into all deployed AI agents and their operational parameters. It enables administrators to define guardrails, monitor usage, log decisions, and enforce fairness or compliance requirements. The Generative AI Controller allows organizations to toggle between large language models based on data sovereignty, latency requirements, and cost sensitivity—without modifying application code.

This governance architecture is particularly important for enterprises concerned with hallucinations, model bias, or regulatory exposure. While Microsoft’s Security Copilot and Salesforce’s Trust Layer address these issues within their native ecosystems, ServiceNow’s advantage lies in its ability to govern AI agents operating across multiple vendors and cloud environments. The AI Control Tower has rapidly become a core differentiator, with several CIOs citing it as the deciding factor in pilot-to-production transitions.

In addition, the platform’s generative AI functionality runs on RaptorDB and Now LLM infrastructure, both optimized for low-latency enterprise inference. This enables real-time AI responses in high-volume environments such as call centers, IT operations centers, and HR case portals—where reliability and speed are essential.

What are the limitations and market adoption risks that could slow down Now Assist’s trajectory toward becoming a cross-industry standard?

Despite strong enterprise interest, Now Assist faces multiple headwinds. Many enterprises are still experimenting with generative AI in sandbox environments and have not yet committed to full production deployment. There are concerns about hallucination rates, user trust in AI-driven decisions, and integration complexity for legacy applications not hosted on the Now Platform.

ServiceNow’s deep functionality sometimes requires significant upfront implementation efforts, especially in organizations with fragmented data architectures. While the platform supports multi-cloud integration, onboarding non-IT departments like finance, legal, or compliance still demands change management and executive sponsorship.

Competitive pressure is also intensifying. Microsoft has rapidly expanded Copilot into supply chain, ERP, and security verticals, leveraging its incumbency across Office 365 and Azure. Salesforce continues to advance Einstein Agent capabilities within sales and marketing workflows. For Now Assist to become the default choice, it must continue proving superior time-to-value and governance assurances across more sectors and geographies.

How are institutional investors and analysts evaluating the future potential of Now Assist and its impact on ServiceNow’s revenue growth?

Analysts covering the enterprise software sector have highlighted Now Assist as a central component of ServiceNow’s next phase of revenue growth. The American workflow platform developer projects subscription revenue between $12.64 billion and $12.68 billion in FY2025, up from $11.2 billion in FY2024. This forecast includes early monetization from Now Assist’s consumption-based pricing model, where enterprises pay based on AI usage volumes in workflows.

Investor sentiment remains broadly positive, with ServiceNow’s stock trading around $971 as of June 2025, up nearly 7 percent year-to-date despite volatility in tech indices. Institutions with long positions have cited strong free cash flow margins, product stickiness, and AI monetization runway as reasons for confidence in continued outperformance. Analysts expect FY2026 to reflect steeper growth curves if AI agent adoption scales as projected.

The Moveworks acquisition, valued at $2.85 billion, is also viewed as a bet on dominating the employee experience and conversational AI category—another vector for Now Assist integration. While integration risks remain, the deal suggests ServiceNow intends to own every layer of the AI workflow stack—from backend orchestration to end-user interaction.

ServiceNow’s Now Assist platform is emerging as a serious contender to define the future of enterprise AI automation. With a modular architecture, vertical-specific use cases, integrated governance, and multi-cloud alignment, Now Assist offers a foundation for intelligent workflow execution that can evolve with enterprise needs. While incumbents like Microsoft and Salesforce offer broader installed bases, ServiceNow’s focus on deep workflow orchestration and AI-native design gives it a strategic edge in industries where compliance, scalability, and integration matter most.

Whether Now Assist becomes the standard across all verticals will depend on its ability to demonstrate measurable ROI, maintain ecosystem flexibility, and deliver rapid deployment with governance baked in. But if early momentum and platform readiness are any indication, ServiceNow may be closer than many realize to becoming the AI operating system for the modern enterprise.