Despite ServiceNow's AI business booming (50% ahead of plan), its stock is down. The market is confused by the AI shift, lumping all software companies together without understanding who has a genuine tailwind. This creates a disconnect between performance and valuation.
While many AI tools focus on answering questions, the real value comes from instructing systems to perform complex, multi-step tasks. For example, automatically onboarding a new employee requires orchestrating actions across 15 different applications, which is where platforms need to excel.
Waiting months to perfect governance policies before implementing AI is a fatal error. The correct approach is to implement tooling that provides visibility and tracking from day one. This allows for rapid innovation while ensuring that if things go wrong, you can detect and stop them quickly.
Enterprises care about solving business problems, not building AI agents from scratch. ServiceNow is creating a marketplace of "autonomous workers"—digital equivalents of roles like an L1 support engineer—that can perform a full job end-to-end. This abstracts the complexity and delivers a complete solution.
Amit Zavery's unusual title reflects a strategy to unify product strategy, engineering, and operations under one leader. This structure reduces fragmentation and decision-making friction, allowing the company to move faster from concept to customer value delivery.
Market sentiment is fickle, but building a sustainable platform requires unwavering long-term vision. Product leaders must balance investor feedback with a strong conviction about market direction, focusing on sustainable growth rather than reacting to short-term stock fluctuations.
ServiceNow's expansion into the crowded CRM market wasn't a random adjacency. They identified that customer service workflows—case management, issue resolution, orchestration—are functionally identical to the employee IT support workflows their platform was built for, allowing them to leverage their core strengths.
Many companies fail at AI by cobbling together disparate tools without a coherent strategy. Successful "pacesetters" adopt a holistic, platform-first mindset, providing structure, expertise, and focusing on high-value projects enterprise-wide, which avoids this pitfall.
The idea of consolidating all enterprise data into one place is a fallacy. A more effective approach is to build an integration and semantic layer that creates a virtual, unified view of distributed data, enabling insight without costly and futile migration projects.
The enterprise software market is too fragmented for one company to own the entire stack. Claiming to be the single orchestrator is a fatal strategy. Instead, companies must build open ecosystems and integrate with other systems to succeed.