ServiceNow's shares recovered after a steep drop as Goldman Sachs raised its price target, citing the company's rapid AI contract growth and its evolving role in enterprise software amid industry fears over AI disruption
Seven years ago, ServiceNow CEO Bill McDermott set an ambitious goal: to make the company the defining enterprise software provider of the 21st century. At the time, ServiceNow was best known for its IT ticket routing software-a tool for logging issues like broken laptops or locked accounts. Few could have predicted how much the landscape would shift as artificial intelligence began to challenge the very foundation of the software subscription model.
In the first half of 2026, the enterprise software sector faced what some analysts dubbed a "SaaSpocalypse," as companies questioned whether AI agents could replace traditional software licenses by automating tasks previously handled by humans. ServiceNow's stock price reflected these anxieties, falling nearly 50% over the prior year as investors debated whether AI would make seat-based subscriptions obsolete.
AI Revenue Surges
Despite the uncertainty, ServiceNow's second-quarter 2026 results beat Wall Street expectations for revenue, earnings, and bookings. According to the company's July 22 earnings release, subscription revenue climbed 24.5% year over year to $3.88 billion. While shares initially dipped, they rebounded in after-hours trading as investors processed the numbers and the company's outlook.
Goldman Sachs responded by raising its price target for ServiceNow to $152 from $145, maintaining a buy rating. The bank's analysts, led by Gabriela Borges, argued that the company's future valuation will depend less on quarterly subscription beats and more on its ability to prove relevance within the enterprise AI stack. This marks a shift in how investors are being urged to evaluate ServiceNow's prospects.
One key milestone: ServiceNow's annual contract value (ACV) from AI products surpassed $1 billion for the first time in the second quarter. The company reiterated its confidence in exceeding $1.5 billion in AI ACV by the end of 2026, putting it ahead of its own target for AI to reach 30% of total ACV by 2030. Goldman Sachs views AI-driven revenue as more valuable than traditional workflow revenue, since AI deployments tend to deepen customer relationships and open the door to future growth.
Automation and Customer Adoption
ServiceNow's Level 1 IT service management product, which became widely available in May, now resolves 80% to 85% of service requests without human intervention, according to Goldman's research note. This is significant because it demonstrates automation gains within the company's core business, not just in experimental side projects.
Net new AI bookings grew more than 40% quarter over quarter, and the number of customers running AI in production increased ninefold over nine months. Deal volume among first-time AI buyers rose 45% year over year. Goldman also highlighted a new voice AI capability, with one airline now routing all of its roughly 5 million annual customer service calls through ServiceNow's platform. As AI agents take on more complex tasks, the bank expects both customer engagement and revenue per client to rise.
Risks and Diverging Analyst Views
Not all analysts are convinced that AI will be a net positive for ServiceNow's business model. Guggenheim's John DiFucci upgraded the stock to buy earlier in July, but for a different reason: he expects AI monetization to fall short and sees the stock as undervalued rather than fundamentally transformed. He remains concerned that AI could still threaten the traditional software model, a view echoed by some investors who worry about disintermediation from competing AI technologies, longer sales cycles, and delays in federal spending.
ServiceNow's leadership has pushed back on the idea that advanced AI will make its platform obsolete, arguing that most enterprise AI runs on cost-effective, purpose-built models rather than the expensive, cutting-edge systems that could disrupt the market. This debate over which companies can maintain their valuation multiples in an AI-driven world is playing out across the sector, as investors scrutinize AI contract disclosures and look for evidence of sustainable growth.
For context, the debate over how AI is reshaping software valuations echoes broader shifts in the tech sector, as seen when Citi declared the end of the "Magnificent Seven" era and urged investors to look beyond the largest tech names. For more on how changing market leadership is affecting investor strategy, see this analysis of Citi's call on tech sector rotation.
Market Data and Outlook
ServiceNow's market capitalization stood at roughly $80 billion as of late July 2026, with shares recovering from their lows earlier in the year. The company's AI-driven contract value growth outpaced many peers, and its 24.5% year-over-year subscription revenue increase was among the strongest in the sector for the quarter. Investors remain divided on whether these gains signal a durable shift or a temporary reprieve as the industry adapts to AI's impact on software delivery and pricing models.
As the next few quarters unfold, ServiceNow and its competitors will be under pressure to demonstrate that AI can drive not just cost savings, but also new revenue streams and deeper customer engagement. The outcome will help determine which enterprise software vendors can sustain premium valuations in a rapidly evolving market.
AI's growing role in enterprise software is forcing companies to rethink how they price, deliver, and support their products. Traditional seat-based subscription models are being tested as customers seek more flexible, outcome-based pricing tied to automation and productivity gains. For investors, understanding the difference between incremental automation and transformative AI adoption is critical. Companies that can show measurable improvements in customer retention, contract value, and workflow integration may be better positioned to weather the transition, while those that rely solely on legacy models could face increasing pressure as AI capabilities become more widely available.