ServiceNow (NOW.US) Q3 conference call: The Q4 subscription guide is 4.245 billion, up 21.5% year over year, the AI target was increased to 1.7 billion US dollars, and AI momentum will be realized in 2027

The Zhitong Finance App learned that after the US stock market closed on Wednesday, the enterprise software company ServiceNow (NOW.US) announced financial results for the third quarter of 2026. According to the data, the company's revenue for the quarter reached US$4.106 billion, up 20.5% year on year, up 20% at a fixed exchange rate; GAAP net profit was US$277 million, down about 45% from US$502 million in the same period last year; and GAAP diluted earnings per share were US$0.27, down from US$0.48 in the same period last year.

Non-GAAP adjusted net profit was $1,039 million, up about 5% from $992 million in the same period last year; adjusted diluted earnings per share were $1.00, up from $0.95 in the same period last year.

ServiceNow said that revenue growth and profitability indicators for the third quarter all exceeded the upper limits of previous guidance, and announced an increase in subscription revenue and free cash flow profit margin expectations for the full year 2026.

Subscription revenue increased 21% AI business drives contract size expansion

As ServiceNow's main revenue source, the third quarter revenue of the subscription business reached US$3,988 billion, up 21% year over year and 20.5% at a fixed exchange rate. Revenue from professional services and other businesses was $118 million, up 10% year over year.

By the end of September, the company's current remaining performance obligation (CrPO) reached US$13.65 billion, an increase of 20.5% year over year, and an increase of 21% at a fixed exchange rate. This indicator mainly reflects contracted revenue expected to be confirmed within the next 12 months.

At the same time, the total remaining performance obligation (RPO) reached US$29.7 billion, an increase of 22% over the previous year, and an increase of 22.5% at a fixed exchange rate, reflecting the continued expansion of the company's future contract revenue.

In terms of major customer demand, ServiceNow completed 19 additional annual contract transactions worth more than $5 million in the third quarter, and the number of transactions increased by more than 135% over the same period last year. By the end of the third quarter, the number of customers with annual contracts worth more than $5 million reached 680, an increase of about 23% over the previous year.

Below is the full text of the ServiceNow results conference call (artificial intelligence tool assisted translation):

I. Executive speeches

Bill McDermott, Chairman and CEO

The third quarter results can be described as ServiceNow's “three-game winning” moment: quarterly results once again fully exceeded expectations, AI performance accelerated by the biggest margin so far, and the hybrid business model further shifted to a consumption model.

Let's look at standard performance first. Subscription revenue increased 20.5% at a fixed exchange rate, 50 basis points higher than the guideline; cRPO (current remaining performance obligation) increased 21% at a fixed exchange rate, 100 basis points higher than the guideline; operating profit margin was 32.5%, 150 basis points higher than the guideline; and the free cash flow margin was 20%. In the third quarter, there were 19 transactions with a net additional annualized contract value (ACV) of more than $5 million, an increase of 135% over the previous year. Remaining performance obligations (RPO) reached $30 billion, an increase of 23% year over year, which is a large-scale increase.

As far as the “three consecutive wins” is concerned, the third quarter results are even more impressive: for several quarters, the company has been actively building a consumer engine into the business model. The goal is to become the governed executive layer of enterprise AI and provide various commercialization paths, all driven by customer choices. The third quarter was the most impressive achievement so far. The strategy is working. AI monetization has achieved substantial results: net AI ACV increased 65% year over year in the third quarter; Control Tower's net new ACV increased 6 times year over year; intelligent front desk EmployeeWorks ACV reached 100 million US dollars in less than three quarters; the number of AI transactions over 1 million US dollars increased 4.5 times year over year; smart AI consumption in production environments increased more than 13 times year over year; consumption of Action Fabric Assists alone One item was a 500% month-on-month increase. This is not only the direction the customer is moving forward, but also the direction the customer wants the company to go. It is the right direction for long-term shareholder value creation. Looking back, the company set an AI target of 1 billion US dollars by the end of the year, raised it to 1.5 billion US dollars in May, and raised it again to more than 1.7 billion US dollars by the end of the year today. Management has placed higher demands on the team to go beyond that number.

Overall, the company is making every effort to advance to the fourth quarter. Gina will introduce the guidelines later, and the guidelines will be raised. As we all know, ServiceNow has always had a strong end, aiming for the best year in the company's history.

Let's take a few more minutes to talk about today's still complex business environment. A few weeks ago, the company held its semi-annual CEO event, which was attended by more than 125 CEOs. The consensus of the participants was that everyone is investing in the intelligent revolution. Billions of dollars have been invested so far, and they have all gone through the token maximization phase. The major lesson they learned is that in an AI world, the risk of “vibe slop” (vibe slop), failed projects, proliferation, and lack of integration is greater. When it comes to ServiceNow's role as a Super Intelligence Control Tower (SICT) for corporate restructuring, it is widely acknowledged. SICT uses the right models for the right workloads to solve the right problems and unlock the right opportunities for customers. Businesses in all walks of life require an enterprise AI control framework. This is not only a single level of orchestration, governance, or security, but the core of the intersection of the three.

Enterprise intelligence is now in the “rules and rails” (rules and rails) stage. 94% of companies report an AI visibility gap, and 88% can't even distinguish between personal AI accounts and corporate instances. ServiceNow's Control Tower discovers and inventories the entire AI asset. As “rogue agents” (rogue agents) incidents continue to occur, ServiceNow controls the actions that agents can perform. To this end, the company launched AI Passport, which issues an official certification record for each agent based on the context of the platform — who owns the agent, what it is allowed to do, what data it can access, and how much risk exposure it is allowed to bear. This makes up the most powerful “emergency braking” (kill switch) capability in the business world today. When Control Tower revokes a passport, NVIDIA Century will stop accepting it, and the smart device will be terminated at the infrastructure level. The company is promoting this capability everywhere. Control Tower sends signals to Okta, Microsoft's Azure AI Foundry, and Google's Gemini Enterprise agent platform, so that it can cut off access to the agent no matter where it is running. ServiceNow is at the core of operations of the world's largest enterprises, with CMDB, Workflow Data Fabric, and embedded operational intelligence and context spanning more than 20 years in IT, security, and risk.

With Armis and Veza, the company can now accurately locate specific known vulnerabilities in an irreversibly changed cybersecurity landscape called “Shift Zero” (zero transformation). It shifts post-safety remediation to pre-emptive prevention, from manual speed to machine speed, and from blind spots to treatment. The average enterprise runs more than 70 security tools, and ServiceNow provides a single governance system with evidence of “what acted, why, and who is responsible”. This is not a gradual improvement to a passive model, but rather an integrated alternative to a fragmented market and a gateway to autonomous defense. Because of this, ServiceNow has become the fastest-growing cybersecurity company on a large scale, and the growth rate is increasing rapidly.

Operating in an age of superintelligence, the pace of innovation must keep pace with the growth of the scale of opportunities. The ServiceNow team is proud of what they have delivered. The company's Level 1 service desk specialists (specialists) resolve incidents 85% faster than manual customer service, and are now fully self-operated for customers of all sizes and industries, from leading global automotive companies to leading enterprise technology companies. AIOps experts have reduced median resolution time by 40% within the first month. Currently, more than 100 customers are using the company's AI experts to innovate; AIOps, HRSD and CRM experts are expected to be fully launched in the fourth quarter.

As businesses rethink the mission of CRM systems, ServiceNow is leading the way. The old CRM was built for the sales team, and the new CRM must run throughout the entire business. This is a different product and a different structure. Because of this, customers are “ripping and replacing” (rip and replace) rather than just adding on top of the original. Conversational voice AI is the next major leap forward in connecting the front desk to the entire enterprise. Customer dialogue is the starting point of work, and the platform must run it through every system and workflow that follows. Companies are redefining how businesses interact with customers. Sweep's merger and acquisition (tuck-in) brings deep expertise in rapid agent deployment, adding further impetus to accelerate and improve customer outcomes. One year after Logik AI was merged into ServiceNow, the company was named a leader and customer favorite in the Forrester Wave “Configure, Price, Quote (CPQ) Solution” report. There is a similar shift in gravity in the field of employee experience.

Targeting the broader enterprise market, the company launched Flow. Many businesses want leading domain expertise but aren't ready to adopt a formal ITSM. Flow fills this gap — a brand new, self-service, pay-per-use conversational help desk. Customers can sign up today and use it today, which is an important reason for its lightning start among businesses and government agencies around the world. ServiceNow EmployeeWorks continues to be a rapid growth engine, providing enterprises with one-stop search, knowledge, work order flow across IT, HR, finance, and procurement. It has also become a one-stop platform for employees to build AI assistants, intelligence, and automation, and is protected by corporate guardrails (guardrails) throughout the process. This is just the tip of the iceberg of groundbreaking innovation on the ServiceNow platform. Even the best platforms can't deliver for businesses on their own. ServiceNow Control Tower Alliance is a new ecosystem that brings together leading companies in the fields of AI, cloud infrastructure, security, governance, and token management to help customers adopt trusted enterprise AI safely and on a large scale. Founding members include Anthropic, AWS, Cisco, HiddenLayer, Kong, Okta, OpenAI, WitnessAI, and Zenity.

Today, ServiceNow announced the expansion of its collaboration with OpenAI to help enterprises move seamlessly from AI reasoning to governed actions. The collaboration extension first launched as a new ServiceNow version of ChatGPT plug-in, powered by Action Fabric. The company aims to develop security and risk solutions based on the OpenAI cybersecurity model, Codex integration, AI workflow factories, and voice-driven governance for the ServiceNow super intelligent control tower. The two sides have high hopes for this cooperation, particularly in the field of cybersecurity. Furthermore, the collaboration between Google Gemini Enterprise and ServiceNow Action Fabric has been expanded: Gemini Enterprise provides a conversational front-end, and ServiceNow provides governed industry workflow execution. The collaboration with cPrime's INRY showcased the partners' “build first, then sell” results on ServiceNow — Inry launched EmployeeWorks within six weeks, setting a new benchmark for value realization time rather than an exception; they did not sell the solution externally until they personally used it. The median submission time has now been reduced by 60%, and the completion rate is 97%. ServiceNow reached an agreement with Aramco Digital (Aramco Digital) to standardize and govern the digital workflows of Aramco's affiliates, subsidiaries, and joint ventures in more than 50 countries. There is no shortage of such collaborations.

It could have stopped at the numerous industry accolades it has received — three new Gartner Magic Quadrants, two new Forrester Waves, IDC reports, etc. But it should end with the ultimate yardstick for measuring a decisive corporate technology company — the customer. A leading Asian telecommunications company with over 130,000 employees and contractors, became the first company in the region to deploy ServiceNow Autonomous Workforce, enabling a zero-touch IT and HR help desk, which will handle 70,000 IT requests and 6,000 HR inquiries every year. Using ServiceNow AI experts, The Salvation Army (Australia) has returned more than 5,000 hours to frontline workers so far, and this time has been diverted to serving community members in need. The German Professional Football League has expanded its cooperation with ServiceNow as its official CRM partner — within just one month, fan service has been integrated from 7 digital channels into a single ServiceNow platform. 89% of inquiries were resolved at first contact, and the number of cases was cut in half.

In a global logistics leader's previous freight operation, manual processes across silos were heavy and frustrating. ServiceNow created an AI partner “Shipment Issue Analyzer” (Shipment Issue Analyzer) for it. As a result, it saved nearly 100,000 hours a year and shortened the resolution time from three days to less than 30 minutes. Jack Henry & Associates, a leading American fintech company, chose ServiceNow CRM to automate routine tasks with AI, enhance after-sales operations, and modernize CRM capabilities. A consumer finance company previously faced the problems of scattered channels, unclear authority and responsibility, and legacy systems swallowing up signals in terms of risk identification.

The company's Applied AI Front Deployment Engineer (FDE) team built an “AI Risk Front Door” (AI Risk Front Door) for it — a two-tier intelligent architecture that targets 85% accuracy, reducing the time from signal to work order distribution by more than 85%. Nestlé (Nestlé) has begun to use Control Tower to use AI in its operations on a large scale and strengthen governance. It is gradually deploying intelligent marketing operations in 60 countries, which is expected to reduce the cost of coordinating marketing activities by 25%. Both sides continue to drive innovation across key business functions. InterContinental Hotels Group (IHG) — one of the world's largest hotel and travel services companies — uses ServiceNow's Veza to govern “who and what” can access its systems to safely expand across 7,000 hotels worldwide. These excellent companies are making AI work for people, relying on ServiceNow's AI platform and the security of super intelligent control towers. The company sees clear momentum in AI monetization, driven by organic innovation, pricing, and intelligent packaging.

The security business is uniquely differentiated, and the potential is likely to be greater than today's overall ServiceNow in a few years. The company performed strongly in all industries, including the public sector — which once again delivered its biggest quarter of the year.

The company is not bound by computing power or capital, and is activating a hybrid business model. As can be seen from the revised full-year guidance, the company is moving from the “rule 56” to the “rule 57” and then towards the “rule 60” — the sum of free cash flow and revenue growth. The operating rate of the company's six businesses has exceeded 1 billion US dollars, and the Total Addressable Market (TAM) continues to double and expand. Few other companies can match this kind of fundamentals. As the cost of intelligence falls, the software industry's tailwind is strengthening. ServiceNow is a unique growth company. It has deep roots and a mature global distribution system within the enterprise, and implements the principle and commitment of “the world works with ServiceNow”.

Thank you for your trust and support, and I look forward to your questions. The meeting is now handed over to President and Chief Financial Officer Gina Mastantuono (Gina Mastantuono).

Gina Marston Tuono, President and CFO

Thanks Bill. The third quarter was once again strong, with all revenue and profit indicators exceeding the high end of the guidelines. Performance confirms that as enterprises shift from AI testing to large-scale deployment, ServiceNow's strategic position is becoming more prominent. Customers need not only productivity and growth from superintelligence, but also visibility and security driven by confidence. The ServiceNow AI platform is at the core of operations of the world's largest enterprises. The company is uniquely positioned to help customers apply AI to the entire business, govern the intelligence in every action, and transform intelligence into safe and measurable results.

Third-quarter subscription revenue was US$3,988 million, up 20.5% year over year at a fixed exchange rate, 50 basis points higher than the guide high-end. The RPO reached US$29.7 billion at the end of the quarter, up 22.5% year-on-year at a fixed exchange rate, and the average contract period for customers continued to extend. CrPO was US$13.65 billion, up 21% year over year at a fixed exchange rate, 100 basis points higher than the guideline. Each workflow has a wide range of needs: the technical workflow has 54 transactions over $1 million, of which 6 are over $5 million. Core workflow demand remains strong, as every new AI asset and agent brings higher management, monitoring, security, and governance requirements. Among the top 20 deals, ITSM appeared in 11 transactions and ITOM appeared in 9 (of which 14 exceeded $1 million); asset management ACV surpassed 1 billion US dollars this quarter, appearing in 13 transactions (11 exceeding 1 million US dollars); and security and risk solutions appeared in 16 (13 transactions exceeding $1 million). CRM and industry workflows continued to grow rapidly, with 13 transactions surging to 28 in excess of $1 million. The core business workflow accounts for 15 of the top 20 transactions (24 over $1 million); the Creator workflow accounts for 19 transactions (13 over $1 million). From an industry perspective, commercial and consumer services led the net increase in ACV over the same period last year; the technology industry is also growing strongly, nearly 40%. The US federal business performed well this quarter, with transactions over $1 million increasing by more than 30% year over year. As agencies increasingly view ServiceNow as an enterprise AI operating system, federal net new ACV growth is expected to accelerate further in the fourth quarter.

The third-quarter renewal rate remained the industry's leading 98%. At the end of the quarter, 680 customers had ACV exceeding USD 5 million, and in the past year, another 31 customers had ACV exceeding USD 20 million. As the largest customers continue to grow with ServiceNow, platform adoption continues to expand, with 19 of the top 20 deals involving six or more products. The momentum for AI solutions continues to accumulate: the net addition of AI ACV increased 65% year-on-year in the third quarter, causing the company to raise the AI ACV target for the second time in the year — from $1 billion at the beginning of the year to $1.7 billion by the end of 2026. The number of AI transactions over $1 million increased 4.5 times year over year in the third quarter; customers are using AI more widely in enterprises, and transactions involving five or more types of AI products increased 8.5 times year over year.

AI is used throughout the platform and is present in every workflow. ITSM's AI transaction volume increased nearly 80% year over year, and HRSD nearly doubled; Xinxing's AI solution transaction volume grew faster, ITOM grew more than 7 times, and portfolio management increased more than 6.5 times. Net new ACV for safety and risk AI increased 4.5 times year over year, App Engine AI more than 4 times, and asset management AI nearly 3 times. CRM AI also performed well this quarter, with net new ACV increasing by 2 times both month-on-month and year-over-year.

Equally important, customers are rapidly moving from adoption to production. As mentioned earlier, smart AI consumption in production environments has increased more than 13 times year-on-year since the beginning of the year. The company is committed to helping customers achieve value faster, and with the support of pre-deployment engineers, the time to value has been accelerated by 80% since the beginning of the year. For example, a European customer went online in just 12 weeks and is expected to spend nearly 1.5 million Assist throughout the year. Once deployment expertise was provided, AI adoption was twice as fast in the first five weeks after intervention.

In terms of profit, the non-GAAP operating margin was 32.5%, 150 basis points higher than the guideline, and was driven by revenue exceeding expectations, increased efficiency, and the pace of expenditure. From a productivity perspective, the company's internal use of AI now generates more than 1 billion US dollars in annualized value, which is more than double the level at the end of 2025. The profit margin on free cash flow is 20%. These results continue to prove the company's ability to strike a strong balance between world-class growth, profitability, and shareholder value.

Looking ahead, the 2026 subscription revenue guidance increased by US$15 million at the midpoint, from US$15.77 billion to US$15.785 billion, an increase of 21% year-on-year at a fixed exchange rate. The full-year free cash flow margin target was raised by 100 basis points, from 35% to 36%, driven by lower capital expenditure. In the context of investors increasingly scrutinizing AI-related infrastructure spending and leverage, ServiceNow can seize AI opportunities while reducing capital expenses and expanding free cash flow margins. The gross profit margin of subscriptions is expected to remain at 81%, and the operating profit margin is 31.5%, up 50 basis points from the previous year. Execution has completely offset the dilution brought about by this year's acquisitions, and is still expanding significantly in terms of operating profit margins and free cash flow margins, confirming the strength and scalability of the business model. Finally, the estimated GAAP diluted weighted average number of shares outstanding is 1.04 billion shares. In the fourth quarter, subscription revenue is expected to be between $4.245 billion and $4.255 billion, up 21.5% year-on-year at a fixed exchange rate; CrPO is expected to increase 18.5% at a fixed exchange rate. This reflects a higher share of locally deployed transactions and excludes the rising T4c backlog balance — both of which contribute revenue but are not included in CRPO. The expected operating margin is 32%, and the average GAAP diluted weighted average number of shares outstanding for the quarter is 1.05 billion shares.

Overall, the third quarter was another quarter of strong execution and accelerated AI adoption. What's even more exciting is the scale of the opportunity at hand. From SI Control Tower and Autonomous Security, to EmployeeWorks and a growing AI expert portfolio, the company is helping customers implement AI within the enterprise and transform innovation into measurable business results and return on investment (ROI). Equally important is helping customers accelerate adoption without losing control — this is where ServiceNow differentiates itself. By integrating workflow, data, AI, and governance into a single platform, the company helps customers navigate the complexity of the AI era while unlocking its full potential. This gives the company confidence in the huge opportunities for immediate growth and its ability to create long-term value for customers and shareholders.

Management appreciates the continued focus, execution and commitment of employees around the world. Their ability to operate with discipline while innovating is fundamental to the company's ability to deliver consistently from season to season. Now let's move on to the question and answer session.

II. Q & A session

Deutsche Bank Analyst Brad Zelnick: Results-Driven Pricing

Q: Focus on the trend of AI-native application companies implementing outcome-oriented or value-oriented pricing, and the extent to which customers are requiring companies to follow this path; in terms of financial models, the possible impact of such pricing.

A (Bill McDermott): The company has the best of both worlds: customers value the predictability of seat-based pricing; the operation of Fortune 2000 companies relies on the budget; the company provides this predictability; at the same time, it also promotes a consumption model. The idea is simple - let customers go online quickly. Once online, the token economy takes off, and the company has the opportunity to increase the revenue of a single user by 5 times, and this is only because the customer has received far more value than this, which is a win-win situation.

It should also be pointed out that with the release of Flow, an independent AI-native autonomous service desk provider is no longer needed, as the company has delivered this capability globally, and customers can buy it online and go live on the same day. This will be another net addition to the company's ACV engine, which is clearly a challenge to competition.

What is noteworthy about the super intelligent control tower is that its activated AI actions increased 500% month-on-month, adding up to a 13-fold increase in AI consumption. The company is benefiting from the current model — 21% year-on-year growth, and this “hockey stick” growth pattern has yet to be fully realized. This is another exciting point for investors to think about.

A (Gina Marston Tuono): As far as the impact of the financial model is concerned, the customer is very focused and satisfied with the current hybrid model and is not asking for results-oriented pricing. If the future landscape changes, the company is ready and waiting; but for now, customers are very satisfied with the hybrid model.

Wolfe Research Analyst Alex Zugin: CRPO and Growth Confidence

Q: Focus on some of the minor impacts in the fourth quarter CrPO and subscription revenue guidance. Stock prices fell significantly after the market due to fourth-quarter guidance, further explaining the confidence that growth will remain high or rise further (especially next year).

A (Gina Marston Tuono): The company remains as confident as ever about growth opportunities. All indicators exceeded expectations — revenue, CrPO, operating margin, free cash flow, and increased free cash flow profit margins.

Regarding revenue exceeding expectations: The company passed half of expectations in the third quarter (along with all exchange factors and exceeding expectations by half) to the full year guidance. There are two reasons why the full increase was not made. First, at the size of the company, the growth rate is still very strong; however, to help customers achieve value faster, the company makes strategic decisions to invest in customer success by incorporating delivery expertise into platform solutions to accelerate AI deployment for some large-scale transactions.

From an accounting perspective alone, the value of these deployments was stripped from subscription revenue and included in professional services rather than subscription revenue. Notably, when contracts are renewed, the value of these services will return to subscription revenue, creating a structural acceleration of growth. That amount is small — around 25 basis points for the third quarter and 50 basis points for the fourth quarter, which is the only reason why the third quarter did not fully exceed expectations into full-year guidance. As a result, subscription revenue is strong enough.

Regarding CrPO, there were strong early contract renewals in the third quarter, which exceeded expectations for the quarter. This had a negative impact on the fourth quarter, as these transactions were brought forward from the fourth quarter to the third quarter, and their growth was included in the third quarter. Another factor: Strong public sector demand drove up the share of local deployment in the fourth quarter — a good result, but it was a headwind of 25 basis points against the fourth quarter CrPO, but it would completely translate into revenue. Furthermore, incremental investment in deploying expertise has a slight headwind against RPO and does not affect revenue in the long run.

Looking at it more broadly, cRPO is a very delicate accounting indicator that may not fully reflect the full momentum of the business. For example, the year-on-year subscription backlog growth of about 50 basis points in the fourth quarter was excluded from the CRPO due to T4c terms, but will be fully factored into revenue. Therefore, although CrPO is a good indicator of next year's revenue, it is by no means perfect. The momentum that is being shown in the business—particularly around various AI advances—will definitely translate into strong revenue growth in 2027 and beyond. At the end of the day, the company is more confident than ever about growth opportunities.

Morgan Stanley Analyst Sanjit Singh: AI Momentum and Revenue Acceleration

Q: The AI ACV target has been raised twice to US$1.7 billion during the year, while the overall CrPO is generally stable, and the organic caliber has slowed slightly. Focus on when AI momentum will begin to be transformed into an acceleration of overall revenue and CRPO; in terms of market entry (go-to-market), pricing and packaging have been adjusted and doubled in delivery. Whether AI and sales are in place, there is still room for improvement.

A (Bill McDermott): Business has never been better. One of the major advantages of having a super intelligent control tower is that every partner — whether it's a hyperscale cloud vendor or lab company, from Nvidia to major laboratories — is allied with ServiceNow and realizes the importance of creating enterprise value for their customers through super intelligent control towers. The network effect is entering a very high level, which is a significant kinetic energy advantage the company is experiencing.

The company knows the importance of getting customers online quickly, and customers now need to derive value from AI. Therefore, as stated by Gina, the company has made the necessary strategic decisions to enable customers to go online quickly, so that they can not only benefit from licensing, but also activate tokens and create the token economy expected by shareholders and their own shareholders. This virtuous cycle is entering the high-end — super intelligent control tower activity increased 500% month-on-month, and AI consumption increased 13 times. The strategy is working, and everything is still in its early stages.

Part of the acceleration can be seen now. The real acceleration will occur in 2027, as described by Gina, because the key is for customers to complete implementation and activate tokens in their workflows or business processes. The company and ecosystem have made decisions on this because this is where long-term value is created — for the company, shareholders, and most importantly for customers.

A (Gina Marston Tuono): Looking back at Financial Analyst Day's statement: By 2030, the AI business will account for 30% of the company's ACV. The company is on track to achieve this goal steadily and even ahead of schedule, as can be seen from the continued increase in AI goals.

J.P. Morgan Analyst Samick Chatterjee: Investment Customers Accelerate AI Adoption

Q: Regarding strategic decisions to co-invest with customers to accelerate AI adoption, was there any investment in the third quarter; were there early data points in these collaborations to support confidence in expanding AI adoption, and what are the ideal metrics to measure results.

A (Gina Marston Tuono): The AI market is changing rapidly, and so are companies. According to the data, the AI adoption progress of supported customers was twice as fast in the first five weeks, and the amount of Assist consumption and product usage was several times higher than that of unsupported customers. Assist consumption and product usage are the metrics to focus on. As customers' AI spending accelerates, as expected, it unlocks significantly greater monetization opportunities, making ROI extremely attractive. As a result, the company is including more such deployment teams in the forecast because the results are encouraging.

A (Bill McDermott): Another point worth noting is the Sweep acquisition. It's often difficult for customers to switch from one CRM to another because of the long implementation cycle, and no one wants a long implementation cycle, especially when it comes to serving customers. Today, CRM deployment time has been drastically reduced — no longer in years, but in months and days, 30 or 60 days for real large-scale enterprises. The same logic also applies to various workflows such as enterprise super intelligent control towers and ITSM, which can be activated within 24 hours.

What is currently being built is a completely open ecosystem, injecting the “rules and tracks” of enterprise operation, connecting the woven structure of data and processes, and advancing at a record pace. This will push the implementation cycle to record speed, which is necessary for tokens to be fully consumed, activated, and generated revenue.

No other company in the enterprise software industry is growing by the “Rule of 57” — increasing revenue by 21%, increasing free cash flow by 36%, and building the world's best super-intelligent control tower to date. If you have a company like this, it's worth sharing best practices with them.

Bernstein Analyst Peter Weed: Internal Productivity and Staffing

Q: Focus on the company's investment in internal productivity optimization, and how this is reflected in the number of personnel — much of it seems to focus on front-office products and sales and marketing; how to achieve target productivity in these areas, and these will also be factors driving future revenue.

A (Gina Marston Tuono): The company achieved more than $1 billion in efficiency gains through internal use of AI, the vast majority of which came from the use of its own product “Now on Now.” Efficiency gains mean there's no need to hire that many people, yet the company is still hiring for key positions. Although the total number of sales and marketing personnel has declined, the number of sales people with quotas has achieved double-digit growth, while jobs such as sales operations have declined significantly.

R&D organizations are the same: Top talents such as AI engineers have actually increased, and at the same time, large efficiency benefits are driven through AI, which means there is no need to hire as many support personnel or management expenses of R&D organizations. The company is still fully recruiting in the two major fields of market entry and R&D. However, recruitment is in the right position, while operational and logistics positions have declined significantly due to amazing efficiency.

A (Bill McDermott): The company uses its own EmployeeWorks solution internally. Every employee in the market entry system — the best in the industry — has a “coach”, called EmployeeWorks, who independently activates all the controls needed to build customer relationships and bring innovation to customers without requiring active employee requests; insights are also pushed to the front line to improve productivity. Three years ago, about 100 people in the sales and operation department relied on emails to circulate information, but now they are completely autonomous and have become a “sales coach in your pocket”, driving huge productivity. At the same time, the number of frontline workers (feet on the street) has increased significantly, while the overall number has declined slightly — this is an ideal situation. 90% response time for customer service or employee service inquiries is now self-completed, and the employee experience has improved dramatically.

Even though the number of people remains stable, the company is strengthening its talent pool: continue to bring in net new top talent on the AI innovation side and on the quota side, and set higher standards for the talent needed. With a stable population, the quality of innovation and human capital has improved dramatically — this is sometimes not reflected in numbers.

William Blair analyst Arjun Bhatia: Is AI cannibalizing or incremental

Q: One of the core debates among investors is whether AI is encroaching on software companies or increasing them. In the current results, AI uses acceleration and guidance for upward adjustments, while some other indicators have not reached an inflection point or have a time lag. Focus on changes in overall ServiceNow spending by early adopters and cutting-edge AI customers after adopting Now Assist and AI capabilities.

A (Bill McDermott): Global GDP is being built on superintelligence, and looking back ten years from now, this smart generation will be viewed as a “revival moment.” All business cases relating to the return on investment (ROIC) of AI are 10 times greater than any previous AI solution.

Take the company itself, for example: $1 billion a year is a huge amount of money, and the company's operating performance is astonishing—maintaining the same growth rate as before the $1 billion savings on a larger base, completing extraordinary work with fewer people, and being able to take the pressure off and focus on what really matters because of the autonomy of the AI platform. The company is a living example of this. The business cases that the company, Amit, and Paul review on a daily basis are all 10-fold improvements compared to what was previously seen.

A (Amit Zaveri, President, Chief Product Officer and COO): Regarding use cases and adoption growth: Many customers usually start with one or two use cases, such as incident management, tiering, or solution planning. Once online, usage can be increased to 3 or 4 times, and new use cases continue to emerge as customers see results in production environments. Many of the customers mentioned in the last quarter and this quarter are renewing licenses and renewals with higher tokens because adoption is rising.

For example, Nestle's marketing optimization intelligence workflow, which went live in six weeks, has now been rolled out in 90 countries, and is significantly increasing the value of a single use case globally.

This is a common pattern. The company is also seeing an extension of autonomous IT, AIOps, CRM optimization, and other industry/industrial use cases. The growth path is clearly visible.

Jefferies Analyst Samad Samana: AI Deployment Resource Allocation for Large Customers

Q: Decisions about allocating resources to large customers to accelerate AI deployment — when to make that decision, how should it be modeled, whether it is widely available or customer-specific, and factors to consider in revenue recognition and profit margins, and explain the relevant assumptions in the forward-looking guidance.

A (Gina Marston Tuono): The AI market is changing rapidly, and so are companies. When it saw a real inflection point for supported customers, the company decided to double its investment because the consumer flywheel would drive significant incremental growth. Deployment times improved rapidly, and these services, as described above, were only used for some large transactions — 25 basis points in the third quarter and 50 basis points in the fourth quarter. The company does not expect to include this delivery expertise in the long term. As with any other new technology adoption cycle, the key is to optimize the first adopters and utilize adoption in a way that can be reused previously. As AI advances, autonomous deployment capabilities are becoming easier, so this is not expected to be a long-term arrangement, but it is definitely the right move and will continue to drive the consumer flywheel.

A (Amit Zaveri): The company also uses AI to implement agents to build deployment capabilities. When helping customers go online, a lot of rework is done by AI. The core is to identify early use cases and simplify the launch. As soon as customers bring one or two use cases online, usage quickly climbs. So this is not a long-term partnership, but a very short-term, rapid process of creating value for customers.

Evercore ISI Analyst Kirk Marten: Control Tower Orchestration Layer Deployment Pace

Q: Focus on the process of enterprises preparing to build an orchestration layer to manage smart devices on a large scale — whether to build now or wait until more production is deployed; and the evolutionary path where customers first establish a baseline and wait for the smart group to grow before driving consumption.

A (Bill McDermott): At a macro level, super intelligent control towers are redesigning the visibility, governance, and security posture of these large enterprises. As can be seen from the various collaborations announced today (OpenAI in particular), the world's best and smartest companies all recognize that activating the control tower on top of the definitive “rules and tracks” that businesses rely on to operate is critical to business growth.

A (Amit Zaveri): The common concerns of customers last year were: they didn't know anything about the progress of AI, how many shadow projects there were, and what the intelligence was doing. Therefore, when Control Tower was launched last year, the response was excellent because it was placed before AI was deployed as a governance, trust, and security layer, giving the system the ability to be trusted. As the company builds discovery capabilities for multiple third-party AI systems and any self-built AI agents, customers get a single platform for monitoring and management (including costs), and can terminate any agent that acts beyond its authority.

It has become an important part of the governance layer and the runtime layer, which is the difference — it enters production before AI, and usage naturally rises as customers build confidence and build more AI. The key is visibility, control, and security, not the orchestration itself; under this, the company can orchestrate many matters according to the systems used by the customer.

This is the customer's primary upfront investment, unlocking significant value for the company's future. It is built on the core competencies of CMDB and asset management, and incorporates the ability to govern physical assets, physical AI, and non-human identities. This resonates and works well for customers looking to adopt AI on a large scale.

A (Bill McDermott): Take Accenture (Accenture) as an example — with over 800,000 employees. Today, every corporate function operates on ServiceNow, using the Control Tower to manage nearly 900 ServiceNow native AI assets, measure the business results of various departments, and achieve a significant increase in productivity in large-scale enterprise adoption of intelligent AI.

Another global technology leader, is driven by Armis and Veza — which not only manage the identity of people (employees) and agents, but also ensure the safety of the company's operating technical environment (network, equipment, critical infrastructure, etc.), reduce service costs, increase productivity, and fix problems at machine speed. This will be the main theme that will continue to appear. The company originally had around 80 different security tools, which was quite a dangerous situation.

Nestlé has also expanded its ServiceNow footprint through the perspective of a super intelligent control tower, operating governance in a large complex global enterprise. All of its operations are governed by super intelligent control towers, and the cooperation between the two parties has only just begun. The opportunities ahead are vast, and the company is ready to fully advance.

A (Amit Zaveri): Add one more point: by combining discovery capabilities with SecOps products built over many years, you can achieve discovery, prevention, and active repair within a single platform. By combining the control tower with SecOps, Veza, and Armis, you get a platform with full visibility and the ability to “save when it happens”.

Wells Fargo analyst Michael Turin: The tone of IT budget discussions

Q: At the beginning of November, focus on the tone of the overall IT budget discussions you've heard, ServiceNow's positioning (especially where Armis and smart products fit), and the impact this has on the company's priorities at the end of the year and 2027.

A (Bill McDermott): The key is strategic relevance — the company has a record system that has been trusted for decades, and the net new innovation from ServiceNow is impressive.

Irrelevant solutions or single point solutions will be eliminated, and strategically relevant platforms will not only perform well, but will do much better, especially those that are relevant in the super-intelligent era. The company's pipeline is growing extremely well. Super Intelligent Control Tower, Veza, Armis, MoveWorks — Generating $100 million in ACV in three quarters, all of these businesses far surpassed expectations at the time of merger, as did Logik AI. The company is building a large number of innovations, making the right strategic choices to complement its own research, and is well recognized by customers.

The biggest opportunity now is to walk up to customers and let them fully understand the value — customers are being impacted by all parties, but the only constant demand is “ROI now.” The company has gone through the proof-of-concept stage, testing phase, single-point solution, vibe coding, or DIY stage, and is now in a serious enterprise-level stage: getting things done and delivering real value. This platform is one of the few that can excel now and in the future.

Needham Analyst Matt Calitri (Mike Cikos): Monetizing Action Fabric

Q: Regarding the monetization of Action Fabric, in particular the expansion of cooperation with OpenAI - what are the differences between early adopters using EmployeeWorks and those using external agents, and what is the meaning of monetization.

A (Amit Zaveri): The company's philosophy has always been to provide customers with choices: customers should be able to use any tool to access ServiceNow capabilities and perform actions (actioning), which is the differentiating advantage. Through Action Fabric, customers can build any interface through interaction between MCP and A2A. The partnership with OpenAI made ChatGPT a way to access ServiceNow, but all the work is done within ServiceNow; ChatGPT only initiates calls. Work that was originally done through its own experience is now carried out through this interface, and the company derives full monetized value from it — because every request for ServiceNow to complete the work consumes Assist. The job couldn't be done anywhere else because the company had the context, ability to understand intent, connectivity to all third-party systems, and workflows already running within the enterprise customer ServiceNow.

As a result, the company is opening up a variety of ways to access ServiceNow and using this to obtain monetization opportunities that go far beyond simply providing its own interface. EmployeeWorks is another option, but its capabilities far surpass ChatGPT or Gemini Enterprise—the latter is just the caller; EmployeeWorks undertakes extensive reasoning, orchestration, planning, and provides professional intelligence, giving employees capabilities far superior to those of other third-party front desks.

EmployeeWorks has a lot of built-in differentiation, but the company also allows customers to access in another way through Action Fabric and continue to obtain value and continue to monetize their ServiceNow investments, thereby increasing revenue through many mechanisms. The partnership with OpenAI has broad prospects. Both sides will deliver a large number of skill-based capabilities, while the other side relies on the company to actually complete the work — value is created from this.

A (Bill McDermott): ServiceNow is essentially an execution layer, an execution layer for the entire AI economy. As can be seen from today's announcement and more collaborations in the future, this is not only a place where the work is completed, but also a gathering place for everyone in the enterprise to do business with every smart body — this is a huge market, and the company is at the center of it. As proof, Action Fabric's Assist grew 500% in less than 30 days, expanding extremely fast. This represents a business model innovation that will become much larger than today's entire ServiceNow in a very short time.