If data truly powers generative AI, then access to relevant business data is crucial for successful implementation. Certain SaaS providers, like ServiceNow, inherently benefit from this advantage as they leverage their own platforms to enhance business-focused AI models, setting the stage for effective execution.
For ServiceNow’s Chief Customer Officer and former CIO, Chris Bedi, creating practical experiences that improve efficiency is key. “A model is only as effective as the platform it operates on. If it’s not integrated into a user experience or workflow, it loses its purpose,” Bedi explained.
Brent Leary, the founder and principal analyst at CRM Essentials, noted ServiceNow’s intentional focus on practical AI applications. “By developing a full-stack generative AI platform, ServiceNow can concentrate on optimizing workflow creation and integration, which can positively affect processes across various departments and platforms,” Leary stated.
ServiceNow is embedding AI into all its workflows, and Bedi categorizes its generative AI capabilities into three main areas:
1. Systematic Request Handling: Bedi emphasizes the importance of addressing requests efficiently, whether they come from customers, suppliers, or employees. “We aim to expedite responses for all requesters,” he said.
2. Agent Support Enhancements: The second area focuses on empowering agents, regardless of their specialization. “HR, IT, customer service—regardless of function, we aim to help agents perform repetitive tasks faster or transfer those tasks entirely to automated systems, yielding significant productivity improvements,” he explained.
3. Accelerating Innovation: Lastly, Bedi envisions a future with transformative automation capabilities, such as converting text to code or automating workflows. This could include allowing users to turn images of diagrams or brainstorming sessions into actionable workflows.
Adopting a Comprehensive AI Strategy
ServiceNow is implementing a multifaceted AI strategy through a balanced approach of building, acquiring, and partnering, according to Holger Mueller, an analyst at Constellation Research. “ServiceNow’s diverse strategy is essential as its customer base has a wide range of AI partnerships that the company must cooperate with,” he mentioned. Partnerships with leading firms like Nvidia and Microsoft are among these collaborations. Additionally, the company aims to develop its own AI solutions to offer out-of-the-box experiences while augmenting this with acquisitions.
With customers at varying stages of AI readiness, ServiceNow must provide a range of solutions tailored to these capabilities. Jeremy Barnes, VP of AI product at ServiceNow, emphasized the need for flexibility. “Leading companies have largely mastered the necessary organizational transformations for digital transformation,” he said. However, for those still progressing, ServiceNow combines its solutions with support from Independent Software Vendors (ISVs) and Managed Service Providers (MSPs) to assist them in effectively harnessing AI.
Financial analyst Arjun Bhatia from William Blair observes strong customer willingness to invest in ServiceNow's new AI capabilities. “Demand for the new Pro-Plus SKUs has been notable, and enterprises are looking at generative AI as a key investment area,” he wrote in a recent report. Moreover, minimal pushback on pricing indicates that customers recognize the value.
Adapting to Customer Needs
IDC analyst Stephen Elliot highlights that ServiceNow has been investing in generative AI and acquiring talent for over five years, and clients are now reaping the benefits. “Users of Now Assist report promising outcomes, including ticket deflection, enhanced knowledge base summarization, and improved virtual agent experiences. Cost savings and increased productivity are central themes of their business value realization,” Elliot noted.
Bedi categorizes AI initiatives into two perspectives: short-term improvements and the long-term potential of AI. “Mode one focuses on enhancing existing workflows,” he explained. This reflects how companies currently utilize AI technology to streamline operations. However, the real transformation lies ahead. “Mode two envisions starting from scratch to redesign processes according to AI capabilities,” he said.
ServiceNow also leverages AI internally, employing a platform called AI Control Tower to provide a cohesive development environment for internal applications. “Our goal is to empower engineers to select models freely without unnecessary management burdens,” Bedi outlined.
From an IT management standpoint, ServiceNow treats AI models as integral assets that require operational resilience and a proactive cyber posture. “Each model in production is an asset, and we ensure they are effectively managed and monitored for performance,” Bedi added.
As Barnes further elaborated, ServiceNow aims to cultivate a greater focus on AI among its customers. “We’re transitioning from core generative AI use cases to rethinking the entire work process,” he said. This includes the potential to tackle more complex tasks with advanced tools, facilitating collaboration between AI and human contributions to optimize productivity.
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