ServiceNow Launches Expansion to Now Assist Generative AI Offerings

ServiceNow Launches Expansion to Now Assist Generative AI Offerings

The News: ServiceNow announced in early November the general availability of three generative AI-based enhancements within the Now Assist portfolio, including Now Assist in Virtual Agent, flow generation, and Now Assist for Field Service Management (FSM). These capabilities are being positioned as helping organizations’ workers operate more efficiently, while letting workers and customers access and interact with data and processes more seamlessly and naturally, thereby removing friction points between humans, information, and workflows. You can read the press release highlighting the generative AI feature expansion on ServiceNow’s website.

ServiceNow Launches Expansion to Now Assist Generative AI Offerings

Analyst Take: ServiceNow announced the availability of several generative AI capabilities within the company’s Now Assist portfolio, including Now Assist in Virtual Agent, flow generation, and Now Assist for FSM. The general availability of these capabilities will allow the company’s customers to access a natural language-based generative AI interface that allows users a seamless and intuitive way to access and interact with information held within the platform. While each feature is addressing a specific productivity or task, the new generative AI enhancements are designed to work together across the entire ServiceNow platform.

Quickly Stand Up Intelligent, Self-Service Experiences

Now Assist in Virtual Agent enables customers to integrate relevant information or actions from their knowledge base and service catalog to quickly deploy more advanced, generative AI-powered chat-based self-service experiences. The new updates for Now Assist in Virtual Agent include support for Q&A in Knowledge Management and multi‑turn conversations for ordering catalog items or making service requests, with the ability to provide additional information directly within the chat.

The last element – support for multi-turn conversations when ordering items or making service requests – is a clear example of how vendors are working to offer generative AI-based conversation technology that lets self-service interactions begin to mimic the feel of human interactions. By enabling a less-formal, more natural style of conversation that can understand intent, human customers are more apt to use the technology to solve their problems instead of asking to speak with a live agent.

Using Natural Language to Build Workflows

A key challenge in today’s enterprises is efficiently building workflows and automations. Developer expertise and time is limited, and ServiceNow’s flow generation enhancement is designed to address these resource scarcities by facilitating the conversion of plain text into low-code workflows. As such, developers do not need to create workflows from scratch, thereby significantly improving the time to value for businesses for new workflow generation while reducing automation backlogs.

Supporting Field Workers via Generative AI

Now Assist for FSM is designed to use generative AI to let field workers access all relevant activity, parts, and incidental work data, while providing concise summaries of work order tasks. This feature is particularly vital for field technicians who are not accessing data from a static system or who frequently move between sites and are relying on mobile devices to complete their work.

ServiceNow Leveraging Generative AI to Break Down the Walls Between Humans and Information

ServiceNow’s recently announced generative AI capabilities are reflective of the company’s goal of removing the barriers or friction between workers and the information they need to do their jobs or the walls that make it challenging for customers to interact with businesses. Where ServiceNow seems to have an advantage is that it is going all-in on the idea that generative AI technology, automation, and information should be consolidated on a single platform.

In addition to the corporate benefits of consolidation (reduced technical debt, ease in tightening cybersecurity and data security risks, reduced training, and maintenance costs), the use of a single platform for core tasks will help drive exponential benefits of using generative AI. As generative AI models are deployed, they will not only be trained on and continuously learn from the target data but also be working within a seamless and fully integrated environment that has baked in AI across the entire platform.

This platform-based approach enables generative AI to be seamlessly infused across all workflows, which should result in better and more intuitive experiences, regardless of a worker’s role, the type of activity being carried out, or the type of data being accessed. This approach will continue to become increasingly important as the lines between various departmental functions increasingly are blurred and simple access to data and processes becomes the catalyst for excellent customer experiences.

Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.

Other Insights from The Futurum Group:

ServiceNow Announces Expanded GenAI Tools

ServiceNow Announces AI Lighthouse Program to Fast-Track GenAI Adoption

ServiceNow Revenue Up in Q2 2023 to $2.15 Billion, Beating Estimates

Author Information

Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.

He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.

In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.

He is a member of the Association of Independent Information Professionals (AIIP).

Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.

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