ServiceNow expands platform with additional generative AI capabilities to ease enterprise productivity   

Low-code enterprise automation company ServiceNow has announced the expansion of its Now platform’s generative AI capabilities, introducing case summarization and text-to-code features. The company said these advancements aim to drive speed, productivity and value for customers across various industries.

According to the company, the gen AI capabilities are purpose-designed to alleviate repetitive tasks and improve productivity.

The Now platform’s case summarization automatically distills crucial information from IT, HR and customer service cases, streamlining resolutions. Additionally, text-to-code converts natural language text prompts into executable code for the ServiceNow platform, providing developers with an optimized and efficient way to create code.

“By infusing generative AI features into the fabric of the Now Platform and all ServiceNow workflow offerings, we aim to help customers drive business value from a single source,” Jon Sigler, VP of Now Platform at ServiceNow, told VentureBeat. “The ServiceNow large language model (LLM) was specifically developed to comprehend the Now Platform, workflows, automation use cases, processes and more, ensuring higher accuracy and performance for ServiceNow use cases and increased trust.”

Powered by strategic partnerships

Sigler emphasized that strategic partnerships and collaborations with tech giants such as Nvidia and Hugging Face drove the company’s exclusive ServiceNow LLM development. These alliances actively expedited the advancement and integration of enterprise gen AI capabilities, merging cutting-edge research, advanced AI infrastructure and expert domain knowledge.

“Our strategy is to accelerate the development and deployment of highly effective and specialized language models to unleash the true potential of generative AI for the enterprise,” Sigler told VentureBeat. “Through our work with Nvidia, we’re developing powerful, enterprise-grade generative AI capabilities that can transform business processes with faster, more intelligent workflow automation. We also continue to partner with research organizations like Hugging Face to establish new, responsible AI practices to train and share large language models.”

In collaboration with partners Nvidia and Accenture, ServiceNow also recently unveiled the AI Lighthouse program. This initiative is tailored to enable customer companies to develop their gen AI applications swiftly, bypassing the need for protracted assessment and procurement processes.

Through the AI Lighthouse program, customers will access ServiceNow’s enterprise automation platform and engine, as well as Nvidia’s AI supercomputing and software, complemented by Accenture’s consulting and deployment services.

Leveraging generative AI to drive enterprise productivity 

ServiceNow said that case summarization enhances efficiency and expedites customer outcomes by distilling vital information from case details, prior interactions, actions and resolutions. This automation facilitates swift hand-offs between internal teams, boosts productivity and delivers streamlined resolutions for customers and employees.

“We are tapping into the power of generative AI to analyze and provide case summaries in seconds,” Sigler told VentureBeat. “Through our initial use of our generative AI tools internally, we’re seeing agents spend 30% less time getting up to speed on a case and 42% less time writing case resolution notes. The new offering will remove the tedium from the reporting process and speed up issue resolution to boost agent productivity and provide better customer experience.”

Likewise, text-to-code aims to empower developers with a time-efficient approach to creating code for routine commands. By composing plain, natural language text descriptions, developers harness gen AI to receive high-quality code suggestions and complete code, thereby improving code hygiene, accuracy and quality. 

Streamlining coding

The company asserts that this integration of AI technology will streamline the enterprise coding process, making it more accessible and effective for developers.

“Text-to-code boosts productivity for both pro and low-code developers, as it mitigates repetitive and time-consuming work, especially given developers tend to create the same code for common commands,” said Sigler. “Developers can write plain text descriptions of the type of code they want, and generative AI within the Now Platform will convert the text into high-quality code suggestions and share it in-line for developers to review and implement.” 

The new functionalities rely on a proprietary ServiceNow LLM specifically developed to comprehend the Now Platform, workflows, automation use cases and processes.

“Unlike many generic large language models, StarCoder is carefully trained and fine-tuned using a vast amount of proprietary enterprise data from ServiceNow,” Sigler explained. “We believe that it will increase the productivity of every user who uses the ServiceNow platform across the organization.”

The LLM, derived from the 15 billion parameter StarCoder LLM, originated from the ServiceNow co-led, open BigCode initiative. It underwent training and tuning using Nvidia accelerated computing, including Nvidia DGX Cloud.

What’s next for ServiceNow? 

Sigler stated that the company is actively exploring how gen AI can enhance its sales teams’ efficiency in onboarding and promptly addressing product-related inquiries. Additionally, it aims to accelerate employee growth and career development by implementing gen AI.

Sigler also outlined ServiceNow’s future strategy, which involves integrating gen AI throughout the Now Platform. He said the company aims to enable its customers to swiftly operate with intelligence at scale, fostering gen AI-powered innovation across all aspects of their businesses.

“We believe that generative AI will play a transformative role in enabling intelligent automation, powerful problem-solving and personalized experiences for our customers, and we are intent on providing that for them in the most efficient way possible,” Sigler added.