By: Amit Verma, Specialist – Software Engineering, Automation COE (ACE), LTIMindtree

Introduction

The technology of generative AI (GenAI) is at the forefront of innovation, bringing about significant changes in various industries, including IT. With the ability to create content on the fly, generative AI is a must-have technology that can help organizations drive innovation. It can also help streamline processes and transform operations.

ServiceNow, a popular cloud-based workflow automation platform and a leader in innovation, recently announced its generative AI capabilities at its annual event, Knowledge 2023. These capabilities come with compelling use cases such as content summarization, Now Assist for search, content generation, and many more to follow. With the introduction of GenAI capabilities to the ServiceNow platform, how users interact will change significantly.

GenAI capabilities in ServiceNow can be used for various modules, such as IT service management, customer service management, and knowledge management. We can offer designed and contextually fitting customer experiences by examining historical data with personalized responses, recommendations, and solutions. It can also help human agents step up and take on more important tasks with the help of generative AI capabilities in the ServiceNow Virtual Agent.

Let’s understand in detail about GenAI and how ServiceNow’s GenAI capabilities can help us drive business more efficiently and effectively.

What is generative AI?

Before we dive into ServiceNow’s GenAI capabilities, let’s understand this booming term. An intelligent computer system or algorithm can create content with little or no human oversight. The content could vary from precisely written articles to images to video clips. It can mimic human intelligence and thought processes by learning through the patterns and actions from training data.

Unlike traditional AI, generative AI can learn on the fly from the datasets available and generate original content. It works on deep learning techniques like neural networks and reinforcement learning, through which it can generate new content by analyzing patterns and information.

Generative AI in ServiceNow

ServiceNow introduced a GenAI Controller and Now Assist for search. These tools allow enterprises to plug in one of the GenAI tools, such as OpenAI, Microsoft Azure OpenAI, or ServiceNow proprietary Large Language Models (LLMs) into the ServiceNow platform. This allows users to leverage AI without complex integrations or platform changes.

LLM integrations enable seamless utilization of GenAI capabilities within existing flows or workflows. This enhances search functionalities, personalized user experiences, and interactions, thus improving user experience. With Now Assist for search powered by GenAI, users can get specific and targeted answers to queries. The responses are quick and accurate, and the interactions are smooth.

A practical example of a ServiceNow Generative AI Controller could be an implementation of a flow that can summarize long incident descriptions during incident creation. The summarizing capability of the Generative AI Controller helps generate a summary of the incident description. This summary can then be pushed as a work note on the incident, helping agents identify the reported problem and work towards resolution quickly.

Service request data can be analyzed by GenAI to identify common patterns and suggest opportunities for automation. It can be implemented to guide users in decision-making by providing insights based on historical data analysis, market trends, and customer behavior. Organizations can make well-informed decisions that drive growth and success in their business with the help of this tool.

ServiceNow GenAI can help an organization improve the overall business process by identifying gaps and suggesting steps to bridge them. It can be a real game changer for organizations that want to innovate and deliver a remarkable value add to their customers. However, organizations that want to implement ServiceNow GenAI face several challenges and considerations.

Challenges and risks associated with implementing generative AI in ServiceNow

• Data privacy and security ─ Organizations must take steps to safeguard the data fed to the generative AI language model from unauthorized access. Strict data privacy and security measures must be ensured to prevent data breaches and data integrity violations.
• Technical challenges during implementation ─ Optimal performance of any generative AI implementation requires overcoming challenges like data quality, algorithm selection, and model stability.
• Hallucination ─ Generative AI can produce false narratives. It can also generate unacceptable or biased data depending on the data it is being fed.
• Lack of transparency ─ Understanding the source of the data generated by the generative AI is cumbersome, and some organizations might need to know to establish authenticity.

These risks could be mitigated by considering some of the best practices that ensure responsible and effective utilization of Generative AI.

Best practices for generative AI implementation in ServiceNow

• Understand common failure modes and workarounds ─ The output generated by the generative AI models can introduce errors or provide junk data. We must understand the common failure modes and develop workarounds to fix these issues. This can involve refining input prompts, adjusting parameters, or employing post-processing techniques to improve the quality of content generated.
• Check data output for accuracy ─ Organizations should ensure that the output generated by generative AI models is accurate and transparent. Models should be continuously assessed and fine-tuned for accuracy.
• Be vigilant for biases – Organizations should always identify any preconceptions or prejudices in the content generated. If found, measures should be taken to overcome them.

Conclusion

Generative AI from ServiceNow has the potential to enhance productivity, streamline workflows, and create a great customer experience. While its capabilities are significant, implementing ServiceNow’s GenAI comes with challenges, and some considerations are inevitable. We need to ensure that our data privacy is maintained, i.e., our sensitive and confidential data remains protected from unauthorized access and breaches. We do need to take into consideration the false narratives being produced by the GenAI models, which could be biased and irrelevant.

GenAI presents ample opportunities to ServiceNow platform users, provided its capabilities are harnessed judiciously, and the challenges discussed above are addressed well. It can open gates to several new opportunities for innovation and increase customer satisfaction.