Artificial intelligence use has surged in recent years, from college students using ChatGPT to write essays to organizations across industries adopting generative AI and AI agents. According to a 2024 McKinsey survey, 78 percent of respondents reported using artificial intelligence for at least one business function. That’s an increase from just 56 percent of businesses in 2021. As businesses find more ways to implement artificial intelligence to improve their processes, the need for improved functionality is also climbing.
In an episode of The Distillery Podcast, Nate Weldon introduced ServiceNow’s new Yokohama release and the artificial intelligence features users will be able to implement on their platforms. Nate is the senior vice president of technology at Cask NX and has a wealth of experience in ServiceNow, both as a user and a partner. He used ServiceNow in his work with a life sciences company for six years before joining Cask NX, where he has utilized ServiceNow as a partner for 11 years. Here are some of the highlights Nate says users can look forward to with the release of Yokohama and its artificial intelligence capabilities.
Enhancing automation with agentic AI
With the Yokohama release, clients will see significant advancements in agentic AI, i.e., artificial intelligence agents that can operate autonomously or with supervision. The agentic AI is designed to handle decision-making processes for organizations using machine learning and historical data. Nate says these tools will give clients powerful tools and capabilities that can improve processes and efficiency.
Trust is a key component that is necessary for these capabilities to truly benefit business. Clients need to trust that their data is being handled securely and that the agent AI is producing sound results. Without trust in automation agents, driving adoption can be a difficult task. “ServiceNow is the enterprise AI provider that I think most organizations are going to be willing to accept and trust with their data,” Nate says.
To ensure successful adoption of agentic AI capabilities, organizations should take a measured approach to build confidence in the tool and build a strong base of historical data to drive trustworthy results.
Ensuring data quality
While AI capabilities continue to evolve, the effectiveness of these tools ultimately depends on data quality. Poor data—such as incomplete records and vague descriptions—can lead to AI “hallucinations,” i.e., false responses. The agents need quality foundational data, especially when it is only relying on internal data to formulate responses. “Sometimes when the AI is generating its response, it can, for all intents and purposes, make stuff up,” Nate says. “So we want to avoid that. We don’t want an agent making stuff up on our behalf that could impact our business.”
Inaccurate outputs from AI can have significant consequences, including poor business decisions, repetitional damage, and even security risks, Nate says. To avoid a “garbage in, garbage out” result with artificial intelligence, organizations must ensure that the right historical data is brought into the system and verify that the data is producing good results before going further.
On the other hand, artificial intelligence systems offer the best results with a large quantity of high-quality data. Tools in ServiceNow give clients greater power to access their best data and use it to build better agents. The Yokohama release will include the Workflow Data Fabric tool, which enables companies to integrate and access data from multiple sources without physically moving it, thanks to its zero-copy data connector capability. This tool will give clients the ability to bring in even more data from various silos to power AI agents with a deep reservoir of accurate historical data.
By prioritizing data integrity, businesses can maximize the potential of ServiceNow’s AI capabilities and ensure more reliable, impactful outcomes.
Taking a “crawl, walk, run” approach
It’s natural to want to jump right in with new features like the AI capabilities Yokohama provides. However, Nate stresses that it is important for clients to take a more measured approach when beginning anything new. “Understand what your business goals and what you want to accomplish, and plan these things out before you even touch ServiceNow,” he says. “Know what you want the end result to be.”
Cask frequently advises clients to think of projects with a “crawl, walk, run” mindset. Rushing into implementing new features like AI without a clear strategy can lead to inefficient processes, errors, and poor outcomes. Instead, Nate says that organizations should start slow, validate their data, and progressively increase automation as they build confidence and trust in the AI.
Starting with a “crawl” gives organizations the ability to carefully look at the data that is educating their AI while supervising the input and output of the tool. Once it is clear that the system is producing reliable results, they can “walk.” Then they can “run” with it as they transition into a more automated system.
ServiceNow’s Yokohama release gives clients powerful new AI-driven solutions to improve operations, enhance decision-making, and improve access to quality data. Using a strategic approach, organizations can harness the power of their data and agentic AI to drive efficiency and innovation.
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We’re with you for what comes next
You're working in a rapidly shifting environment.
Global dynamics, AI advancements, heavy competition–the only certainty is change.
We get it. And we’re here to help you harness the full potential of ServiceNow to simplify transformation.
Let's navigate the future together.
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