ServiceNow has long been a cornerstone of enterprise IT operations with its flagship Now platform.  

In recent years, the company has been growing its capabilities with the introduction of enterprise AI capabilities, including Now Assist. As a platform that organizations use to literally run their operations, having a high degree of confidence is absolutely critical. With generative AI in particular, there has been some hesitation for enterprises about safety and concerns about potential hallucinations.

Today, the company announced a series of new governance capabilities for its flagship Now platform designed to help increase confidence in enterprise AI usage. The new governance features address a growing challenge in enterprise AI adoption: the gap between experimentation and full production deployment. 

The governance components include Now Assist Guardian, Now Assist Data Kit and Now Assist Analytics. The new tools help organizations manage AI deployments across their enterprise. These tools are crucial as companies move beyond proof-of-concept stages into full production environments.

“Last year, broadly, it was more an experimentation approach and this year it’s getting real,” Jeremy Barnes, VP AI Product at ServiceNow told VentureBeat. “People are deploying AI for something related to their top or their bottom line.”

Why AI governance is critical to enterprise adoption

In an enterprise, governance and compliance are critical operations. 

The ServiceNow platform recognizes the often complex relationship between different enterprise stakeholders. 

“Typically, our customers will have governance and compliance in a different organization to the organization which is defining and owning the economic benefits of the generative AI,” Barnes said. 

What that generally means in most organizations is that one team can get a proof of concept together to try out generative AI. At that stage, there are not the same constraints as when an application or service is rolled out across an enterprise in a full production deployment. Inevitably a governance team within the enterprise will tell the development team that they can’t deploy something without first ensuring compliance with the organization’s policies. Barnes said that what tends to happen as a result, is that generative AI efforts end up in ‘limbo’ between proof of concept and production for a very long time. 

He noted that the new AI governance updates help bridge this divide by providing tools and visibility that satisfy both business and compliance requirements.

“AI governance is not just about researching the models,” Barnes commented. 

He explained that it’s about having a system that includes AI components and traditional workflows. It’s about understanding and being able to make sure that the system fits within the expected outcome desired by the enterprise. Governance is also about understanding when something is wrong and providing the ability to manage the situation.

How agentic AI  accelerates the governance imperative

Among the reasons why more AI governance is needed now is the fact that agentic AI is starting to be deployed.

Many organizations, including ServiceNow, are deploying agent frameworks to provide more autonomous capabilities to AI. Barnes noted that with more autonomous AI agents, there is a greater need for robust governance, controls and human oversight to ensure the systems are operating as intended and within acceptable parameters.

The governance tools and workflows provided by ServiceNow aim to help enterprises manage the risks and maintain the necessary level of control over these more autonomous AI systems.

The intersection of enterprise AI governance and hallucination

A primary challenge for enterprise adoption is the risk of hallucination. Governance itself is not the answer to that challenge, but it’s a component of the solution that is needed.

Hallucination is an industry-wide concern and is something that impacts all generative AI models in one way or another. ServiceNow is taking a multi-layered approach to mitigating hallucination. The approach includes fine-tuning language models to be more focused on extracting information rather than generating new information. 

Governance is another critical aspect of helping to mitigate risk. The new Now Assist Analysis Guardian tool will now also provide an extra layer of protection against hallucination, analyzing AI outputs. Barnes said that a key goal for ServiceNow is to make sure that hallucination is not a ‘showstopper’ for enterprise AI deployments, but rather is viewed as a risk that can be addressed with tools in the platform.

How enterprise AI will help Configuration Management Database deployments

Configuration Management Database (CMDB) is a cornerstone of IT operations management. CMDB systems manage the inventory of systems, software and configurations used across an enterprise.

As part of the ServiceNow update today there is also a new Now Assist for CMDB capability that brings the power of AI. Barnes explained that the new capability does not directly address the population or discovery of the CMDB, which is typically done through other means but rather focuses on improving the productivity of users interacting with the CMDB data. 

The CMDB analysis feature is part of ServiceNow’s broader strategy to provide AI-powered productivity enhancements for different personas within their customer organizations. The CMDB analysis feature is integrated with the AI governance framework, ensuring that the deployment and use of this AI-powered tool is subject to the same governance processes and controls. This helps address the trust and operational constraints that IT operations teams may have when deploying AI-based tools within their critical systems and data.

“The more that you rely on an AI tool, the more you need to be sure that, it is trustworthy for what you’re doing,” Barnes said.