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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 syste …