Leaders are under extraordinary pressure to use AI tools to automate and accelerate tasks like patch remediation and endpoint security. But as IT departments try to deploy new AI tools, they are running up against a longstanding problem: disconnected, sometimes contradictory, sources of data, including logs, telemetry, and documents.
“It’s shocking to me that in 2026, a lot of organizations are still using spreadsheets to track IT assets, and nobody is reconciling the data,” says Mareike Fondufe, senior director of solutions marketing for endpoint management at Ivanti, citing Ivanti research showing that 34% of organizations still track IT assets in spreadsheets. “If a device exists in one procurement system and also exists in another system, those systems don’t communicate with each other, and another system might have outdated information.”
Overwhelmed IT teams are counting on automation to help them move away from a reactive support model, where they must constantly chase down the sources of blue screens and other problems. Rather than resolving inconsistencies, AI can amplify underlying data quality issues — scaling errors across systems and workflows.
This can lead to IT teams pausing automation efforts because they don’t trust the underlying data.
“AI without trusted data isn’t just ineffective,” Fondufe says. “It increases operational and security risks, from zero-day exposure on unpatched endpoints that fall outside patch visibility to regulatory non-compliance from assets that sit outside audit scope.”
Even when leaders think they have a holistic view of their IT environments, there are often hidden gaps. In one recent case, an Ivanti assessment revealed that a customer had 30% more devices than leaders were aware of, resulting in security gaps. “They realized they didn’t have full visibility into their infrastructure. Without complete visibility and context, they cannot confidently act or automate,” Fondufe says. “If something went down, they wouldn’t even be able to identify which servers supported critical services.”
Within many organizations, ownership is often fragmented across teams, meaning that no one is in charge of exploring solutions that can create a single source of truth.
Ivanti acted as “Customer Zero” for its own Autonomous Endpoint Management strategy and solutions. In addition to improved visibility and reduced risk, the organization reclaimed nearly 56,000 employee hours per year, much of it via simplified compliance reporting.
In another example, Ivanti worked with a healthcare organization that saw decreased ticket volume, enhanced end-user experiences, and improved IT job satisfaction after embracing AEM. But first, Ivanti helped the organization modernize its fragmented IT operations and establish a trusted system of record for its IT and security operations. With that trusted system of record, the healthcare customer was able to shift from a reactive, tool-driven management approach to a data-driven model that leverages automation for detection and remediation.
AI is a powerful enabler that allows companies to solve all these pain points faster and more efficiently,” Fondufe says. “The Ivanti Neurons Platform provides a unified data foundation that helps organizations move from fragmented visibility to trusted context — allowing solutions like AEM to deliver insight and action.
Stop reconciling IT data across disconnected systems. See how Ivanti Neurons helps you build the trusted data foundation your AI initiatives require.