Transcript
endpoint management can address them, we first need to consider just the sheer number of devices an organization has that it needs to build policies around. Most organizations, the likely largest IT spend is to fund the need for IT administrators to manually deploy policies, to manually patch systems, update software, monitor compliance, and remediate vulnerabilities. Perhaps there's these one-off automations that exist that help, but not across the full endpoint management spectrum. So with autonomous endpoint management, companies can automate and secure those devices intelligently using things like AI and machine learning capabilities to ever advance that feature set. If you think about the productivity that saves across any IT department, there are a good number of use cases an organization can think through that will directly reduce IT spending and provide leadership better leverage from its think capacity. A few that rise to the top for me in particular include zero-touch provisioning and the ability to eliminate the need for multiple authorization steps throughout a process. Those are typically manual, you know, that have to go through multiple layers of approval or authorization. Compliance and policy governance via continuous monitoring of the devices. This ensures your remaining compliance with your organization's required policies, whether those be security policies, access policies, or software usage as examples. And then of course, you know, a big use case being threat detection and response using AI and machine learning driven monitoring to identify suspicious activity and then be in a position to automate, contain, and remediate those threats. Where you automate these cases, your organizations can prioritize its resources to more higher value productivity activities versus what we see in repetitive or mundane tasking. Consider using IT admins to handle only exceptions as opposed to manually provisioning or rolling company devices.
