"Help desks need help. But many of the agents coming to the rescue are chatbots in disguise. They claim to "resolve tickets" or "transform IT support," but when you actually roll them out, most of these tools end up routing tickets, not resolving them. Remove their agent mask and they're glorified intake forms with a friendlier UI. I've worked with dozens of enterprise IT teams who want something better, something real."
"Despite the hype around AI agents, the fact is most teams don't want magic. They just want some breathing room: fewer repetitive tasks, faster ticket resolution, and real impact on SLAs and costs. In this article, I'll share what I've seen work-whether you're starting from scratch or rethinking an existing "agent" that just doesn't deliver. Step 1: Start with a measurable problem Don't begin with the technology. Begin with the pain."
"One IT leader I worked with had a backlog of unresolved tickets that were eating into SLAs, primarily due to access requests and MFA resets. Their goal was clear: reduce Tier 1 ticket load by 30% without hiring more employees. Start with one high-volume, repetitive use case. Good candidates include: MFA resets "What's the status of my ticket?" questions Software provisioning Password resets or unlocks"
Help desks face high volumes of repetitive requests that many AI 'agents' only intake rather than resolve. Enterprise teams need production-ready AI agents that perform tasks like MFA resets, access requests, software provisioning, and password unlocks to reduce Tier 1 load and improve SLAs. Start by identifying a measurable, high-volume use case with a clear trigger, a definable outcome, and sufficient volume to impact metrics. Focus on automating straightforward, repetitive workflows rather than pursuing broad, magical solutions. A targeted deployment can free IT time, accelerate resolutions, and lower operational costs. Prioritize measurable impact over technology-first experiments.
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