Nothing works well in a silo.
In fact, your business may be taxed by an inadequate knowledge base (KB), inefficient use of a knowledge base or insufficient distribution of knowledge resources. The knowledge base is meant to offer answers, provide instruction and solutions to problems. If it isn’t being used… it’s a problem. The service desk team could be reinventing the wheel each time a common request flows into the ticket queue, instead of working from a centralized, vetted source of knowledge.
Part of the challenge is creating quality knowledge resources to begin with—documenting processes and instructions (and maintaining them) is a time investment to be sure, but it’s well worth the effort up front. How much time is saved when analysts can reference quality resources all have agreed upon?
Even if your KB is airtight, there is the potential hurdle of distribution: is it easy to find the right information or make sure that information gets to the right end user?
Artificial intelligence (AI) elevates everyone’s game, eliminating common pitfalls: duplicate or inconsistent information, constant upkeep, overreliance on specific contributors, lack of focus on continual improvement. It improves the end user experience, and it also makes service desk operations and ticket management much easier for support analysts and admins.
Tikit’s Unique Use of KB
The thing about AI is that it can make a lot of things happen at once.
Creating and Populating the KB
Tikit, a Microsoft Teams-based service desk solution, uses an AI-powered virtual agent to streamline ticket management. It uses the KB to train the virtual agent on which responses to serve to an end user who is requesting help. So, the way to trigger the AI is by creating KB resources about requests you receive, including various words and phrases end users use when they submit requests, along with rich text, images or customized forms in the article body. Just starting a KB? No problem. The more articles you create, the more the AI will learn.
Delivering KB Resources
When it comes to delivery, AI is more effective than search. The virtual agent acts like an analyst teammate by reading the message, interpreting its intent and serving up a related KB response to the end user. That’s the key: the AI breaks through the concept of siloed information because it actively finds the resource and delivers it to the requestor.
End User and Analyst Experience: Improved Productivity
The result is a seamless experience for the end user: they ask for help and receive a KB response. If the KB article doesn’t resolve the issue, the support analyst can step in to help. By deflecting common requests and allowing the virtual agent to try to resolve the request first, support analysts can take control of the queue and minimize the influx of requests.
Tikit’s use of AI streamlines the ticketing process, but it also positions the knowledge base as a driver of ticket resolution and efficiency. There is an incentive and tangible result to feeding the KB: it makes the AI respond more accurately to requests and improves service desk productivity.
AI will only continue to improve various business functions. How will you choose to engage it?