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During the pandemic, employee wait times to hear back from IT have soared because IT departments have received an onslaught of calls. Enterprises are actively leveraging newer technologies like Virtual Support Agents (VSAs) to improve wait times and raise employee satisfaction.

VSAs are a type of virtual assistant that includes chat bot and automation capabilities. They deliver information, provide answers to common questions and perform transactions to provide IT support assistance in an IT service management scenario alongside the IT service desk. Since natural language is the preferred way of conversation, using VSAs requires no technical training, which makes the solution easier to adopt.

VSAs are not just a chatbot. 

While chatbots use rule-based algorithms to answer questions, VSAs integrate with the existing systems in the company to enable it to service and fulfill tasks for employees. Backed by AI and conversational capabilities, VSAs understand context, user preferences and sentiments.

Per HDI’s report, self-help can drive a 42% reduction in tickets. That sounds like music to any IT Service desk’s ears. For example, an employee raises an issue: Her printer is not working. This is a relatively routine issue that can be resolved by the employee herself. The employee gets on the chatbot airing her complaint, and the VSA flies into action offering a solution in the form of a how-to knowledge article from an up-to-date knowledge management repository. The employee then tries the fix. If the solution now works, the problem is solved. If not, the employee can send another ticket.

The selection and serving of how-to knowledge articles by a VSA is not trivial. There is a lot of AI and deep-learning science behind it. In spite of no prior labeling of data, the VSA picks up exactly the relevant article. It understands phrases, sentences and context. Being contextually aware comes from the deep history data of the employee’s prior queries — for example, how many tickets have been raised in the past.

Let’s say an employee is unable to configure her inbox, and the chatbot offers a relevant article. If the fix does not work, the employee could create a ticket or talk to a live agent. Upon receiving the call in the chat window, the live agent invokes a standing incident history of all the prior conversations the employee has had with IT. He has the history available at his fingertips and acts as a fallback to a VSA when the VSA is not able to resolve an employee’s issue. After resolving the ticket, the live agent could cycle back to build a new knowledge article, further enriching the enterprise’s repository of knowledge articles.

There are always unique issues for which a relevant knowledge article may not exist. In that case, the system pulls up an appropriate form in order to capture the specific details of the issue leading to the creation of a rich ticket. The rich ticket includes details such as the browser version the user is on or what error code she saw. This helps IT resolve tickets quicker because the rich ticket provides a head start.

What are the challenges to adopting VSAs? 

The VSA is only as good as the knowledge repository it relies on. It needs a corporate-wide commitment to the success of the solution, which involves the diligent documentation and updating of knowledge articles across the company.

It helps to have a strong company culture for sharing information. This culture will depend on an enterprise that is willing to adopt new technologies. With a progressively younger workforce, VSAs play to this strength. While VSAs require a shift in the culture where the knee-jerk response is to pick up the phone or send off an email after running into an IT glitch, they can help employees help themselves and allow a company to digitally evolve and transform.

The speed of VSA implementation, however, depends on the type of AI being used. General-purpose AI lends itself to longer implementation time and limited coverage.

In addition, for VSAs to be successful, the entire company needs to be using it. If employees don’t get the answers they are looking for from the solution, they won’t keep using it. No room for trial and error. The success of the VSA solution resides in the richness of the knowledge repository.

What should you look for when evaluating a VSA partner? 

IT support is a mature field with its own language. Over the past few years, IT support has developed rapidly with companies like ServiceNow and BMC that have enriched the marketplace with innovative solutions. A partner that connects to these crucial platforms is essential for a VSA solution.

Once connected, the right VSA partner needs to use purpose-built AI for IT in order to understand, route, orchestrate and fulfill requests from the diverse platforms in a client’s IT support universe. Look for partners with this experience and who have developed a rich repository of comprehensive knowledge articles both from open and closed databases. With the right partner, enterprises can do away with investing in expensive AI and domain skills.

While there are many general purpose AI-powered systems like IBM Watson or MS LUIS available in the market, these have to be exhaustively trained in IT management before they can be used in a service desk environment. Additionally, these systems will also need to be trained periodically to keep the systems up-to-date. General-purpose AI platform might require a large time investment to train and fulfill the complex IT service desk deliverables.

Ask any potential partner if their solution will allow you to hit the ground running. A general-purpose AI partner might require clients to build their own repositories over time, but who has the time for that?

By Uday Birajdar

CEO and co-founder at AutomationEdge

This article first published on Forbes here.

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