automation

Atlassian today added generative artificial intelligence (AI) capabilities to Jira Service Management, an IT service management (ITSM) platform built on top of Jira project management software already used widely by DevOps teams.

Generative AI is at the core of a virtual agent that analyzes and understands intent, sentiment, context and profile information to personalize interactions. Based on the same natural language processing (NLP) engine that Atlassian is embedding across its portfolio, the virtual agent dynamically generates answers from sources such as knowledge base articles, onboarding guides and frequently asked questions (FAQs) documents.

In addition, it can facilitate conversations with human experts any time additional expertise is required to respond to more complex inquiries.

Atlassian is also extending the reach of Atlassian Intelligence, a generative AI solution launched earlier this year, to provide concise summaries of all conversations, knowledge base articles and other resolution paths recommended by previous agents that have handled similar issues. It will also help IT staff craft better responses and adjust their tone to be more professional or empathetic if needed.

During setup, support teams can easily configure the virtual agent experiences to match how they deliver service without writing a single line of code.

Edwin Wong, head of product for IT solutions at Atlassian, said these additions are part of a larger commitment Atlassian is making to unify the helpdesk experience. The company plans to leverage Atlassian Intelligence to coordinate routing of all employee requests to the right tools as it aggregates requests from multiple communications channels such as web portals, email, chat and from within third-party applications, he noted.

The overall goal is to reduce the number of tickets generated by leveraging AI as much as possible to handle service requests in a way that costs less to implement and maintain, Wong said.

In the longer term, Atlassian will also apply generative AI to enable organizations to automate IT asset management further, he added.

There is little doubt at this juncture that AI will be pervasively applied across both ITSM and DevOps workflows. As those advances are made, it should also become easier to address issues that arrive either programmatically or by generating a ticket for a service request that is then processed by an ITSM platform such as Jira Service Management.

Each organization will need to decide how quickly to incorporate AI into ITSM, but hopefully, the level of burnout experienced by IT personnel will be sharply reduced as more tasks are automated. Less clear is the impact AI will have on the size of IT teams required to provide those services, but for the foreseeable future, there will always be a need for some level of human supervision.

In the meantime, IT teams should take an inventory of the processes that are likely to be automated by AI today with an eye toward restructuring teams as more tasks are automated. Ultimately, the goal should be to let machines handle the tasks they do best so humans can provide higher levels of service that deliver more value to the business.

Image courtesy of Cash Macanaya on Unsplash: https://unsplash.com/automation cash-macanaya-X9Cemmq4YjM-unsplash/