Atlassian today previewed additional artificial intelligence (AI) capabilities that will be added to its Trello project management software to, for example, make it possible to create a list of projects based on the interactions occurring via email, Slack and voice-enabled agents such as Apple Siri or within Jira applications.
Trello will use AI to extract due dates, action items and priorities from raw text.drop tasks into your schedule, block off time for deadlines for calendars and mark items as “done” once completed. “It creates and organizes your to-do lists,” says Victor Dronov, group product manager for Trello at Atlassian.
Additionally, Trello now provides the ability to “mirror” a card, a visual representation of a task, to enable any changes made to be replicated across multiple boards that might exist within an organization.
Expected to be generally available in April, these capabilities will make it simpler for organizations to collaboratively improve productivity, says Dronov.
Atlassian has been steadily adding AI capabilities to its portfolio of software-as-a-service (SaaS) applications for the past several years. The overall goal is to leverage a range of AI models to automate a range of tasks via a natural language interface that serves to make applications such as Trello more accessible to a wider range of end users.
While AI has the potential to dramatically improve the productivity of organizations, the most immediate impact is clearly on automating tedious tasks, such as organizing a to-do list, that most people used to manually perform.
The level of adoption of these AI capabilities will naturally vary widely by end user but it’s generally only a matter of time before AI agents will be more widely employed, especially as voice-enable interfaces are added.
Less clear, however, is how much of a competitive advantage these types of AI tools will provide when the bulk of employees have access to the same capabilities. In effect, AI is rapidly becoming a new set of table stakes that many end users are going to naturally expect to be able to invoke. Any application experience that doesn’t provide access to AI tools will in comparison soon appear antiquated.
In the meantime, every organization will need to decide to what degree to invest in training to get the most out of AI capabilities that are being embedded within applications. There is a natural tendency to just provide end users with access to software in the expectation that they will discover the capabilities provided on their own. However, organizations that do invest in training do tend to derive more business value from software investments. End users will also need to be regularly reminded to vet the output of AI models that are probabilistically guessing what the right next step may be, which in some instances might still be a hit-or-miss proposition.
Hopefully, AI will make it simpler for end users to invoke a much wider range of capabilities that previously might have gone unnoticed. In fact, it might be argued that the less training required to master an AI application, the better it really is.
