Scaling Jira Onboarding with AI

Role: Lead Product Designer, owning end-to-end onboarding strategy and execution across AI-powered experiences

Team: Led design within a cross-functional group of 11 engineers, an architect, and a PM

Outcomes: 16 experiments shipped → +9,300 annualized customers successfully onboarded

Sep–Dec 2025

 
 

Customer problem

Who are we designing for?

New Atlassian users at medium size organizations. Let’s take Melanie, a marketing manager who is thinking about trying Jira out as a project management tool as her marketing peers all leverage different project management software (spreadsheets, Asana, Notion). She’s looking to organize and track her team’s core marketing initiatives more efficiently.

 
 

What problems does she currently face?

  • Significant friction to get into the actual product

  • Onboarding isn’t tailored to project maturity, role, or goals & assumes technical knowledge that doesn’t match workflow

  • Overwhelmed and unsure where to start because met with 50+ CTAs after landing in product

  • Uncertain about where to invite team

{insert images or video of current E2E, as well as quotes}

 

Business problem

We’ve seen a ~5% decline YoY in FY25 as compared to FY24 cross key functionally onboarded metrics

{visual}

These four key drop-off points, along with qualitative feedback, guided the themes we focused on:

Confused → confident

Not-for-me → made for me

Alone → together

{visual of themes}

 
 

Research

Customer interviews

I completed sixteen interviews with new or non-Jira users. The goal was to:

  • Determine the level of guidance customers want when setting up their first space

  • Clarify users' onboarding expectations

  • Identify pain points in the current flow goal

This research validated the pain points shared above, and also brought about some key insights:

  • Onboarding preferences vary. Some prefer a hands-off approach, while others want to be hand-held.

  • Customers expect the ability to integrate data from existing tools.

  • Customers expects an AI assistant to be available for onboarding and ongoing help.

  • Customers want to understand why we ask for team and workflow information.

  • Clarity on output and next steps is critical

 

Comparative analysis

I also explored industry best practices through a competitive audit. Some of the onboarding trends I noticed and adopted into my design were:

  • Empty states to guide initial action

  • Show strong prompt examples

  • Highlight invite actions upfront

  • 1 more

  • 1 more

{visuals of comparative audit}

 
 

Design

Explore variations

{insert image}

Final E2E flow

{insert images}

 
 

Outcomes & impact

  • Delivered E2E optimized onboarding experience for Jira

  • Broke vision down into 20+ experiments and influenced roadmap to get them prioritized

  • Design & shipped 16 experiments that led to +9,300 annualized business customers to functionally onboard (177% of our stretch goal for the year)

 
 

Learnings

  • Orchestrating cross-team delivery by identifying and unblocking dependencies

  • Rapidly gaining domain expertise and adapting as priorities shift

  • Designing AI experiences while navigating ambiguity and emerging technology