CBA uses Atlassian tool to stay focused on $400m AI goal

You have probably watched a large-scale transformation lose momentum because teams could not see how their daily work connected to the headline ambition. Commonwealth Bank of Australia is using Atlassian's Strategy Collection to solve that problem. The bank wants to be a world leader in AI banking and banked about $200 million of AI benefits in the most recent financial year. This financial year the target is $400 million. Strategy Collection is how CBA keeps leaders and teams coordinated on that goal, linking topline priorities directly to daily work streams and showing appropriate resourcing and capacity in real time.

Helen Lau, engineering platform general manager at CBA, told Atlassian's Teams 26 Europe conference that the bank is live with the suite. Strategy Collection is three tools that together form what Atlassian markets as strategic portfolio management. In simpler terms, it acts as a connected operating model. Leaders and teams can see how the AI goal rolls down into team actions and how those actions roll up to contribute to the topline target. Lau said the transparency matters because it changes how people think about their work. "If you have that in front of you, you're saying, 'I need to build an awesome product and service for my customer. At the same time, I need to deliver this value'. [It means] you need to think of how you do your job best, basically."

What happened

CBA first attempted to implement Strategy Collection in September last year with a proof-of-concept in two internal departments. Eight weeks into a planned twelve-week proof, Lau stopped it. "[Both] organisations, Atlassian and CBA, weren't ready to roll this out group-wide, so we stopped," she said.

The two organisations have a history of working together spanning almost two decades. When CBA migrated its on-premises Jira and Confluence to cloud-based versions four years ago, it worked closely with Atlassian to introduce 22 product features to cater to the bank's needs. The two revived that collaborative approach to ensure the second attempt succeeded.

The relaunch happened in March. In six weeks CBA migrated over 9000 goals into Strategy Collection and trained all its top 20 percent of the organisation, up to the C-level, on how to use the tool. Lau said AI is fast becoming part of the bank's DNA. "We've been using and embedding AI everywhere in our business, from customer experience to fraud and scam [detection and prevention], to financial crime to cyber, and now in my own backyard [where] productivity is what's close to my heart."

What this means for transformation leaders

The CBA case shows that alignment tooling only works when both the vendor and the customer are ready. Lau's willingness to stop the first proof-of-concept eight weeks in is the hard part. Most organisations let a struggling pilot limp to its planned end date, then write a lessons-learned deck that no one reads. CBA and Atlassian used the failure to build the 22 features that made the second attempt viable.

The six-week migration and training window is fast for a bank of CBA's scale. That speed suggests the bank treated goal migration as a data problem and training as a change problem, not the other way around. Migrating 9000 goals means someone built a script or a bulk import process. Training the top 20 percent first means the bank prioritised the people who set goals and review progress, not the people who inherit them. That sequence matters because it ensures the tool reflects how leaders actually run the business before teams are asked to use it.

The connected operating model language is worth unpacking. Strategy Collection links topline priorities to daily work streams, but the real value is in the roll-up and roll-down visibility. Teams can see how their work contributes to the $400 million target. Leaders can see which teams are on track and which need more capacity or different resourcing. That two-way transparency is what keeps large-scale programmes from drifting. When a team knows that their fraud-detection sprint contributes to a specific slice of the AI benefit target, they can make better trade-offs about scope, quality and speed.

The $200 million banked last year and the $400 million target this year are large numbers, but they are also specific. CBA is not talking about AI maturity or digital transformation in the abstract. The bank is measuring benefits in dollars and using Strategy Collection to keep everyone focused on delivering them. That specificity is what makes the alignment tooling useful. If the goal were vague, the tool would just be a prettier way to track vague work.

For L&D and transformation leaders, the lesson is that alignment tooling is not a substitute for clear goals, but it is a force multiplier when the goals are clear. CBA's AI ambition is unambiguous. Strategy Collection is how the bank makes sure that ambition does not get lost in the gap between executive intent and team execution. If your organisation is running a large-scale programme and teams cannot see how their work connects to the headline goal, the problem is not motivation. The problem is visibility. Fix the visibility and the motivation follows.

Sources:

• iTnews, 12 October 2026