CommBankโs move is best read as an operating-model decision, not a tidy reorganization. By placing customer experience, digital channels, and data-led automation under one executive umbrella, the bank is trying to collapse the usual handoffs that slow product decisions and fragment accountability. That matters because banking technology only creates value when it is tied to customer outcomes, not isolated platform upgrades. The real signal here is a management structure designed to keep execution, experience design, and business priorities moving in the same direction.
The practical enabler is an already highly digitized retail base: with 99% of customer interactions happening digitally, the bank can layer more conversational and intuitive services onto an existing footprint rather than rebuilding from scratch. But the architecture is not just front-end polish. Investment in the data platform and metadata layer suggests an attempt to make services discoverable, governed, and scalable across teams. That is reinforced by cross-functional work among product, engineering, design, analytics, and data science, plus gradual rollout and strong governance.
The risks are equally structural. A more natural interface can still fail if it produces confusion, bad answers, or uneven service quality, so the bankโs emphasis on trust and staged deployment is more than cautionary language; it is an acknowledgment of operational fragility. The other constraint is organizational maturity: without broad upskilling, shared ownership, and disciplined metrics such as customer feedback, complaint reduction, and adoption, the model becomes branding rather than capability. Its significance lies in execution discipline, not novelty.
Five months ago, I published a blog post about bankingโs new power role: the chief digital, data, and AI officer. This is an executive mandate designed not just for a simple consolidation for efficiency but to unify digital, data, and AI around a single strategic vision for growth, decision-making, and transformation.
Commonwealth Bank of Australia (CommBank) has taken a related โ but different โ approach. In June 2025, the bank appointed Dr. Michael Baumann as the executive general manager of customer, digital, and AI. I spoke with Dr. Baumann to understand the thinking behind this integrated role, how itโs shaping CommBankโs digital strategy, and what it means for the future of banking.
Q: Dr. Baumann, your role combines customer, digital, and AI leadership. Why have you brought these functions together?
Absolutely. Itโs a unique combination but one that makes strategic sense. Our goal is to create exceptional CX. As generative AI (genAI) advancements continue to accelerate, weโre seeing digital and AI naturally converge. Data powers AI, so having data, digital, and AI closely aligned is critical. And then thereโs the customer: Everything we do is for them. By bringing these functions together, weโre making sure that our technology and innovation efforts are always aligned to our customersโ needs.
Q: Tell us how AI is being integrated into your digital experience and CX.
Weโre already seeing that 99% of our retail customer interactions are digital, so the foundation is there. The next step is making those interactions more conversational and intuitive. I imagine a future where customers donโt have to call us or navigate menus. Instead, they can just talk to a virtual agent in the app or even through a smart speaker. Itโs about creating a seamless, natural experience.
Of course, weโre not flipping a switch overnight. Trust is everything in banking, so weโre introducing these capabilities gradually. Weโre proud of the security features within our app, and we know that our customers appreciate us for that. We want to build on that trust as we roll out more automation and AI-driven features.
That said, weโre very conscious of the risks. GenAI is still new, and we need to implement it safely, especially in customer-facing experiences. Itโs critical that customers get what they need, when they need it, and that we avoid misinformation or confusion; so weโre taking a step-by-step approach, with strong governance built in from the start.
Internally, weโre also using agentic AI to streamline operations โ things like onboarding, compliance, and customer support. Itโs all about making things faster, smarter, and more helpful.
Q: What kind of organizational structure and technical architecture supports this integrated approach?
Collaboration is key. I report to Angus, our group executive for the retail bank, and I oversee digital, our retail data science and data office teams, as well as strategy and ESG. We work closely with the group data office, even though it sits separately in our technology team.
Weโre also investing heavily in our data platform and metadata architecture. Having the right infrastructure is essential to enabling AI and genAI at scale. And on a day-to-day level, I work closely with product teams, channel leads, engineers, designers, data scientists, and analytics folks. Itโs a very cross-functional environment and nothing happens in isolation.
Shortly, we will welcome a chief AI officer to the organization. This is a role that will complement mine, as weโre both focused on AI but from different angles. The chief AI officer helps drive enterprisewide AI strategy and governance, while I focus on how AI is applied within the retail bank to improve CX. Itโs a great example of how weโre aligning leadership across the business to make AI a core capability.
Q: What contributes most to the success of this function?
People, without a doubt. Technology is important, but itโs the people and their mindset that really drive outcomes. We donโt have a separate innovation lab โ innovation is everyoneโs job. The teams working on real customer problems are the ones experimenting with AI. Some move faster than others, and thatโs OK โ itโs an organic process.
We also run an โAI for allโ program across the bank that gives everyone access to tools and training. Not every problem needs to be solved with genAI, but itโs a great way to challenge assumptions and encourage new thinking. We want people to feel empowered to try things, experiment, and learn.
And more broadly, weโve seen that when you bring digital, data, and AI together under one roof, you eliminate silos. That means faster decision-making, better alignment, and more cohesive execution. Itโs a big part of why this model works.
Q: How are you tracking progress to ensure that initiatives deliver impact?
We focus on outcomes that matter to customers. One of our key goals is to reach โNPS + 30โ โ a top-tier Net Promoter Scoreโ (NPS). Weโre also looking at how to improve the CommBank app experience, how widely new digital features are being adopted, and whether weโre solving real customer problems.
Additionally, we track progress with customer feedback, interaction scores (where customers rate their experience at different points), and by monitoring complaint reduction. These give us a clear picture of where weโre doing well and where we need to improve.
Weโre not innovating just to be flashy. If we can help customers reduce stress, feel more confident, and improve their financial well-being, then we know weโre on the right track. And when we do right by our customers, the business outcomes tend to follow.
Conclusion
Q: As financial services firms accelerate their push toward AI, what should leaders keep in mind?
First, ensure that your organization is operationalizing AI at scale, rather than creating one-off solutions. Second, upskill employees, evolve roles, and foster collaboration. Third, improve experiences more holistically across touchpoints, not just on digital touchpoints.
If you would like to learn more, Iโd love to chat! Forrester clients can use this link to schedule a guidance session.
Cowritten with Janis Teo, senior research associate
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