A strategic shift is taking shape in the banking sector. Just five months ago, Westpac appointed its first chief data, digital, and AI officer, Andrew McMullan, reporting to CEO Anthony Miller. Shortly after, in June, NAB named Pete Steel as group executive, digital, data, and artificial intelligence, reporting to CEO Andrew Irvine. On Tuesday this week, Macquarie Bank announced the appointment of Ashwin Sinha as chief data, digital, and AI officer. And just yesterday, Westpac announced that Luis Uguina will join Westpac as GM of data, digital, and AI.

The strategic implications of this role — especially with direct CEO reporting — are significant: Digital, data, and AI are no longer just enablers; they are becoming the foundations upon which competitive advantage, customer experience, and growth are built.

The pace of innovation unleashed by generative AI platforms and non-banks is accelerating rapidly. Agentic commerce and payments are poised to radically transform how consumers search, decide what to buy, and pay for products and services. Banks’ fear of customers bypassing bank-owned digital platforms to complete their banking tasks is real.

Under pressure to act, banks are responding by reshaping their leadership and operating models — converging data and AI with digital into a single leadership role. This shift addresses a persistent challenge: Business stakeholders aren’t leveraging analytics to drive decisions, making the value of analytics teams debatable. But that’s about to change. Banks are now setting their sights on:

  1. AI-driven innovation for customer-facing interactions — not just internal operational efficiency.
  2. Embedding intelligence into product and service design.
  3. Reducing time to market through better collaboration between data, digital, and AI teams.
  4. Unifying data and AI strategies with the right governance to unlock business value.
  5. Improving cost efficiency by eliminating duplication.

What we expect to see in the next 12 months:

  • Enhanced search on mobile banking apps and websites, powered by prompt intelligence, where search evolves from keyword matching to intent-driven discovery
  • More proactive financial insights that anticipate customer needs and offer context-aware product and service suggestions through conversational banking
  • Insights-driven product and service design, with features and pricing shaped by a continuous feedback loop connecting customer feedback, digital analytics, and product data
  • Agent-first banking operations, with know-your-customer processes, transaction disputes, and account opening becoming agent-first and where automation supervisors will optimize AI based on enterprise goals

The creation of this new power role heralds a new era in banking — one where success hinges not on technical mastery or incremental process optimization but on the ability to imagine and architect entirely new models of value creation. Just like BNY’s plans for its enterprise AI platform Eliza, which aims to identify second-order connections (interdependencies) and track the value of the collective workflow in order to fix issues before they actually arise. This is a role that demands strategic foresight and bold thinking to reshape the banking operating model.