Westpac maps its path to becoming an intelligent bank
In its September 2026 Data, Digital and AI (DD&A) update, Westpac Banking Corporation outlined the progress of its technology transformation strategy, presenting measurable results across digital engagement, workforce AI adoption, and engineering productivity. Delivered by Chief Data, Digital and AI Officer Andrew McMullan and Chief AI Officer Dan Jermyn, the presentation detailed three strategic pillars: turning data into intelligence, AI for everyone, and accelerating delivery.
The metrics disclosed signal that adoption has moved well beyond aspiration. 80% of quality sales were originated digitally in the 12-week period to August 2026, 99% of service interactions were completed digitally between October 2025 and August 2026, and more than 35,000 employees now have access to AI tools, with 72% having integrated AI into their daily workflow.
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Three pillars driving the DD&A strategy
The presentation structured Westpac’s DD&A progress around three interconnected pillars, each supported by quantified outcomes and named initiatives.
Turning data into intelligence
The foundation of Westpac’s data strategy rests on consolidating 285 fragmented source systems into a single governed enterprise data platform called Adapt. From this unified foundation, Westpac has built the Westpac Intelligence Layer, which connects data and AI capabilities to enable personalised customer experiences across the mobile banking app, digital banker, and digital contact centre.
The Intelligence Layer has delivered meaningful efficiency gains. Based on initial use cases, model build and deployment is 5x faster, and activation of customer insights is 6x faster, according to the presentation.
AI for everyone: workforce adoption at scale
The workforce AI adoption figures presented represent sustained uptake rather than one-off access. 95% of employees completed non-mandatory AI training, 95% use AI tools on a monthly basis, and the employee AI confidence score improved from 73 to 80 between February 2026 and August 2026.
The adoption trend over the period from January 2026 to August 2026 illustrates the depth of this shift. AI adoption among users rose from 69% to 95%, while consistent use (defined as performing actions on more than ten days in a month) grew from 14% to 72% over the same period.
Accelerating delivery through AI-powered engineering
AI has also been applied to Westpac’s engineering and technology delivery functions. Agentic code conversion has contributed up to a 35% increase in code development productivity, addressing the challenge of complex legacy technology slowing delivery. The St.George data warehouse migration, accelerated through AI-assisted tooling, is expected to be delivered two years ahead of plan. Separately, the BizEdge initiative recorded a 40% increase in delivery productivity, measured as velocity delivered per person per sprint in Release 5 compared to Release 1.
AI in action: where the results show up for customers
The presentation detailed a series of customer-facing and operational use cases where the DD&A strategy has produced quantified outcomes. The table below summarises the key examples disclosed.
| Use Case | Area | AI Contribution | Measured Outcome |
|---|---|---|---|
| Home loans | Mortgages | Application payslip and bank statement automation | ~100k hrs banker capacity (estimated annual benefit) |
| Consumer Finance | Consumer lending | Real-time application payslip automation | ~50k hrs banker capacity (estimated annual benefit) |
| Website search | Digital customer experience | AI-powered customer search engine | 75% increase in selection of first search result vs. 12-week average before launch on 21 August 2026 |
| Personalised deposit offers | Consumer banking | Personalised offers delivered at scale | 500k customers reached in 2 weeks; >2x account uptake vs. control group |
| Smart digital leads | Business banking | AI identifies customer opportunities | 16k customer conversations; 2.8x increase in settlements over the five months to August 2026 vs. prior corresponding period |
These outcomes sit within Westpac’s “responsible by design” framework, which embeds AI governance at the board, executive, and operational levels. The presentation noted that governance mechanisms include automated risk assessments with human accountability, as well as risk-based controls embedded in code and enforced at runtime.
What this means for Westpac investors
The DD&A strategy is explicitly positioned in the presentation as supporting Westpac’s five stated priorities: Performance, Customer, People, Risk, and Transformation. The stated strategic destination is a reduction in the cost-to-income ratio and improved returns, with the three pillars collectively designed to increase customer advocacy, foster engaged employees, and drive growth and productivity.
A structural shift in how Westpac executes its technology strategy is also underway. The Catalyst operating model moves from yearly funding and siloed teams toward persistent funding and teams positioned closer to customers, a change the presentation frames as enabling faster speed to market and end-to-end accountability.
The presentation also disclosed six global technology partnerships underpinning the DD&A strategy:
- Microsoft (Everyday AI)
- Snowflake (Intelligence Layer)
- AWS (Operations at Scale)
- NVIDIA (AI Factory Platforms and Open Models)
- AMP (Engineering)
- Google (Digital Customer Experience)
The presentation positions progress across all three pillars as the building blocks for improved financial returns, though no specific earnings guidance or financial targets were disclosed in this update.
Investors exploring the financial backdrop behind these technology investments will find our full explainer on Westpac’s 1H26 profit result covers the lending growth trends, impairment charge movements, and capital position that frame where efficiency gains from the DD&A strategy need to land.
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