Manager, COO BCM & Risk Maturity

Snowflake, Westpac, NSW Health showcase how trusted data is turning AI into business outcomes. 21 Aug 2026 7 mins The market is entering a new phase where trusted data, rather than AI models, will determine AI business value success. The race to build the "agentic enterprise" is creating a major new opportunity for partners, with Snowflake revealing that customers are increasingly investing in the data, governance and infrastructure foundations needed to deploy AI at scale. At its World Tour in Sydney, Snowflake said the market is entering a new phase where trusted data, rather than AI models alone, will determine which organisations successfully translate AI into business value. Snowflake CIO Mike Blandina highlighted growing demand for data modernisation, governance and AI integration services, citing projects at Westpac and NSW Health as examples of how organisations are turning AI ambitions into operational outcomes. Blandina also took the opportunity to articulate its vision for the 'agentic enterprise' stating that the next phase of enterprise AI will be defined not by large language models alone, but by how organisations connect trusted data, governance, applications and AI agents. "The biggest myth is deploying your AI agents, and the data will figure itself out," Blandina told attendees. "Deploying agents does not equal the agentic enterprise." Blandina outlined four pillars underpinning Snowflake's strategy: model choice; software and application connectivity; data and business context; and an agentic control plane. Central to the strategy is Snowflake's Horizon Catalog, which provides metadata, governance and business context across enterprise environments, allowing AI systems to interpret data consistently and avoid conflicting outputs. Blandina pointed out that poorly governed data remains the biggest obstacle to AI adoption, citing customer feedback indicating most organisations still do not consider their data estates AI-ready. "There's just no good AI strategy without a great data strategy," he said. Snowflake has also expanded support for multiple AI models, allowing customers to choose between proprietary and open-weight models while introducing governance and cost controls at the workload level. The intelligence era. Westpac chief digital, data and AI officer Andrew McMullan detailed how the bank has consolidated data from 285 source systems into a unified intelligence layer built in partnership with Snowflake, accelerating model development fivefold and customer insight activation sixfold. He revealed that 95 per cent of its 35,000 employees actively use AI tools as part of their everyday work as the bank races to build what it calls an "intelligence era" operating model. The results are already flowing into frontline banking operations, according to McMullan, who described AI as a tool for empowering employees rather than replacing them. "In the last month alone, 95 per cent of our employees are actively using AI tools as part of their day-to-day work," he said. The bank has also launched internal AI agents designed to dramatically cut time spent gathering information. A tool called "Start Your Day Informed" analyses thousands of overnight signals and presents bankers with only the information requiring attention, enabling relationship managers to spend more time engaging with customers and less time preparing for meetings. Westpac's presentation underscored a broader theme running through the event: the industry's shift from AI pilots and proofs of concept to production-grade deployments built on governance, security and trusted data foundations. For McMullan, trust remains the critical differentiator. Westpac has developed a framework centred on five pillars: transparency, responsibility, purpose, security, privacy and trusted intelligence. "Trust isn't something that you build or audit later into a system; it has to be designed from the very start," he said. The bank's "Westpac Intelligence" platform now combines data, analytics, machine learning, decisioning and AI into a single enterprise layer designed to surface actionable insights while maintaining governance controls and human oversight. The initiative is also helping accelerate fraud detection efforts. McMullan said processes that once required three to six months of analysis can now be completed in hours by rapidly identifying behavioural indicators such as new payees, unusual transaction patterns and unfamiliar devices. Importantly, he stressed that AI remains advisory. "A machine learning model doesn't prevent fraud. What it does is it gives you the indicator. Our responsibility is what we do next," he said. NSW Health tackles complexity with FinBot. Snowflake showcased how public sector organisations are beginning to operationalise AI. NSW Health chief financial officer Alfa D'Amato outlined the development of FinBot, an AI-powered decision support tool designed to help finance and operational leaders navigate one of Australia's most complex healthcare systems. With more than $40 billion in annual expenditure, 226 hospitals and over 180,000 employees, the health system generates significant volumes of operational and financial data. D'Amato said FinBot enables leaders to move from questions to answers in seconds instead of weeks by combining finance, workforce, costing and performance data into a unified decision-making environment. "The answer is not producing more reports," he said. "The answer is transforming information into knowledge and knowledge into action." The system can benchmark performance, identify cost-saving opportunities and recommend actions based on evidence and operational context, while maintaining extensive governance and validation controls. "AI supports decisions. Humans remain accountable for them," he said. AWS and Snowflake double down on partner-led AI growth. Snowflake A/NZ regional vice president partners and alliances Cathy Conroy and AWS A/NZ partner lead Pip Gilbert positioned the vendor's recent alliance as a key enabler of enterprise AI projects moving from experimentation to production. The two companies' expanded strategic collaboration agreement (SCA), announced in May, includes a US$6 billion infrastructure commitment from Snowflake to AWS over five years and deeper integration around generative AI, agentic AI, AWS Marketplace and joint go-to-market programs. The agreement also expands investment in customer success initiatives, workload migrations and industry-specific solutions designed to accelerate enterprise AI deployment. Conroy described the SCA as "a significant step forward" that will help customers and partners accelerate adoption of agentic AI while helping organisations move from pilots to enterprise-scale deployments. Gilbert added the partnership extends well beyond the headline investment figure. "There are 28 different technological integrations between our services," she said, noting that the alliance spans both horizontal AI capabilities and industry-specific solutions. The executives said that enterprise AI adoption is creating a new wave of modernisation projects as customers revisit ageing data estates that previously proved too costly or complex to transform. According to Gilbert, AWS funding programs and migration initiatives are helping reduce what she described as the "cost of change", creating fresh growth opportunities for channel partners looking to build data modernisation, analytics and AI practices. AWS recently expanded its infrastructure footprint across Australia and New Zealand (A/NZ) following the launch of the AWS Asia Pacific (New Zealand) Region, which opened in September 2025 with three Availability Zones and local data residency capabilities. AWS has committed approximately NZ$7.5 billion to the region, which it expects will contribute NZ$10.8 billion to New Zealand's GDP and support around 1,000 jobs annually. The New Zealand region has become increasingly important for partners targeting regulated industries, enabling local customers to keep workloads and data within New Zealand while accessing AWS AI and cloud services with lower latency. Gilbert described partner ecosystems as central to AWS' growth strategy and that customers are increasingly willing to modernise ageing data environments as AI initiatives move higher on executive agendas. "The path to business value is far smoother," she said. Conroy added that partners able to adapt their go-to-market approaches around data and AI will be best positioned to capitalise on the opportunity ahead. "We are absolutely transforming the way customers operate their day-to-day business," she said. Don't miss a thing From its editors straight to your inbox. Get started by entering your email address below. Editor ARN | Reseller News With years of experience covering the latest technology trends and business news across the IT channel, Julia Talevski has been keeping the IT industry connected in Australia and New Zealand. She is currently the editor for ARN and Reseller News, responsible for keeping the community engaged at every touch point through its newsletters, websites and main events such as EDGE, WIICTA and Innovation Awards.

Westpac Banking Corporation has raised A$1.5 billion through issuing Tier 2 subordinated notes. The offering comprises a A$250 million fixed-to-floating tranche and a A$1.25 billion floating-rate tranche, both callable and maturing in August 2036. The notes are structured as regulatory capital instruments under Australia's Basel III framework. Westpac expects them to qualify as Tier 2 capital, strengthening its regulatory capital position and loss-absorbing capacity during financial stress. The instruments include non-viability provisions allowing conversion into ordinary shares or write-off if the Australian Prudential Regulation Authority determines Westpac is, or would become, non-viable. The notes form part of Westpac's debt issuance programme. Westpac is one of Australia's major banks, providing retail, business and institutional banking services across Australian and New Zealand markets.