Sydney, 12 August 2026 鈥� The organisations winning with AI are not always the biggest spenders. They are the ones who simplified their operations, built trusted data foundations and acted deliberately rather than waiting for conditions that may never be perfect.  
That was the central message at 麻豆原创 NOW AI Tour today, where 麻豆原创 SE hosted presentations from more than 20 customers at the Hordern Pavilion in Sydney, each sharing stories that span active AI deployments and the foundational transformation work that makes AI possible. 
Among those on stage were Queensland’s Department of Transport and Main Roads, Fortescue, SA Power Networks, Woolworths, Zespri, TAFE NSW, Toyota Finance, Taronga Conservation Society Australia, Metcash, Linfox, Rheem and Suntory Oceania. 

“We’ve moved past asking whether AI matters,” said Angela Colantuono, President and Managing Director, 麻豆原创 Australia and New Zealand. “The question now is whether it’s making the difference that actually matters 鈥� and the organisations here today have answered that. They are also not waiting for perfect conditions. They are acting now, and that is what sets them apart. Rachel’s appointment reflects our commitment to helping our customers make that same shift.” 

麻豆原创 appoints Rachel Hunter as Head of AI, ANZ 
麻豆原创 also announced the appointment of Rachel Hunter as Head of AI for Australia and New Zealand (ANZ). Hunter brings more than 25 years of experience leading cloud, data and AI teams across Asia Pacific and ANZ, most recently as General Manager, Cloud, Data and AI at Davidson. 
She also founded DataSeeds Consulting and has held senior leadership roles at Databricks and Oracle. At 麻豆原创, Hunter leads AI Customer Advisory across ANZ, helping organisations translate AI ambition into practical, governed and scalable adoption. 

“AI has already found its place in Australian and New Zealand business; not in the strategy deck, but in the day-to-day,” said Hunter. “The most widely used applications are helping finance teams process invoices faster, helping marketers personalise connections with customers and helping operations teams catch problems before they escalate. This is not experimental AI. It is already working.” 

What Australian and New Zealand businesses are听actually doing听with AI听
麻豆原创’s analysis of the most widely deployed AI use cases across its ANZ customer base for the twelve months to听mid-year听2026 shows AI is already embedded in everyday business operations 鈥� from听tailoring marketing emails to processing invoices听and听monitoring operations in real time.听

The analysis underlines how Australian and New Zealand听organisations听are embracing AI to automate core business tasks.听Finance automation accounts for three of the top five听use cases, with AI removing manual, error-prone work from expense processing, invoice听capture听and compliance.听Meanwhile, marketing intelligence听is strongly represented, reflecting how deeply AI has already embedded itself in听customer engagement, while听the presence of AI infrastructure听use cases听may signal a growing understanding that听maximising听value from AI is dependent on business context and cross-organisational听integration.听

The Autonomous Enterprise听
麻豆原创 reinforced its vision for the Autonomous Enterprise at the event 鈥� a future where AI is embedded into the business applications听organisations听already rely on. Networks of AI agents are increasingly able to understand business context, recommend actions and execute routine work across finance,听procurement, supply听chain听and HR under human oversight,听fundamentally transforming the future of work.听

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SYDNEY 鈥斕�The business functions with the greatest potential to unlock enterprise-wide AI value may also be creating its biggest constraints, according to听a听new听analysis of听global research released today at 麻豆原创 NOW in Sydney.听听

The new research found that, while enthusiasm for enterprise AI is driving both investment and ROI, siloed adoption has created five enterprise fault lines that threaten to mitigate potential gains. In particular, Finance teams are forging ahead in a silo, Legal teams are struggling with governance gaps, shadow AI is rife in customer-facing teams, HR is managing a data deficit and Procurement teams are dealing with innovation outrunning its foundations.  

“Organisations听aren鈥檛 missing out on value from AI听because听they听lack ambition or investment.听Instead, the dollars are falling through听the听cracks听between functions,” said Rachel Hunter, Head of AI, 麻豆原创听Australia听and New Zealand. “The听organisations听that make the most of AI听will be those听who remove AI sprawl and听connect the discipline of Finance, the oversight of Legal, the pace of听Sales and Marketing, Procurement’s innovation and the workforce focus of HR around trusted data and shared outcomes.”

Organisations听aren鈥檛 missing out on value from AI听because听they听lack ambition or investment.听Instead, the dollars are falling through听the听cracks听between functions.

Rachel Hunter

Inconsistent AI sprawl across functions has enterprise-wide consequences for outcomes 

The new insights have been sourced from the 麻豆原创 Value of AI 2026 report, which spoke to 2,600 business leaders across 13 countries to explore how business invest, implement, and drive value from AI. The new analysis has identified key challenges across five critical business functions. 

Finance is mature but its silos could slow everyone else.听听

• Finance听respondents noted they had invested more than any other function, leading to 65% noting they were scaling or leading in AI automation and 52% scaling or leading in generative AI.
• Yet only 16 per cent of its AI is currently deployed across functions, though that鈥檚 expected to rise to 45 per cent in just two years.  
• Only 34 per cent of Finance respondents consider themselves data ready for AI, and integration or interoperability is its largest agentic AI barrier. Given Finance touches all points of the enterprise, keeping its AI capability siloed may limit far more than Finance’s own returns. 

Legal is least ready to govern the AI it is most aggressively deploying.听听

• Legal respondents apply AI to more tasks than any other function at 33 per cent today, which is expected to reach 50 per cent in two years.  
• Yet 49听per cent say AI is not delivering its full potential, the highest of any function.听听
• While Legal respondents were most likely to note听a defined AI strategy听at the leadership level (82%),听it also reported听the lowest听governance听readiness听for AI processes and frameworks听at 26 per cent. The function intended to provide the guardrails听is itself听most in need of stronger foundations.听

Customer-facing teams are moving fast and creating governance exposure.听听

• Sales and Marketing respondents have the second highest data readiness at 63 per cent, trailing only Operations, and the ranked the highest for piloting agentic use cases (68%).  
• Yet more Sales and Marketing respondents said st shadow AI was the most material AI risk to them at 80 per cent,  while 73 per cent reported shadow AI use at least occasionally. The function may be moving faster than its data readiness or governance today. 

HR could听lead workforce transformation if its data can earn trust.听

• HR respondents emerged as one of the front leaders in Generative AI maturity, with 24 per cent leading in implementations despite respondents having the one of the lowest average AI spending levels at US$25.1 million.  
• Yet data readiness stands at just 37 per cent. In a function responsible for the enterprise’s most sensitive workforce decisions, that data gap could undermine the transformation HR is best placed to lead. 

Procurement’s听innovation is outrunning its foundations.听

• Procurement respondents are ahead of most other functions in leading agentic AI maturity and cross-functional AI deployments, despite lower spending than some functions like Finance. 
• Its听respondents are also听strategically aware, being the most likely to agree听(78%)听that听delivering ROI from AI听requires data听readiness,听integration听and use-case readiness.听听
• Yet 86 per cent report incomplete or inconsistent data 鈥� the highest of any function. Procurement’s ambition is clear, but without stronger data foundations it risks creating isolated breakthroughs rather than scalable enterprise value. 

Strategic adoption, not investment, now determines value 

For leaders, the next phase of AI is not about adding more isolated use cases. It is about joining the strengths already present across the business to extending Finance’s discipline beyond its boundaries, equipping Legal to govern at the pace of adoption, bringing shadow AI into trusted environments, giving HR the data quality needed to transform work responsibly, and connecting Procurement’s innovation to dependable data and enterprise workflows. 

“The听organisations听pulling ahead will treat AI as an enterprise operating model, not a series of departmental technology projects,” said Hunter. “That means shared data, connected processes, clear governance and a workforce equipped to use AI with confidence. Investment matters, but integration is what turns it into value.”

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Sydney, 16 July 2026 | After years of having an acknowledged AI trust deficit, Australian businesses are embracing AI faster than ever, with investment, adoption and expectations on ROI all increasing according to new 麻豆原创 research. But that new-found confidence may also be creating new blind spots.

AI now supports over a quarter (29%) of tasks in the average Australian business, up from 25% last year¹, with leaders expecting that to reach 48% within two years, up from 41% in 2025. While Australia still trails high-adoption markets including the US, Germany, China, Japan and India, its higher-than-average pace of growth could potentially help close the gap.

The听麻豆原创 Value of AI Report 2026, conducted by Oxford Economics across more than 2,600 business leaders in 13 countries, identifies a clear gap between Australia鈥檚 AI ambition and its readiness to deliver on it, particularly around data foundations, governance frameworks and leadership oversight.

鈥淭hink of this as Australia鈥檚 AI school report: improving, but still not working to its potential,鈥� said Angela Colantuono, President and Managing Director, 麻豆原创 Australia and New Zealand. 鈥淲ith an estimated AU$150 billion of AI-related infrastructure investment promised over the next several years, Australia has a once-in-a-generation opportunity to turn AI confidence into national competitive advantage. But infrastructure alone won鈥檛 get us there. And with multiple new AI obligations coming into play for Australia between now and the end of the year, driven by local and international regulation, organisations need to strengthen their data foundations, governance frameworks and leadership structures. Otherwise, we risk building the rails for an AI economy without being ready to run on them.鈥�

Investment and ROI is accelerating

As an average, Australian organisations expect to spend approximately AU$35.5 million² on AI this year, up from AU$27.5 million last year, with a further 44% increase expected over the next two years. That said, Australian spend still trails the global average of AU$40.4 million by around AU$5 million, a gap that reflects both the opportunity and the urgency to move faster.

Returns are growing alongside that investment. Australian companies expect to drive ROI of 19% this year, up from 15% last year, and rising to 37% in two years 鈥� though still below the global average.

“The returns are starting to come but not fast enough, and not for everyone. AI value compounds over time. The organisations that act now, focus on the right end-to-end processes and get their data in order will look back in two years and be glad they did. The ones that wait will be asking why the gap got so hard to close,” continued Colantuono.

Agentic AI is central to those ROI expectations. ROI from agentic AI is expected to reach AU$21.2m in the next two years, more than quadrupling from last year鈥檚 estimates of AU$4.4m. Despite this, 62% of Australian businesses say they are satisfied with their current AI ROI, even though over half acknowledge AI is still not achieving its full potential.

Governance needs work

The governance picture is more concerning. Only one in five (22%) say they are mostly or fully ready in AI governance when it comes to skills and expertise, against 33% globally. Some 42% suggest they are deploying agents faster than they can standardise and govern them, rising to 68% when including those who are unsure. Over half (54%) of business leaders say employees are increasingly accepting AI outputs without sufficient scrutiny.

The operational risks are real: 43% do not have human-in-the-loop processes for agentic workflows, while nearly half (49%) report that AI agents have already taken incorrect actions during pilots or deployment, typically causing some rework and delays.

Leadership structures also trail global peers. Under half of Australian companies have a dedicated AI leader responsible for AI adoption (46%), leadership KPIs for AI (33%), or even training on AI capabilities and risks (41%).

Professor Toby Walsh, Scientia Professor of Artificial Intelligence at UNSW鈥檚 School of Computer Science and Engineering, said 鈥淟ack of understanding risks driving decisions by fear rather than evidence, and so closing the governance gap must start with closing the trust gap. Artificial intelligence is only valuable if people know when to trust it, and when to question it. Good governance shouldn鈥檛 be viewed as slowing innovation. It鈥檚 what allows organisations, employees and the broader community to adopt AI with confidence.鈥�

Data recognised as essential, but readiness lags

While Australian leaders rank integrated data systems (64%) and data quality (51%) as the biggest enablers of AI readiness, data quality remains the biggest challenge for AI in Australia, with the share of businesses that say they are data-ready for AI falling from last year; nearly three-quarters (73%) report challenges with poor data quality.

Sovereign AI requirements are also shaping how organisations scale 鈥� 99% of Australian organisations say they now operate under some form of sovereign AI framework or requirement, and 76% cite data residency constraints that limit model choice.

Workforce readiness will determine whether momentum translates into value

More than four in five (82%) Australian businesses are not convinced their upskilling is keeping pace with AI鈥檚 rapid evolution, while 77% report shadow AI occurs at least occasionally. Only 1% of leaders believe AI will have no impact on workforce planning.

鈥淭hese findings point to an urgent need for role-specific training, stronger safe-use guidance and change management that brings employees along as AI becomes embedded in daily work,鈥� said Colantuono.

Confident adoption, early stage maturity

Australia鈥檚 maturity is progressing, particularly in generative AI, where 53% of organisations are scaling or leading 鈥� close to the global average of 54%, but still 17 percentage points behind the US, China and Germany. The gap is wider on agentic AI, where only 19% are scaling or leading versus a global average of 24%.

On more established technologies, Australia sits close to the global average in software automation and RPA but trails in traditional machine learning at 52% who are scaling or leading versus 59% globally.

In addition, the dominant adoption pattern remains project-by-project 鈥� targeted deployments within individual processes rather than coordinated, enterprise-wide transformation. Additionally, Australian organisations are less likely than global peers to connect AI strategy to industry-specific priorities.

鈥淎ustralia has moved from AI hesitation to AI momentum,鈥� Colantuono concluded. 鈥淣ow we need to turn that momentum into maturity: stronger governance, better data and a workforce ready to use AI with confidence. Get that right, and Australia won鈥檛 just catch up, it can lead the world in responsible, high-impact AI,鈥� concluded Colantuono.

More information on the research will be shared at the 麻豆原创 NOW AI Tour taking place at the Hordern Pavilion in Sydney on 12 August.听 For more information or to register, click .

For the full report click here: 麻豆原创 Value of AI 2026 Australia

¹ For the 麻豆原创 Value of AI 2025 research findings, click here.

² Respondents were asked to provide听financial听estimates in USD. AUD figures are based on an听exchange听rate听of AUD $1 = USD$0.69, using the exchange rate听as of 13 July 2026.

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