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.”

The post Mind the gap: How听AI sprawl听sees value from AI fall through the cracks听 appeared first on 麻豆原创 Australia & New Zealand News Center.

听At its flagship event , (NYSE: 麻豆原创), today highlighted the five most widely adopted AI use cases among its Australian customers. Based on analysis of all 麻豆原创 customers in Australia and New Zealand (ANZ) between May 2024 to May 2025, the most popular AI use cases in ANZ, these include:听

• Automated expense generation using receipt images听

• Automated invoice processing听听

• Expense verification and compliance checks听

• Real-time alerts for supply chain disruptions听

• Sales demand forecasting powered by predictive analytics听

鈥淢y conversations with CEOs are increasingly revealing how they are looking to embed AI into some of the most fundamental parts of their business,鈥� said Angela Colantuono, Managing Director, 麻豆原创 Australia. 鈥淭hese applications are helping Australian organisations make faster, smarter decisions, reduce risk and unlock new value. But to fully realise AI鈥檚 potential, we need to invest just as much in people as we do in technology.鈥�听

Dr Catriona Wallace, AI Ethics Expert and Founder, Responsible Metaverse Alliance, who keynoted at the event shared, 鈥淎I is the number one existential risk we face today. Yet only a small fraction of Australian organisations are equipped to use it responsibly. If we want AI to drive innovation, productivity and public trust, we must move beyond ambition to action. That means embedding responsible AI frameworks that are transparent, ethical and human-centred, and doing it now, before the gap between use and governance becomes too wide to close.鈥�

Customers and partners across Australia and New Zealand show AI momentum听

From education to manufacturing, 麻豆原创 partners and customers are also showcasing strong momentum in AI and cloud transformation.听

La Trobe University has become the first university in the ANZ region to go live with 麻豆原创 S/4HANA Cloud Public Edition leveraging the GROW with 麻豆原创 transformation journey.听 From the move, La Trobe has been able to modernise its core operations across Finance, Procurement, Logistics, Sales, R&D Engineering and Real Estate and lay the groundwork for future innovation, including AI-driven insights and automation.听

鈥淭his transformation is a major step forward in how we operate,鈥� said Shainal Kavar, Chief Information Officer, La Trobe University. 鈥淚t鈥檚 helping us simplify complexity, streamline processes, improve reporting and decision-making and free up our people to focus on higher-value work. Most importantly, it sets us up to embrace innovation and unlock the potential of AI in the years ahead.鈥�听

Lion, one of Australia and New Zealand鈥檚 leading brewers, is accelerating its cloud-first transformation with RISE with 麻豆原创 on AWS. By adopting a clean core, the 麻豆原创 principle of keeping core ERP system free from customisations, as well as 麻豆原创鈥檚 Business Technology Platform, Lion has improved order-to-cash cycles, scaled digital channels, and empowered teams with real-time insights. The company also partnered with 麻豆原创 to build 鈥楯oey鈥�, an AI-powered beer recommendation app, in under 10 days, demonstrating the speed and value of 麻豆原创鈥檚 generative AI tools.听

鈥淎I is helping us move faster, make smarter decisions, and deliver better customer experiences,鈥� said Ram Kalyanasundaram, Group Technology and Digital Transformation Director at Lion. 鈥淚t鈥檚 not just about automation, it鈥檚 about enabling our teams to focus on what matters and giving them the tools to innovate. 麻豆原创鈥檚 AI capabilities have been a game-changer in how we think, operate and grow.鈥�听

麻豆原创 Intrepid Women AI Tour 2026听

麻豆原创 is also proud to announce the return of the 麻豆原创 AI Intrepid Women Tour in January 2026. This four-day executive study program is designed to empower female leaders with the skills, confidence, and strategic insight to lead in the age of AI.听

Following the success of the 2025 tour, the 2026 program will bring together Australia鈥檚 most influential female technology executives to explore AI innovation across 麻豆原创鈥檚 global innovation hubs.听

鈥淟ess than 15% of senior AI executives are women today,鈥� said Colantuono. 鈥淟ast year鈥檚 program proved that when you bring female leaders together to build AI literacy and share experiences, the impact is extraordinary 鈥� not just for their businesses, but for the future of innovation in Australia.鈥�听

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鈥�Media Contact:听

Rebecca English (+61) 438 520 181, rebec@sap.com, AEST
麻豆原创 麻豆原创 Room; press@sap.com听

About 麻豆原创鈥�

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