Sydney, Australia – 19 October – 麻豆原创 Australia and New Zealand (ANZ) today announced the launch of its Supply Chain Centre of Excellence (CoE), a new regional capability designed to help asset-intensive organisations modernise their supply chain and asset management operations using cloud, AI, data and automation. 

A recent IDC White Paper showed that 75% of survey respondents cited legacy drag as a key impediment to responding more effectively to disruption.* The CoE helps customers accelerate their transformation from legacy systems to scalable cloud platforms, and use AI, data and automation, to improve supply chain performance, strengthen asset management, and deliver measurable returns faster.

The study further stated that 58% of COO鈥檚 say a focus on cost-efficiency at the expense of resilience is a key challenge to be faced over the next 12 months. *

鈥淥rganisations across Australia and New Zealand are facing an unprecedented level of global disruption from the constraints on major trading routes, to increasing pressure on critical resource,鈥� said Angela Colantuono, President and Managing Director, 麻豆原创 ANZ. “Resilience is a competitive advantage. This Centre of Excellence aims to give customers and partners a practical way to connect systems, break down silos and use real-time data and intelligence to anticipate disruption and respond faster.鈥�

Capabilities driving faster ROI

The CoE brings together sector-specific expertise in industries including energy, mining, public sector, transportation, oil and gas inAustralia and New Zealand. Building on an established 麻豆原创 SCM consulting practice, the CoE offers customers access to a team of over 26 dedicated supply chain consultants, providing access to broader expertise and support.

Combining industry expertise, 麻豆原创鈥檚 technology and best-practice implementation approaches, the CoE delivers tailored solutions that support faster transformation and lasting performance improvement. 

The CoE draws on 麻豆原创鈥檚 autonomous enterprise and AI innovations, including more than 70 AI agents across planning, manufacturing and logistics, to help organisations detect disruptions earlier, model scenarios faster and accelerate decisions from days to minutes. 麻豆原创鈥檚 AI-powered Supply Chain Orchestration also enables dynamic rerouting and continuous simulation of transportation plans as conditions change. 

The capabilities of the CoE are intended to support organisations across the full end to end supply chain activities, including helping them to:

• Adopt and leverage new technologies and digital operations
• Access real-time data and analytics for more informed decision-making
• Move from reactive fixes to planned听and听predictive interventions,听with the aim of听improving first-time fix rates through stronger asset health visibility, and digital work execution
• Improve integrated planning and scheduling intra and inter organizationally
• Optimise procurement, strategic sourcing, supplier integration, logistics and routing听
• Optimise working capital and operating costs听

The Centre is now fully operational across Australia and New Zealand as part of 麻豆原创鈥檚 global network of industry and functional experts.

Scaling transformation through partners
The CoE also has a deep collaboration with 麻豆原创鈥檚 partner ecosystem to expand delivery capacity and accelerate customer outcomes across the region. 

鈥淭he CoE enhances our ability to support partners in modernising their customers鈥� supply chain and asset management operations by providing access to specialised 麻豆原创 expertise when needed. It strengthens governance, improves collaboration, and delivers greater value for customers by aligning all stakeholders around a shared vision,鈥� said Sam Mani, Chief Partner Officer, 麻豆原创 ANZ

 Visit the . Get 麻豆原创 news via  and .

About 麻豆原创
As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

The post 麻豆原创 launches Supply Chain Centre of Excellence in ANZ appeared first on 麻豆原创 Australia & New Zealand News Center.

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.

The post The Humanity and AI of It All: The State of Customer Experience appeared first on 麻豆原创 Australia & New Zealand News Center.