Organizations in Australia and New Zealand (ANZ) are investing in AI generated at a higher rate than their global counterparts, but more often experience cost blowouts when it comes to staffing for these initiatives.
32% of ANZ organizations are directing more than a quarter of their tech budgets towards AI for the next 12 months (25% worldwide). ANZ respondents have seen a 44% return on AI investments. Compared to the global average, ANZ organizations are more likely to cite increased customer satisfaction as an important goal for their AI initiative, and are less likely to prioritize internal improvement projects (47% vs. 55%). The staffing costs for ANZ generation AI were higher than expected (63% for ANZ vs. 48% worldwide).
This is according to the findings of the “radical ROI of Generated AI” from Snowflake (NYSE: Snow), an AI Data Cloud Company. A global research report, conducted in collaboration with the Enterprise Strategy Group, examined 1,900 businesses and IT leaders from nine countries. Everyone actively uses generated AI for one or more use cases.
According to the report, early AI adopters in ANZ reported that their efforts with GEN AI were more likely than the global average, reporting that the organization allowed better, faster decisions (91% vs 84% globally), and slightly higher than the average ROI due to GEN AI spending (41% vs 41% on average).
“We are pleased to announce that the company is offering a wide range of services and services that are currently being used to provide a wide range of services,” said Theo Hourmouzis, Senior Regional Vice President, Australia, New Zealand and ASEAN SNOWFLAKE. “There is a clear appetite and willingness to advance the AI curve, but there are hurdles local businesses and IT leaders struggle to overcome. The two biggest challenges are talent and data.”
Promote better customer experience through AI investment
The report found that 32% of ANZ organizations have more than a quarter of their technology budget towards Gen AI for the next 12 months, revealing that customer experience has emerged as a critical outcome.
Compared to the global average, ANZ organizations more frequently cite improved customer satisfaction, delivering personalized experiences, and improving customer engagement as key goals in their AI strategies (global average of 53% vs. 43%).
Given that focus, it is not surprising that ANZ respondents are likely to emphasize GEN AI projects for end customers (53% vs. 44%), while less for employee initiatives (47% vs. 55%).
“Improving the customer experience is where local organizations focus on GEN AI strategies, and many businesses already offer clear benefits,” says Hourmouzis. “Top local customers in industries such as retail, banking, aviation and public sectors are already enjoying the benefits of a customer-focused strategy using snowflakes to make better decisions faster.”
Despite overall satisfaction, not everything sails smoothly
ANZ respondents reported specific challenges more frequently than the global average in the Gen AI initiative.
Many competing priorities: ANZ respondents often struggled to identify the right use cases (71% vs. 54%). Data Disorders: Compared to the global average, local organizations cited data diversity/scopy (56% vs. 42%) lack of data diversity/scopy (56% vs. 42%) (56% vs. 42%), data management tasks (62% vs. 55%), and data preparation (59% vs. 51%) more frequently as difficult areas. Furthermore, ANZ organizations frequently say that data silos are difficult to break down (76% vs. 64%). Unexpected Costs: A majority (84%) of ANZ organizations say that more than half of GEN AI use cases cost more than they are expected to enter production, compared to the global average of 78%.
At this last point, it appears that one of the main causes of unexpected costs is the human factor. The report found that the cost of staffing for Gen AI is often higher than expected on ANZ (63%) than expected than the global average (48%).
“It is important to note that the industry is still in the relative early stages of AI adoption,” Hourmouzis said. “These challenges, including talent issues, will be like a sea decline 10, 20, 30 years from now, once AI evolves into a normal, everyday part of our business life.”
“The first step for local businesses is to address data issues. Without an effective data strategy, they will have a hard time having an effective AI strategy. Once the foundation is revised, the rest will be appropriate.”
There is a great opportunity for businesses to overcome these challenges and maximize their data potential to achieve more accurate, relevant and impactful AI results with a unified data platform.
learn more:
Read the full research report titled “Radical ROI of Generated AI” and double-click on the findings in this blog post. Learn how Snowflake offers thousands of users an easy-to-use, connected, trusted and robust platform to support both current and future AI needs in this blog post. Learn more about how global organizations can start AI data agents today, define your ROI framework, measure the business impact of this, and measure the practical guide to AI agent ebooks. Stay above the latest news and announcements from Snowflake on LinkedIn and Twitter/X
Methodology
Researchers at the Enterprise Strategy Group conducted deeper research using early recruiting organizations from November 21, 2024 to January 10, 2025. This is already augmenting and running the business process of production using commercial and open source models rather than consumer grades such as ChatGPT, and commercial and open source models subscription software. Of the 3,324 respondents, 1,900 (57%) said they were using commercial or open source generator AI solutions.
