The IDC Data and AI Pulse: Asia Pacific 2024 study, commissioned by SAS, has revealed Asia Pacific (APAC) organisations are rushing to jump onto the AI bandwagon, with nearly half (43%) planning a large investment increase in AI, of over 20%, in the next 12 months.
According to the study, while organisations are investing heavily in AI, only 18% of APAC businesses identify as AI Leaders, highlighting a significant gap between those driving long-term transformational change and the majority who are merely experimenting with various projects without a clear AI strategy. In Australia, just 9% of participants were in the AI Leader category – half the rate of the APAC overall average. The majority of Australian businesses identify in the mid stages of their AI maturity journey.
“Around one-third of Australian businesses surveyed are just beginning to evaluate AI and consider how best to invest in this space,” says Craig Jennings, Vice President, SAS, Australia and New Zealand. “Australian organisations can see the potential for growth that AI brings, and return expectations are high. However, it is critical these organisations get the foundations right to ensure AI success, and we must seek to bridge the AI skills-gap that is holding back many organisations from reaping true business value.”
Of those surveyed across APAC, AI Leaders indicated their top business outcomes from AI initiatives are focused on driving new revenue growth (32%), increasing operational efficiency (31%) and increasing profits (26%). By comparison, AI Followers indicated improving customer service (27%), expanding market share (25%) and faster time to market (25%) as their top business outcomes.
“The disparity in target outcomes between AI Leaders and AI Followers demonstrates a lack of clear strategy and roadmap. Where AI Followers are focused on short-term, productivity-based results, AI Leaders have moved beyond these to more complex functional and industry use cases,” said Shukri Dabaghi, Senior Vice President, Asia Pacific and EMEA Emerging at SAS.
"As businesses look to capitalise on the transformative potential of AI, it’s important for business leaders to learn from the differences between an AI Leader and an AI Follower. Avoiding a ‘gold rush’ way of thinking ensures long-term transformation is built on trustworthy AI and capabilities in data, processes and skills," said Mr. Dabaghi.
"The IDC Data and AI Pulse: Asia Pacific 2024 study is an important snapshot of how hundreds of large APAC organisations are approaching adoption and implementation of AI, highlighting the leaders and followers across industries,” said Chris Marshall, Vice President, Data, Analytics, AI, Sustainability, and Industry Research at IDC Asia/Pacific. "These insights give us the opportunity to unpack the barriers to successful AI implementation, allowing businesses to make wiser investments into these new and emerging technologies, without being caught-up in the gold rush”.
Generative AI is only one part of the AI journey
While a great deal of AI hype has focused on generative AI, the study reveals that organisations have also been investing in predictive and interpretive AI. In 2023, generative AI accounted for just 19% of total AI investment but by 2024, it is expected to increase to 34% reflecting a more balanced spending distribution across these three AI categories.
The research suggests AI spending in Asia Pacific will reach US$45 billion in 2024, rising to US$110 billion by 2028 at 24% CAGR (2023-2028).
The study finds that Australia continues to show significant interest in AI, with 35% of organisations planning to increase their AI investment in 2025.[2]
The research reveals that organisations are reallocating budgets for the 2024 increase in generative AI investment, with a third saying it will come from redistributing funds away from infrastructure modernisation and 37% from application modernisation.
Expectations are high when it comes to ROI
The study reveals this prospective gold rush is fuelled by inflated expectations of AI’s potential return on investment. The research found that 40% of organisations surveyed expect at least a three-fold return on investment, with the “fear of missing out” continuing to spur AI spending, with Australian businesses reflecting this sentiment to ROI, expecting up to three times their investment. As a result, the research shows AI has at times been adopted without a clear alignment between investments and their outcomes and business value.
Where organisations are struggling to implement AI technologies, top challenges facing Australian businesses are lack of skilled personnel (35%) and data governance processes (30%), while needing to navigate operations in a highly regulated industry was also a major factor (30%). The data specific challenges that lead to AI failure for Australian respondents are led by data engineering complexity (41%) and inability to access data due to infrastructure restrictions (41%).
With 43% of organisations planning to increase their AI investment by 20% or more in the next 12 months, organisations risk being disillusioned with AI because of these tactical investments’ likely returns. Instead, business leaders should realise that building an AI capability takes time and requires solid AI foundations to ensure long-term value add.
"While consumer access to generative AI tools made AI feel magical, integrating it into an enterprise environment takes a lot of work, the right infrastructure, and often the high expectations placed on these tools are unrealistic," says Mr. Dabaghi. "Understanding these pitfalls provides us the opportunity to learn how we tackle these issues, enabling a higher success rate, and meeting business objectives when it comes to adopting and successfully implementing AI.”
The researched showed that in Australia, AI performance is increasingly driven by efficient data and model management, alongside growing considerations for regulatory compliance. This balanced approach strongly focuses on using robust data platforms to streamline data management and model oversight, enhance collaboration across teams, improve data management, and provide real-time insights.
Pulse of AI across industries
The study provides a detailed analysis of how AI is impacting different industry sectors in the APAC region, with key focus areas including banking, insurance, healthcare, and government sectors.
The skills-gap remains a consistent challenge across industries when it comes to successful AI adoption and implementation. This skills-gap is felt the most within the healthcare industry (41%), followed by the government sector (38%), insurance industry (32%), and less so in banking (29%). Despite this challenge, these industries continue to invest in improving their data and AI capabilities to deliver more streamlined decision-making, greater automation, faster time to market for new products and services, cost savings, and a host of other benefits.
Nonetheless, some use cases are being consistently and successfully deployed - in banking for instance, with its top three use cases: liquidity risk management, asset and liability management and financial crime analytics. In insurance, the research suggests we are seeing AI use cases for insurance claims fraud, omni-channel delivery of products and intelligent pricing. In health care, notable use cases include health care fraud and cost containment, while in government, the popular AI use cases relate to ensuring social benefits programme integrity, supporting emergency response, and tax and revenue compliance.
AI adoption trends vary across countries
The AI landscape in APAC varies by country, with each market showing unique adoption trends. China is leading in AI investments, showing a large increase in AI projects over the next 12 months (59%), with India and Japan following suit (51%; 46% respectively).
