AI ‘gold rush’ reveals lack of clear strategy among late adopters

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 a report from IDC commissioned by SAS.

The study, conducted in June 2024, includes 509 executives across eight APAC markets, including Australia, China, India, Japan, Korea, Malaysia, Singapore, and Thailand.

While organisations are investing heavily in AI, only 18% of APAC businesses consider themselves as AI Leaders, leaving a large gap between those AI Leaders driving long-term transformational change, and AI Followers experimenting with numerous projects and lacking a clear AI strategy.

Of those surveyed, 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, SAS SVP for APAC and EMEA Emerging.

“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 Dabaghi.

Chris Marshall, VP of data, analytics, AI, sustainability, and industry research at IDC Asia/Pacific, said  these insights provide 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. 

While a great deal of AI hype has focused on generative AI, the study reveals that organisations have been investing into predictive and interpretive AI technologies. 

In 2023, generative AI accounted for just 19% of AI investment and is predicted to increase to 34%, reflecting a more balanced distribution across these three AI categories.

IDC’s latest spending guide suggests AI spending in Asia Pacific will reach $45 billion in 2024, rising to $110 billion by 2028 at 24% CAGR (2023-2028).

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.

The study reveals this prospective gold rush 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. 

As a result, the research shows AI has at times been adopted without a clear alignment between investments and their outcomes and business value.

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,” said 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,” he added.