SINGAPORE, November 18, 2024 – A new study by Economist Impact, commissioned by Databricks, reveals that ASEAN enterprises are at the forefront of leveraging data intelligence in artificial intelligence (AI). The report, titled “Unlocking Enterprise AI: Opportunities and Strategies”, highlights that 74% of ASEAN businesses are training their large language models (LLMs) with enterprise-specific data, compared to nearly half (49%) of data scientists across the Asia-Pacific region who continue to rely on general-purpose models.
General-purpose models, while widely used, lack the governance, quality, and contextual relevance that enterprise-specific data can provide. The findings come as global AI investments are projected to surge to US$1 trillion in the coming years, driven by businesses seeking to harness AI’s transformative potential.
Growing Investment, Persistent Challenges
The report surveyed 1,100 technical executives and technologists globally, including 100 respondents from ASEAN nations such as Malaysia, the Philippines, Singapore, and Thailand. It found that while 91% of ASEAN enterprises are already using generative AI (GenAI) in at least one function, only 32% consider their applications production-ready. Key hurdles include costs (40%), skills shortages (38%), governance issues (38%), and concerns over data quality (33%).
“AI is rapidly becoming an integral part of business growth strategies, but organisations must balance ambition with practical concerns around quality, cost, and implementation,” said Cecily Ng, Vice President and General Manager for ASEAN at Databricks. “Our customers in ASEAN need platforms that prioritise data privacy, governance, and sustainable costs to drive effective data intelligence. This report underscores why enterprises taking a holistic approach—spanning data management, governance, and domain-specific expertise—will lead their industries.”
AI Talent and Governance Gaps
The report also flagged significant gaps in AI talent and governance. Only 18% of ASEAN respondents are confident in their organisation’s ability to secure sufficient AI talent, while just 20% strongly agree that their data and AI governance frameworks are robust enough to meet evolving regulations. Fragmented data systems further complicate governance, discovery, and usage, highlighting the need for unified, open approaches.
“AI adoption brings immense potential, but unlocking that value requires businesses to overcome challenges in governance, talent, and data fragmentation,” said Tamzin Booth, Editorial Director at Economist Impact. “In an unpredictable world, data intelligence is a key differentiator. Enterprises must focus on producing high-quality outputs and seamlessly connecting AI to their workforce.”
ASEAN’s Long-Term Commitment to AI
Despite these challenges, ASEAN enterprises remain optimistic about AI’s potential. Nearly 77% of respondents view the technology as critical to their long-term goals, and by 2027, almost all (99%) expect to use GenAI across both internal and external functions. Additionally, 94% plan to deploy open-source AI models, indicating a shift towards greater flexibility and cost efficiency in their AI strategies.
Accenture’s Global Lead for Data and AI, Senthil Ramani, noted: “AI can deliver significant productivity gains and unlock new business opportunities when used strategically. Companies aiming to lead in AI need to integrate it across growth, customer experience, and risk management functions.”
Key Takeaways
- GenAI Usage: 91% of ASEAN businesses use GenAI, but only 32% consider applications production-ready.
- Talent Shortages: Just 18% are confident in securing adequate AI talent.
- Governance Concerns: Only 20% strongly agree that their AI governance is sufficient.
- Future Adoption: By 2027, 99% of respondents plan to implement GenAI, with 94% favouring open-source AI models.
With AI continuing to redefine business landscapes, the report underscores the need for ASEAN enterprises to prioritise governance, innovation, and workforce integration to maximise returns on their AI investments.