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Singapore firms see AI as a bigger challenge than cost—but results still lag
In Autodesk’s Singapore findings, 46% cite technology and AI developments as an organisational challenge, compared with 42% who cite traditional costs; nearly seven in 10 remain short of advanced AI goals.
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Key takeaways
- In Autodesk’s Singapore findings, 46% cite technology and AI developments as an organisational challenge, compared with 42% who cite traditional costs; nearly seven in 10 remain short of advanced AI goals.
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openai.comCreate a landscape editorial hero image for this Studio Global article: What do Autodesk’s 2027 State of Design & Make research, based on 150 Singapore design-and-make industry respondents, and Xero’s survey of 1. Article summary: The available evidence supports an adoption-to-results gap: businesses remain optimistic about AI, but rising costs, fragmented systems and shortages of data capabilities are slowing progress, with nearly seven in 10 sti. Topic tags: general, general web. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, charts with fake numbers, clic
Singapore businesses see artificial intelligence as a major opportunity, but translating that optimism into advanced use remains difficult. Autodesk’s 2027 State of Design & Make reporting says technology and AI developments are a leading organisational challenge for Singapore respondents—and that nearly seven in 10 remain short of their advanced AI goals. The available sources do not substantiate a full comparison with the Xero Singapore SME survey described in the question. 3
Technology and AI concerns edge out traditional costs
In the Autodesk reporting, 46% of Singapore respondents identified technology and AI developments as a leading organisational challenge, slightly ahead of the 42% who cited traditional cost concerns. At the same time, 75% believed AI would improve their industry. Together, those figures point to optimism alongside practical concerns about implementation—not a lack of interest in AI. 3
The same report says nearly seven in 10 respondents remain short of advanced AI goals. That finding signals a difference between seeing AI’s potential and reaching more sophisticated deployment; it does not, by itself, explain how much progress has changed year over year or how Singapore compares with the global average. The available excerpt does not provide those comparisons. 3
Investment does not guarantee implementation
Autodesk’s broader 2027 research says three-quarters of Design and Make organisations plan to increase AI investment over the next three years. It also reports that 40% have integrated AI into design workflows and 34% are implementing AI-driven automation. These are broader report figures, not Singapore-specific results, and they describe investment and implementation—not proven business returns. 22
Singapore manufacturing evidence offers useful context for why deployment can be hard: it identifies limited in-house AI expertise, poor or unstandardised factory data, and uncertainty about performance in live operations as adoption challenges. It also warns that without redesigning work, AI risks becoming a technical upgrade rather than a source of new capabilities and value. This is separate evidence, not a breakdown of Autodesk’s survey results. 21
What the available Xero evidence can—and can’t—show
The supplied Xero reference is about Australian accounting and bookkeeping practices, based on a survey of more than 500 professionals. It reports that 35% said AI helped them maintain or grow output without expanding headcount. That finding is not from the 1,018 Singapore SME owners and senior decision-makers described in the question, so it cannot establish Singapore SMEs’ adoption, returns, spending plans, data readiness, governance practices, or views on workforce change. 18
The available sources also do not substantiate the requested Singapore figures on hiring for data analytics, data science or data management; AI use in software workflows; connected-data confidence; implementation barriers; or the share of Autodesk “Pacesetters.” Those details should not be inferred from the separate sources cited here.
A practical test for sustainable AI results
The supported evidence points to a clear execution challenge: businesses can be optimistic and plan to spend more while still struggling with technology, skills, data quality and operational change. 3
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22 For organisations assessing an AI initiative, a useful test is whether the underlying data and systems are ready, employees have the capabilities to use the tools, and workflows are being adapted—not just whether a new tool has been purchased. The sources available here support those as relevant considerations, but do not quantify their prevalence across the Xero Singapore SME survey.
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In Autodesk’s Singapore findings, 46% cite technology and AI developments as an organisational challenge, compared with 42% who cite traditional costs; nearly seven in 10 remain short of advanced AI goals.
Sources
sbr.com.sgsbr.com.sg › firms-struggle-turn-ai-adoption-resultsFirms struggle to turn AI adoption into results
autodesk.comThe AI Imperative | State of Design & Make 2027 - Autodesk
edb.gov.sgThe latest in Singapore’s AI scene that businesses should know – a round-up from April to June 2026
xero.comAustralia's top accounting and bookkeeping practices ...