Singapore finance leaders see scaling artificial intelligence as the biggest hurdle to broader adoption, according to a Forrester report commissioned by fintech firm Airwallex.
Survey shows reluctance to expand AI use
The study covered 11 markets and surveyed more than 1,200 finance decision makers, including 105 respondents from Singapore. It found that 30 percent of those leaders do not plan to increase AI adoption in the next year, indicating a shift toward extracting more value from current investments.
By contrast, 46 percent said their organisations intend to expand AI use within twelve months, a rate slightly higher than the global figure of 41 percent. Overall, about 86 percent reported that AI is already part of some finance workflows, compared with 84 percent worldwide.
Key barriers to scaling
Data quality emerged as the top obstacle. 64 percent cited fragmented or inconsistent data as a core barrier, matching the global average of 65 percent. The report also noted a technology‑specific challenge: limited ability to monitor, test or validate AI outputs was more frequently mentioned by respondents than the data‑related issue.
Skill gaps and limited experience with AI‑enabled finance processes topped the list of hurdles for both local and global leaders. Building a business case beyond short‑term productivity gains proved difficult, while risk, compliance or reputational concerns were more prominent elsewhere.
In the autonomous AI arena, the region appears ahead. 18 percent said their organisations use AI to execute tasks with minimal human input, compared with 11 percent worldwide. The gap is especially noticeable in bookkeeping, close and reporting, where 27 percent run AI autonomously versus 14 percent globally.
What finance leaders expect from AI
The top expectation for the coming year is that AI will generate forecasts and “what‑if” scenarios to aid human decision‑making. Identifying patterns, trends and root causes to provide analysis for decision makers ranked second.
Most organisations source AI capability through a mix of in‑house teams and external providers. Seventeen percent rely solely on internal resources, while another seventeen percent outsource the entire function.
At wealth platform Endowus, chief financial officer Dominic Ong described how AI has brought previously outsourced finance functions in‑house, allowing the team to stay small—four members in total. AI now scans receipts, suggests appropriate accounting entries, and double‑checks transactions. Ong also created a custom tool with Claude to perform routine end‑of‑month checks, freeing him to focus on higher‑level CFO responsibilities.
For employees on the finance floor, the shift means less time spent on repetitive verification and more emphasis on strategic analysis, a change that could reshape daily workflows and career paths.
The report notes that while the city‑state is modestly ahead in AI adoption, the same challenges—data fragmentation, skill shortages and validation difficulties—remain significant. Addressing these issues will be essential for firms that hope to move beyond pilot projects toward fully integrated, autonomous AI solutions.