Singapore businesses adopt agentic AI faster than they can audit its decisions

A significant majority of Singapore businesses are actively testing or operating artificial intelligence systems capable of executing connected tasks with minimal human intervention. However, fewer than a third possess the capability to generate clear records explaining how these automated tools arrive at their conclusions. According to a study conducted by Sumsub alongside the Singapore Fintech Association, 94% of local firms currently deploy or pilot multi-step AI systems, yet only 29% can maintain an audit trail for autonomous decisions.

This disparity creates a troublesome divide between governance accountability and tangible proof. While an enterprise might designate an individual to oversee a system, it often remains unable to reconstruct specific actions, verify underlying data inputs or explain individual outputs.

The findings stem from the APAC State of Digital Trust AI Governance Benchmark, which evaluated regional enterprises across three distinct pillars. These criteria assessed the operational independence of AI applications, the allocation of formal responsibility for outcomes and the technical capacity to trace and explain decision-making processes after execution.

Responsibility is clearer than traceability

Formal governance structures are already widespread across the local market, with roughly 70% of Singapore businesses establishing clear guidelines to assign accountability for AI outcomes. Within this group, 40% assign responsibility to specific individuals while 30% designate whole teams, closely matching the broader regional average across APAC. Organisations also show greater comfort delegating low-risk, routine tasks to automated systems than high-exposure financial processes, with 90% comfortable utilising AI for low-risk activities compared to an APAC average of 88%. Meanwhile, expansion remains deliberate, as only 16% of local firms significantly expanded the scope or independence of their AI tools over the past year, marking the most measured growth rate among surveyed APAC markets.

Data-related tasks represent the primary area of impact for local AI deployment, as highlighted by 29% of Singapore businesses. Operations and workflow processing accounted for 21% of reported impact, whereas 15% of enterprises identified key applications within risk monitoring, anti-money laundering and fraud detection.

Holly Fang, President of the Singapore Fintech Association, said, “Everyone is focused on how quickly AI is advancing, but the bigger question is whether governance is keeping pace. Our joint survey with Sumsub found that fewer than one in three organisations can produce an audit trail for AI-driven decisions. As AI moves beyond copilots into autonomous agents handling increasingly critical workflows, the focus now should be on building the traceability, accountability and governance needed to deploy AI at scale. As an industry, that’s where our attention needs to be next.”

Technical gaps limit higher-risk adoption

Singapore recorded an overall governance score of 65.6 in the benchmark, placing it slightly below the APAC average of 67.1. The report attributed this position in part to the country’s mature regulatory environment, noting that the Model AI Governance Framework for Agentic AI, introduced earlier in 2026, encourages companies to benchmark their operations against concrete governance expectations rather than high-level policy promises. Sumsub suggested that the score reflects a more cautious and realistic self-assessment rather than a lack of progress in governance.

“Prudence, rather than a lack of strategic intent, defines how the enterprises are scaling AI agents,” said Penny Chai, Vice President, APAC at Sumsub. “When financial liabilities are on the line, immature traceability systems create an unacceptable operational risk. Establishing robust tracking architectures and guardrails is the vital prerequisite to safely deploying high-stakes AI at scale.”

Technical complexity remains the primary hurdle to robust oversight, cited as a major barrier by 66% of Singapore businesses. Half of the surveyed organisations experienced difficulties integrating AI tools with existing operational platforms, while 49% required improved mechanisms to track actions initiated by external or third-party AI software. These tracking hurdles become particularly severe when automated processes traverse multiple software applications, where enterprises require unbroken logs detailing which system executed an action, how a conclusion was formed and who bears ultimate responsibility.

Market appetite for external verification mechanisms remains notably high. Approximately 98% of Singapore businesses expressed readiness to implement third-party solutions capable of linking autonomous actions directly to verified identities and human supervisors.

Across the wider APAC region, heavily regulated industries demonstrated superior governance performance. Financial services led all sectors with a benchmark score of 69.6 and an audit trail adoption rate of 68%. IT and software services followed closely with a score of 68.8, although the report cautioned that rapid technology deployment in the tech sector risks outpacing established governance controls.