APAC AI Spending Outruns The ROI Scorecards Leaders Need
Asia Pacific companies are investing faster in AI than peers elsewhere, but survey data shows CEOs, finance leaders and IT teams still measure returns differently.
Tech Collective Southeast Asia published a contributed analysis arguing that Asia Pacific’s AI budgets have moved faster than the management systems used to judge them.
The regional spending base is substantial.
The article uses Forrester’s 2025 State of AI Survey and Anthropic’s 2025 usage index to place Singapore, Australia, New Zealand and South Korea among the five highest-ranked countries for AI use.
It also contrasts annual AI budgets by region: 26% of companies in APAC fall in the US$400,000-to-US$500,000 band, ahead of 19% in North America and 17% in Europe.
The harder question is whether that money is producing results that executives read the same way.
SAP Concur’s CFO Insights Survey puts the internal split in numbers: AI returns are viewed as on track by 37% of CEOs, 41% of finance leaders and 49% of IT leaders.
That order matters because technology teams tend to see workflow gains first, while finance chiefs and chief executives have to convert those gains into budgets, forecasts and board language.
Finance functions are already using AI in practical work.
J.P. Morgan’s 2026 Asia Pacific CFO outlook lists data analytics and forecasting as an AI use case for 44% of leaders in the region, and routine-task automation for 36%.
Those deployments can shorten work cycles, but the article’s SAP Concur data shows that uncertainty remains high: 38% of finance leaders and 39% of CEOs still classify the value question as unresolved, and only 16% of IT leaders say returns are beating expectations.
The measurement problem is now slowing adoption.
SAP Concur’s survey puts the adoption brake at 54% of CEOs and 50% of finance chiefs who say difficulty assessing returns is holding back AI decisions.
Responsibility is also unusually centralized in the region: 33% of APAC respondents name the CEO as the main owner of AI strategy, versus 18% in North America and 8% in Europe.
That can quicken approval, but it also concentrates risk when business, finance and technology teams are not judging the same evidence.
Leadership groups broadly agree on the first three yardsticks: productivity and saved time, better accuracy and quality, and lower costs.
After that, the priorities separate.
Risk and compliance carry more weight for IT and finance, while CEOs put greater emphasis on security and technology exposure.
Customer experience sits lower in the ranking, leaving many finance AI programmes tied to internal efficiency rather than revenue-facing proof.
Other regional surveys explain why clean ROI is difficult.
Deloitte’s 2025 Asia-Pacific CFO survey names talent shortages as the leading deployment barrier, at 55%.
Data and technology resource limits follow at 44%, while risk and governance issues account for 39%.
SAP Concur’s own survey adds another caution sign: 53% of finance leaders say AI benefits take time to show up, and 51% say early expectations were probably too ambitious.
Data readiness is the second constraint.
NTUC LearningHub’s 2026 financial-services research found that Singapore sector leaders point to data governance and privacy compliance at 34%, and fragmented or poor-quality data at 31%, as obstacles to scaling AI.
Half of APAC financial-services firms have AI in selected departments only, while 20% remain exploratory or pre-adoption.
ISG’s 2025 enterprise AI research gives the global comparison: 89% of enterprises see at least some productivity lift, but 23% can put hard numbers behind it.
The next stage of APAC enterprise AI therefore depends on operating discipline rather than another broad spending push.
Common ROI dashboards, faster-cycle finance use cases and data governance attached to each investment case would give leaders a better test of which AI projects are creating measurable value and which are only moving ahead on enthusiasm.
