Singapore data analysts are seeing their strategic influence grow as organisations accelerate artificial intelligence (AI) adoption, according to new research from Alteryx, though persistent data quality and governance gaps continue to hold back AI ambitions.
The AI-ready data and analytics company’s 2026 State of the Data Analyst: The Rise of Business Logic report found that 75 per cent of Singapore data analysts say their strategic impact has increased over the past year, as the role shifts from technical execution towards strategic oversight of AI-generated outcomes.
The findings suggest that rather than diminishing the role of data analysts, AI is transforming it into one centred on ensuring outputs are trusted and aligned with business objectives. Yet weak data foundations continue to widen the gap between the pace of AI adoption and organisations’ ability to put it to work effectively.
Data quality gaps undermine AI in Singapore
The research, conducted among 175 Singapore data analysts and IT leaders as part of a broader global study of 1,400 respondents, found that 46 per cent of AI and analytics projects in Singapore that fail to meet their objectives are attributed primarily to data-related issues, rather than model or tooling problems.
Singapore analysts spend an average of five hours a week preparing and cleaning data, and a further three hours correcting and validating AI-generated outputs, the study found.
Caution around automation runs deep. Some 61 per cent of Singapore respondents said they prefer a human-in-the-loop approach — the highest of any region in the study and well above the global average of 49 per cent. Just 1 per cent are comfortable with AI operating fully autonomously, below the global average of 3 per cent.
The case for business-level ownership
“Organisations in Singapore are moving fast to adopt AI, but our research shows that speed alone doesn’t guarantee accurate results. Many are still grappling with underlying challenges including poor data quality, weak governance, and uncertainty over when AI-generated outputs can be trusted. What separates organisations that succeed from those that stall is whether the people closest to the business are the ones defining and managing the business logic behind AI.”
Philip Madgwick, Regional Vice President, Asia, Alteryx
The research argues that AI and agentic systems prove most effective when the underlying business logic — the rules and context that define how a business operates — is owned and managed at the business level, rather than by centralised teams removed from day-to-day operations. Some 66 per cent of Singapore respondents agreed that such systems are most productive when managed at the business level.
