Nearly four in five Asia-Pacific (APAC) respondents believe their organisations are directing too much artificial intelligence investment towards incremental improvements rather than fundamental business change, according to new research from Avanade. The company’s Build Beyond Limits: AI Reality Report found that only 17% of regional respondents had fundamentally reshaped how their entire teams operate around AI, despite widespread confidence in adoption. The findings suggest that reported technological maturity has yet to translate into substantial operational change.
The results draw from 1,400 APAC respondents within a global survey of 3,600 business decision-makers across 11 markets. Conducted among organisations with more than US$500 million in global annual revenue, the research examined AI progress, investment priorities and approaches to measuring business value.
High confidence in AI adoption contrasts with limited operational change
Across APAC, 76% of respondents described their teams as Established, Advanced or AI-first in their AI journey, while 73% expressed high or complete confidence that their teams were using AI effectively to deliver their strategies and goals. However, these confidence levels contrast with the limited operational changes reported by respondents, illustrating that organisations can report strong progress in adopting AI without making comparable changes to established working practices.
Avanade’s research distinguishes between investments that improve current operations and those intended to change how businesses create value. Both approaches can deliver benefits, but they require objectives and measures of success that reflect what each investment is expected to achieve.
Bhavya Kapoor, President, Avanade Asia Pacific, said: “Incremental AI improvements can create real value, but improving existing operations and fundamentally transforming a business are different ambitions. APAC leaders need to be clear about where each applies, with investment decisions and measures of success to match. Where transformation is the goal, that means redesigning workflows, responsibilities and decision-making, with clear ownership of outcomes. The real test is whether the intended change happens and its value can be demonstrated.”
Financial accountability remains a weakness in AI investment
The research also identified gaps in how APAC organisations assess the financial results of their AI initiatives. Some 68% of respondents agreed that their organisations had yet to formally calculate the financial return on AI investment and have those results reviewed by finance teams or senior leadership. Separately, only 43% reported using business-value and return on investment (ROI) targets to determine whether their organisations were making meaningful progress with AI.
These findings suggest that AI adoption is not consistently linked to formal assessments of business value. Organisations may regard the deployment of tools, pilot programmes and productivity improvements as progress without establishing whether those activities are delivering their intended financial outcomes. Formal financial reviews can help organisations assess the returns generated by AI initiatives, while defined business-value targets provide a basis for measuring progress against specific objectives. The measures used also need to reflect whether an investment is intended to improve existing operations or achieve wider organisational change.
Avanade Chief AI Officer Ben Beath raised similar concerns about organisations measuring AI progress through activity rather than impact. His assessment focused on whether businesses were changing how decisions are made, work is performed and value is created, alongside investments in AI tools and productivity improvements.
Perceived AI maturity also exceeds reported changes globally
The difference between reported AI maturity and operational change extends beyond APAC. Across the global sample, 77% of respondents classified their organisations as Established, Advanced or AI-first, while 72% expressed high confidence that their teams were using AI effectively. Yet only 18% reported fundamentally reshaping how their teams operate around AI, closely matching the 17% recorded among APAC respondents.
The research also examined whether organisations’ public descriptions of their AI capabilities matched their actual progress. In APAC, 76% agreed that their own organisations publicly portrayed themselves as more AI-mature than they actually were. Globally, 75% believed organisations presented themselves publicly as more mature in AI adoption than their actual capabilities warranted. These perceptions suggest that reported AI maturity may provide an incomplete picture of how extensively organisations have changed their operations.
Avanade CEO Chris Howarth pointed to the company’s work with Thomson Reuters on Reuters Imagen as an example of how organisations could rethink workflows and create value through AI. His comments focused on redesigning how work is performed, an ambition that the survey suggests relatively few organisations have achieved across their teams.
