As businesses in Asia increasingly explore the potential of agentic AI, a Gartner report highlights significant challenges ahead, predicting that over 40% of these projects will be cancelled by the end of 2027.
This forecast raises critical considerations for Chief Operating Officers (COOs) across the region, particularly as they navigate the complexities of integrating AI into their operations.
The report, presented by Gartner analysts, suggests that many agentic AI initiatives are currently little more than early-stage experiments or proof-of-concept projects.
Anushree Verma, a senior director analyst at Gartner, noted that hype often clouds the reality of these projects, leading organisations to underestimate the costs and complexities involved in deploying AI agents at scale.
A January 2025 poll conducted by Gartner revealed that only 19% of organisations had made significant investments in agentic AI, while 42% opted for more conservative investments.
The remaining respondents indicated either no investments or a "wait and see" approach. This cautious stance reflects a growing awareness of the risks associated with agentic AI, such as unclear business value and inadequate risk controls.
Moreover, the phenomenon of "agent washing," where vendors rebrand existing technologies as agentic AI without substantial capabilities, further complicates the landscape. Gartner estimates that only about 130 out of thousands of purported agentic AI vendors offer genuine solutions, raising concerns about the maturity and real-world applicability of many existing models.
Despite these challenges, there is potential for agentic AI to enhance resource efficiency and automate complex tasks in the long term.
Gartner forecasts that by 2028, at least 15% of daily work decisions will be made autonomously through agentic AI, a significant leap from the current baseline. Additionally, 33% of enterprise software applications are expected to incorporate agentic AI capabilities by the same year.
For COOs in Asia, the recommendation is clear: pursue agentic AI only when it delivers evident value or return on investment. The integration of AI agents into legacy systems can be technically challenging, often leading to workflow disruptions. Rethinking workflows and operational processes from the ground up may be necessary for successful implementation.
While agentic AI holds promise for the future, COOs must adopt a strategic and cautious approach to ensure that investments are aligned with clear business objectives and operational needs. This focus on enterprise productivity over mere task augmentation is crucial for realising the full potential of agentic AI in the coming years.
