Projected investment in artificial intelligence (AI) is expected to hit $2.52 trillion globally by 2026, marking a 44 percent year-on-year increase, as reported by Gartner. Despite this financial commitment, around two-thirds of organizations are struggling to implement AI solutions at scale across their operations.
While 88 percent of firms indicate AI usage in at least one area, the challenge remains in fostering scalable value from these initiatives. Key aspects for successful AI scaling, such as decentralizing workflows and integrating AI into everyday business activities, have been recognized by leadership.
A survey conducted by Alteryx revealed that less than 25 percent of AI pilots progress to full production. Furthermore, it is anticipated that by 2028, 33 percent of AI workflows will be decentralized, shifting responsibilities to individual business units. Despite advancements in data quality and AI integration, many organizations face difficulties in demonstrating tangible impacts.
About 23 percent of organizations that have scaled their AI efforts effectively exhibit high data maturity and strong governance practices. However, a significant gap in centralized data governance was noted, especially in Singapore, where 60 percent of respondents reported missing capabilities, exceeding the global average of 53 percent. Ensuring effective governance at the point of AI application remains a critical challenge for many organizations.