67% of Digital Investment Concentrated in AI, Yet Over Half of Organizations Fail to Track ROI – finance.biggo.com

As corporate digital investment rapidly concentrates in the field of artificial intelligence (AI), a stark reality has emerged: a majority of organizations are unable to measure the return on their spending. According to a survey published by Gartner on August 5, 2026, 67% of all digital investment in the supply chain sector was directed toward AI, while 55% of chief supply chain officers lack a clear grasp of the return on investment (ROI) from these AI expenditures. The findings highlight a significant gap between the massive flow of capital into AI and the inability of management on the ground to demonstrate its contribution to profitability.
The research was conducted in two parts. From November 2025 to February 2026, Gartner surveyed 394 supply chain professionals at organizations with annual revenues of $250 million or more to assess the allocation of digital investment. Subsequently, from January to April 2026, 135 senior supply chain executives were surveyed regarding AI use cases and their understanding of ROI. Both studies targeted large-scale organizations, painting a picture of the realities of AI investment and profitability management at global enterprises.
Lorraine Gavin, Senior Principal Analyst in Gartner’s Supply Chain practice, acknowledged that organizations have improved their ability to execute individual transformation initiatives. However, she pointed out that the current challenge lies in deciding where to deploy limited change management resources to support key business outcomes. “The proliferation of AI has raised the stakes of that decision,” Gavin stated, underscoring how the pace of technology adoption has outstripped the development of management governance structures.
The survey results also indicate that while the rapid evolution of AI has led to a surge in use cases, organizations have struggled to keep pace with developing their change management approaches. To frame this issue, Gartner draws a clear distinction between “change methodology” and “change strategy.” Change methodology defines the execution steps and activities for individual initiatives, whereas change strategy is a higher-level concept that determines how to allocate limited resources across multiple AI initiatives to achieve supply chain and enterprise-wide goals.
The firm urged chief supply chain officers to develop strategies that link business outcomes to transformation investments, thereby preventing the fragmentation of AI adoption. It advocates for “right-sized” change management, moving away from fixed, uniform approaches and instead allocating transformation investment based on the desired outcomes. Gartner predicts that organizations adopting this right-sized change management approach will achieve double the ROI on their AI initiatives by 2030 compared to those relying on traditional methodologies.
As a path to improvement, Gartner proposed four key pillars.
First, institutionalize AI change management as an independent strategic discipline, building a foundation to support the AI technology strategy. Second, treat change management capability as a scarce resource and concentrate it on AI initiatives that offer the highest contribution to supply chain outcomes and ROI. Third, adopt a “composable” execution model, tailoring change methods to the scale, speed, and organizational context of each initiative. Fourth, cultivate a leadership layer equipped with business acumen, talent development, and risk management skills capable of guiding AI-driven transformation.
Underpinning these recommendations is the principle of concentrating transformation resources on outcomes directly linked to corporate and supply chain priorities, rather than distributing them evenly across individual activities. Since the scale and speed of support required vary for each AI initiative, Gartner argues that a context-specific execution model is necessary, rather than a single standardized approach. The firm’s view is that treating outcome prioritization, resource allocation, execution methods, and leadership as a single, unified strategy is a prerequisite for clarifying the profitability of AI investments.
The survey findings suggest that corporate AI investment is shifting from a phase of “adoption for its own sake” to one of “outcome verification.” With two-thirds of digital investment flowing into AI, the fact that a majority of senior executives cannot track ROI underscores the urgent need for more sophisticated investment decision-making and stronger management governance. Gartner’s concept of “right-sized change management” offers a practical framework for enhancing the profitability of AI investments and has the potential to influence leadership across a broad range of industries, well beyond the supply chain sector.
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