Despite artificial intelligence’s (AI) promise for enhancing efficiency, many organizations struggle to turn investments in traditional and generative AI into material improvements in worker productivity, according to a survey by Gartner, Inc.
Gartner’s survey of 724 respondents from a range of business functions, taken June through August 2024, revealed that among teams who primarily used traditional AI, 37% reported high productivity gains, while GenAI-using teams fared marginally worse at 34%. (see Figure 1).
Randeep Rathindran, Distinguished Vice President, Research, in the Gartner Finance practice shared the latest findings on the impact AI is having on CFOs and finance leaders during the Gartner CFO & Finance Executive Conference 2025, taking place here 24-25 March.
Randeep Rathindran, Distinguished VP at Gartner, speaking at the Gartner CFO & Finance Executive Conference in Sydney today
“Despite the excitement surrounding AI, its impact on productivity has been inconsistent, leading to what some describe as the AI productivity paradox,” said Rathindran. “While AI has shown potential to boost productivity at the segment level, such as in call centers, broader organizational benefits have been harder to achieve. Therefore, CFOs should recalibrate expectations on how AI will truly impact worker productivity and headcount.”
Figure 1. Comparable Productivity Gains Across All Technologies
![[Image Alt Text for SEO]](https://emt.gartnerweb.com/ngw/globalassets/en/newsroom/images/graphs/producthc.png)
Source: Gartner (March 2025)
Several factors contribute to the limited productivity gains from AI. For example, the inflated expectations of AI’s capabilities lead to disillusionment. While AI can automate certain tasks and provide valuable insights, it does not automatically translate into substantial productivity improvements across the board. Additionally, measuring productivity gains can be challenging, and implementation lags often delay the realization of benefits.
Further, the distribution of productivity gains across functions is uneven. Marketing teams, for instance, report the highest productivity gains from AI implementation, while legal and HR functions fall behind. This disparity highlights the importance of context and the specific applications of AI within different organizational functions.
“The most successful teams approach AI with an openness to learn and explore new use cases, rather than fearing job displacement,” said Rathindran. “By redesigning structures and workflows to eliminate process bottlenecks and shifting time to value-added tasks, these teams maximize AI’s potential and achieve meaningful productivity gains.”
Rather than viewing AI as a silver bullet for driving efficiency, CFOs and business leaders should reset their initial expectations about AI’s impact on productivity and focus on creating the internal conditions that enable AI to deliver its full potential.
This involves challenging assumptions about cost or headcount savings in AI-related business cases and sensitizing C-suite and finance leaders to organizational behaviors that heighten AI’s impact. By adopting a structured, explorative, and collaborative approach, organizations can position themselves to capture the productivity benefits that AI can deliver.
“As AI and GenAI continue to evolve, their transformative promise remains undeniable. However, organizations must ground their expectations in current realities and focus on the factors that truly drive productivity gains,” said Rathindran. “By understanding the nuances of AI’s impact and fostering a culture of acceptance and learning, organizations can harness AI’s potential to achieve sustainable success.”
Gartner clients can access the study at AI’s Impact on Productivity and Headcount and nonclients can access The CFO Report.
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Tags: Small Business, Technology
