A survey cited in a podcast reveals that only a minority of companies manage to move AI into production with measurable results and formal controls.
Corporate adoption of artificial intelligence continues to advance, but value capture remains limited, according to a Genpact survey cited on the Eye on A.I. podcast. The company surveyed 500 senior executives and found that only 12% of the evaluated companies can be classified as AI leadersâmeaning they already use the technology in production environments, with measurable business results and governance mechanisms in place to track those gains.
According to Sanjeev Vohra, Chief Technology and Innovation Officer at Genpact, the remaining 88% of companies remain stuck between testing phases, partial adoption, or stalled initiatives. In his assessment shared on the program, the main obstacle is neither the technology itself nor necessarily the senior leadership, but rather an overburdened middle operational layer tasked with executing changes without the time or structure to manage them.
Vohra described this group as the "frozen middle": middle managers who understand the company's critical processes but are pressured by daily operations. According to the executive, this layer is central to transforming pilots into actual process changes, making it difficult to bypass in corporate AI programs.
The episode also highlights a difference between companies that use assistants and copilots as an initial step and those that manage to advance to more integrated uses. According to Vohra, many organizations treat copilots as an end goal, whereas AI leaders tend to connect them to workflows, metrics, and governance responsibilities.
Governance emerges as another point of concern. According to Vohra, most companies still lack robust programs to oversee AI, even with the advancement of agents and more autonomous systems. In his view, companies that wait for a complete roadmap before starting projects run the risk of falling behind; the recommendation presented in the podcast is to prioritize incremental progress, with controls and measurement from the start.
Only 12% of companies are classified as AI leaders, meaning they use AI in production environments with measurable business results and governance mechanisms in place.
The main bottleneck is the 'frozen middle'âan overburdened middle management layer tasked with executing changes without the time or structure to manage themâas well as a lack of robust governance.
While many organizations treat copilots as an end goal, AI leaders connect them to workflows, metrics, and governance responsibilities to achieve integrated business results.