Organizations Must Redesign Operating Models to Keep Pace with AI Adoption
As organizations continue to adopt AI across their workforces, a new challenge has emerged. Many companies are struggling to redesign their operating models and leadership structures to keep pace with the rapid changes brought about by artificial intelligence.
A recent IBM study found that nearly two-thirds of executives believe AI is reshaping roles and workflows, but few organizations have taken the necessary steps to adapt. The report highlighted a growing disconnect between leaders' perceptions of AI progress and employees' actual experiences.
According to the study, while 78% of executives claim employees are involved in designing AI-enabled workflows, only half of employees agree. Furthermore, leaders report role transformation at twice the rate that employees experience it, indicating steady progress embedding AI into operations, but with a significant gap between leadership and employee perspectives.
The shift towards AI-enabled work is causing human roles to center on direction, judgment, and decision-making, rather than routine tasks. This requires teams to assign work to AI agents, integrate them into daily workflows, and oversee collaboration between humans and machines, placing new expectations on managers who must coach judgment and adapt to changing ways of working.
Organizations that are pulling ahead in this area are addressing operating model gaps directly, redefining decision-making processes and incentives alongside AI adoption. These companies are achieving up to 73% higher revenue growth and an 11% operating margin advantage, as well as stronger trust between leadership and employees.