AI Adoption Linked to Increase in Average Manager Span of Control in US Workplaces
Data from the Bureau of Labor Statistics indicate that the average number of direct reports per manager in the US has nearly doubled since 2013, coinciding with AI integration in workplaces. Companies are reducing middle-management layers to cut costs and streamline operations, with AI tools assisting in administrative tasks.
Substrate placeholder — needs review · Wikimedia Commons (CC BY-SA 3.0)The integration of artificial intelligence (AI) in workplaces has coincided with changes in organizational structures, particularly an increase in the average number of direct reports per manager. According to data from the Bureau of Labor Statistics, the average American manager now oversees 12 direct reports, nearly double the figure from 2013 when Gallup began tracking it.
This shift has occurred over the past three years amid efforts to reduce middle-management positions.
Fortune reported that AI tools are enabling this change by handling tasks such as scheduling, summarizing performance reviews, monitoring project timelines, and identifying team issues. For instance, Meta has implemented a 50-to-1 employee-to-manager ratio in its new applied AI engineering division, which is roughly double previous norms for organizational structures.
A 2024 Gartner analysis indicated that one in five businesses plan to use AI to streamline organizational layers.
the number of managers can lower headcount costs, create flatter hierarchies, and potentially speed up decision-making by reducing layers of communication.
AI tools automate administrative tasks like flagging performance issues, synthesizing team data, drafting communications, and coordinating schedules, which may help managers handle larger teams. A Morgan Stanley analysis published this week examined five prior US innovation waves, from the first Industrial Revolution through the internet era, and found that transformative technologies increased output per worker when combined with organizational redesign.
0% per year by 2000.
S. economist Michael Gapen’s team suggested AI could follow a similar pattern, though productivity gains historically emerge years or decades after initial disruptions. This implies that current changes may lead to long-term efficiency improvements, but short-term adjustments are ongoing.
A Gartner survey found that 75% of HR leaders believe managers are overwhelmed by expanding responsibilities, and 69% say managers lack skills to lead change effectively before full AI integration.
Gallup data indicate global employee engagement has fallen to 21%, near a 15-year low, with managers reporting some of the sharpest declines. These trends highlight potential strains on mentorship, morale, and career progression as spans of control widen.
The reduction in middle-management ranks affects employees by potentially limiting guidance and development opportunities, while managers face increased workloads.
Businesses adopting these structures may need to invest in training and AI support to mitigate overload. The future trajectory depends on how companies balance efficiency gains with human resource needs over the next decade.
Key Facts
Story Timeline
4 events- Past three years
Companies reduced middle-management ranks amid AI adoption and cost-cutting efforts.
1 sourceFortune - 2013
Gallup began tracking average manager direct reports, initially lower than current levels.
1 sourceFortune - This week
Morgan Stanley published analysis on historical innovation waves and productivity patterns.
1 sourceFortune - 2024
Gartner analysis predicted one in five businesses would use AI to streamline layers.
1 sourceFortune
Potential Impact
- 01
Companies may achieve lower costs through reduced management layers.
- 02
Productivity gains from AI could emerge in coming years following historical patterns.
- 03
Managers could face increased workloads leading to higher burnout rates.
- 04
Employee engagement may decline further due to limited mentorship opportunities.
- 05
Businesses might invest more in AI training to support larger team management.
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