With the help of digital technology, complex managerial tasks, such as the supervision of employees and assessment of job candidates, can now be taken over by machines. While still in its early stages, algorithmic management — the delegation of managerial functions to algorithms in an organization — is becoming a key part of AI-driven digital transformation in companies.

Algorithmic management promises to make work processes more effective and efficient. For example, algorithms can speed up hiring by filtering through large quantities of applicants at relatively low costs.1 Algorithmic management systems can also allow companies to understand or monitor employee productivity and performance.2 However, ethical challenges and potential negative downsides for employees must be considered when implementing algorithmic management. In the case of hiring, AI-enabled tools have faced heavy criticism due to harmful biases that can disfavor various groups of people, resulting in efforts to create guidelines and regulations for ethical AI design.

In this article, we build on our years of research on algorithmic management and focus on how it transforms management practices by automating repetitive tasks and enhancing the role of managers as coordinators and decision makers. However, the introduction of algorithms into management functions has the potential to alter power dynamics within organizations, and ethical challenges must be addressed. Here we offer recommendations for how managers can approach implementation using new skill sets.

Profit From Scale and Efficiency While Improving Workforce Well-Being

Algorithms can enhance the scale and efficiency of management operations. In the gig economy, algorithmic systems coordinate and organize work at an unprecedented scale — think about the number of matching riders and drivers using Uber or Lyft at any one time across the globe. Likewise, standards organizations have already taken advantage of the increased accuracy of algorithmic processing to manage both tasks and workers. UPS equips trucks with sensors that monitor drivers’ every move to increase efficiency. Similarly, Amazon heavily relies on algorithms to track workers’ productivity and even generate the paperwork for terminating employment if they fail to meet targets.

However, our research suggests that focusing solely on efficiency can lower employee satisfaction and performance over the long term by treating workers like mere programmable “cogs in a machine.�