When optimization goes wrong: AI can’t see humans behind the data points.

Workflow and process inefficiencies can cost up to 40% of a company’s annual revenue. In many instances, companies seek to resolve this issue by implementing Artificial Intelligence (AI) scheduling algorithms. This is seen as a beneficial tool for business models that depend on speed and efficiency, such as delivery services and the logistics sector.

While AI has certainly helped with some of the time-consuming and often unpredictable tasks associated with scheduling workers across departments, the model is not yet perfect. Sometimes, it makes the problems worse and not better.

AI lacks the human ability to look beyond simply optimizing for business efficiency. That means it has no capacity for “human” variables like workers’ preferences. The limitations of AI scheduling can often lead to unbalanced shifts or unhappy workers, culminating in situations where the AI “help” given to HR actually gets in the way of smooth workflows.

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