Why AI-optimized workflows aren't always best for businesses

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Workflow and process inefficiencies can cost up to 40% of a company's annual revenue. In many cases, companies seek to solve this problem by implementing artificial intelligence (AI) scheduling algorithms. This is considered a beneficial tool for business models that depend on speed and efficiency, such as delivery services and the logistics industry.

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

AI lacks the human capability to go beyond simply optimizing business efficiency. This means it has no capability for "human" variables like worker preferences. The limitations of AI scheduling can often lead to unbalanced shifts or disgruntled workers, culminating in situations where the AI ​​"help" given to HR actually hinders smooth workflows. /p> When Optimization Goes Wrong: AI Can't See Humans Behind Data Points

Automatic AI scheduling has grown in popularity in recent years. Between 2022 and 2027, the global AI planning systems market is expected to grow at a CAGR of 13.5%, and 77% of companies are already using AI or looking to add AI tools to optimize workflows and improve business processes.

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However, it is important to note that the AI ​​cannot yet establish a schedule without human supervision. HR professionals still need to review and adjust the automatically generated schedules, because there is still a huge glaring flaw in the AI ​​algorithms: a lack of "human parameters".

AI is great at sorting through data and finding ways to optimize the efficiency of business processes. Workflow optimization via algorithms that use historical data is ideal for projecting things like order volume and the number of workers required, based on information like marketing promotions, weather conditions, time of day, hourly order estimates and average customer wait times.

The problem stems from the AI's inability to account for "human parameters", which it sees as a drop in efficiency rather than best business practice.

For example, if a company has practicing Muslim employees, they need small breaks in their workdays to observe prayer times. If a company employs new mothers, they may also need time to pump. These are things that are currently beyond the capabilities of the AI ​​to properly account for, as it cannot use human empathy and reasoning to see that these "inefficient schedules" are much more efficient from the point of view of the long-term employee happiness.

Efficiency is not always the best policy; is there a solution?

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