Why AI-optimized workflows aren’t always best for business

Inefficiencies in processes and workflows can cost as much as 40 percent of an organization’s annual earnings. Many times, businesses attempt to solve this problem through the implementation of Artificial Intelligence (AI) scheduling algorithms. This is considered to be an effective tool for businesses with models that rely on efficiency and speed like logistical and delivery services. sector.

Although AI certainly has helped in certain of the tedious and often unpredictably difficult tasks associated with scheduling employees in different departments. However, the algorithm is not perfect yet. Sometimes, it can make the problems even worse, and not improve.

AI is not able to see beyond just optimizing business efficiency. This means that it lacks capability to take into account “human” variables like workers have preferences. However, the limitations associated with AI scheduling often result in unbalanced shifts and unhappy employees, resulting in situations in which it is the AI “help” given to HR can get hindering efficient workflows.

When optimization fails: AI can’t see humans in the data points

Auto-scheduling has gained a popular status during the past few years. Between 2022 and 2027, the global AI scheduling system market is expected to see a CAGR of 13.5%, and 77% of companies are making use of AI or are looking to implement AI tools to streamline workflows and enhance business processes.


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However, it’s crucial to remember that AI isn’t yet able to create schedules with human supervision. HR professionals are required to check and alter the schedules generated by AI because there’s a major and obvious flaw in AI algorithms: a lack in “human parameters.”

AI is a pro in analyzing data and discovering ways to increase efficiency of business processes. Optimizing workflows with algorithms that make use of historical data can be used to forecast factors like order volumes and the necessary amount of employees in a given time, based on data such as promotions for marketing and weather patterns, as well as the time of day, hourly estimations of orders, and average wait times for customers.

The issue is due to AI’s inability of accounting for “human parameters,” which AI interprets as a drop in efficiency instead of better business procedures.

For instance, if a business has Muslim employees, they will require short breaks during their working hours to observe the times of prayer. If a company employs newly-wed mothers, they could also require built-in time in order to supply breastmilk. These are all things that AI isn’t able to ability to adequately be able to handle, since AI cannot draw on empathy or human logic to determine how these “inefficient schedules” are much more effective from an satisfaction of employees.

The efficiency of a business isn’t the ideal option; can you find an alternative?

Auto-scheduling software are able to pull data from a few sources, including timesheets and workflow histories to ensure that work hours are evenly distributed according to what they believe the best way to do so. AI scheduling software needs guidance on why it’s wrong to have the same person be working on the final shift one day only to return to work for the opening shift the following day. They aren’t able to be able to account for the individual preferences of workers or different availability.

One solution to this issue is to continue making changes to algorithm, however, this poses the same problems. In the first place, each when you introduce an additional parameter, it reduces the probability that the algorithm will work efficiently. Additionally, algorithms can only function in accordance with the information they are provided with. When AI tools are given inaccurate, incomplete or incorrect data, they could reduce efficiency of workflows and create additional work for managers or HR personnel. The addition of more filters or restrictions to the algorithm will not make the system work more effectively.

So , what’s the solution? I think that until we find ways to combine AI with empathy and reasoning abilities There will always have a requirement for human beings to assist in the process of scheduling workers.

Yet, they are able to create an energizing, positive interaction between AI scheduling devices and the human beings who make use of them.

For example, delivery companies can incorporate their historical data to AI tools to boost the efficiency of their initial outputs for schedules. This eases the workload for scheduling and HR managers. The human scheduler has an optimized schedule from which to work which means they reduce the time spent fitting employees into the time slots that are needed.

AI could be extremely effective however, it needs human assistance to keep employees content

Humanity is working to creating AI which exhibits ” general intelligence,” which is a term used to describe the level of intelligence observed in both animals and humans. It is a combination of problem-solving, emotions as well as common-sense, which are two aspects that are yet to be replicated by AI.

If you have to automatize repetitive tasks or examine vast amounts of data in order to identify inefficiencies and improve working methods, AI outshines humans nearly every time. But once you incorporate nuance, emotion or general intelligence as when it comes to the scheduling of tasks, humans still require the final say in balancing efficient workflows and satisfaction of employees and long-term expansion.

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