Saturday, February 4, 2023

Why AI-optimized Processes Don’t Suit Every Business

By Swapnil Mishra - January 24, 2023 4 Mins Read

While AI has undoubtedly aided in some unpredictable tasks involved in scheduling employees across departments, the model is still far from perfect.

A huge part of a company’s annual revenue can be lost due to inefficient workflow and processes. Companies frequently use Artificial Intelligence (AI) scheduling algorithms to solve this problem. It is viewed as a valuable tool for industries like delivery services and logistics that rely on speed and effectiveness.


AI cannot see beyond optimizing for business efficiency as humans can. This means that “human” factors, such as employee preferences, are not supported.

The drawbacks of AI scheduling can frequently result in unbalanced shifts or unhappy workers, which can ultimately lead to circumstances in which the AI “help” provided to HR impedes efficient workflows.

Also Read: How AI and Blockchain Integration Benefits Businesses

Drawbacks of AI

When optimization goes wrong, AI can’t see the people generating the data. AI for auto-scheduling has become very popular recently. It’s crucial to remember that AI cannot currently create schedules without human supervision. AI is very good at sifting through data and figuring out how to make business processes as efficient as possible. Workflow optimization algorithms that use historical data are ideal for estimating order volume and the necessary number of workers based on marketing promotions, weather patterns, time of day, hourly order estimates, and typical customer wait times.

The issue arises from AI’s inability to consider “human parameters,” which it interprets as efficiency drops rather than improved business procedures. AI is currently unable to use empathy and human reasoning to recognize that these supposedly “inefficient schedules” are much more efficient from the perspective of long-term employee happiness. It is currently impossible for AI to account for some things correctly. It occasionally worsens the issues rather than solving them.

Efficiency isn’t always wise

Auto-scheduling software can only gather information from a few sources, such as timesheets and workflow histories, to distribute work hours in a way it deems ideal. AI scheduling tools require assistance in comprehending why it is undesirable to have one employee work the closing shift one day, then have them back for the opening shift the following day. They can’t yet consider differences in availability or workers’ personal preferences.

Adding more parameters to the algorithms is one solution that could be used, but it has its own issues. First, the algorithm’s likelihood of working well decreases each time a new parameter is added. Second, the performance of algorithms depends on the data they are given. The scheduling may reduce workflow efficiency and add to the workload of managers or HR staff if AI tools are provided with inaccurate, incomplete, or imprecise data. The algorithm won’t function more effectively if more filters or restrictions are added.

Unfortunately, humans will probably always need to be involved in employee scheduling until people figure out how to give AI empathetic reasoning abilities. However, businesses can work to foster a more beneficial, synergistic relationship between the humans who use AI scheduling tools and those tools themselves.

For instance, delivery companies can feed historical data into AI tools to improve the accuracy of their initial schedule outputs. The workload for scheduling and HR managers is somewhat lessened as a result. The human scheduler can work from an optimized base schedule and spend less time trying to fit workers into the required time slots.

Also Read: Challenges Of AI In Supply Chain

Although AI may be highly effective, it requires human assistance to satisfy employees. The term “general intelligence,” which refers to the intelligence found in humans and animals, is still actively developed by humanity. It combines emotional intelligence and common sense, two things that AI has not yet been able to replicate. AI almost outperforms humans when it comes to automating repetitive tasks or analyzing vast amounts of data to identify inefficiencies and better work processes. To balance optimized workflows with employee satisfaction and long-term business growth, humans will still need the final say once nuance, emotion, or general intelligence are added, as is the case with task scheduling.

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Swapnil Mishra

Swapnil Mishra is a Business News Reporter with OnDot Media. She is a journalism graduate with 5+ years of experience in journalism and mass communication. Previously Swapnil has worked with media outlets like NewsX, MSN, and News24.

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