Artificial Intelligence is creating waves of disruption across many industries, be it manufacturing or human resources (HR). One of the major industries which AI has penetrated today is supply chain and logistics. Experts say that by 2020, AI could be completely transforming warehouse operations, with improvements in efficiency, profits and targets. The warehouse powered by AI would become more responsive and dynamic.

How can AI help in Warehouse Optimization?

One way through which AI can optimize the warehouse is by increasing the productivity of their workforce, especially warehouses that deals with regular pick and pack operations. Another way would be to use AI to enhance the communication between different operational departments, which would in turn ensure a smooth running of day-to-day tasks. For example, online supermarket Ocado uses robots that can converse back-and-forth at a very short span of time, thus eliminating various human inaccuracies.

This would help in achieving overall targets and ensuring that the tasks are completed, while using time efficiently.

Multiple operations in the supply chain industry are expected to become fully automated by 2030. Predictable physical activities can easily be replaced by smart machines, saving time and money usually spent on wages, human mistakes, lunch breaks among various others. Robots, such as Amazon’s Kiva robots, can pick up goods and distribute them to different stations within a warehouse in mere minutes, and only needs five minutes to charge every hour.

Although 30% of jobs have the potential to become automated, employees are not expected to be fully replaced by robots. Automation will be integrated into current operations to be used as an aid; something to work alongside workers and help with routine tasks.

How is AI useful in data processing and mining?

Another area that AI can efficiently take over is the task of processing data and collecting data obtained from different warehouse operations. Complex operations can be captured and used to recognize patterns, regularities, and interdependencies from unstructured data. A smart warehouse will then be able to adapt, dynamically and independently, to new situations within the entire logistics system. Data thus collected can be analyzed to arrive at better and improved business strategies that use AI to their advantage.

To conclude

Machine learning algorithms and AI can be implemented in warehouse operations and supply chain so that they are able to anticipate situations, and solve problems efficiently. Thus, decisions are made in a short time.

AI can use the real-time insights gathered at every touch point in the warehouse’s workflow, to improve inventory accuracy and increase turns. Warehouse activities can therefore be actively monitored, while anticipating the workflow and proactively recommending optimizations.

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