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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Industry 4.0, powered by artificial intelligence and machine learning goes beyond anything dreamed up during previous technological revolutions. The future would bring forth a world where machines not only do the physical labor, but are also in charge for the ideas- planning, strategizing and making decisions. Artificial intelligence has brought forward such advancements in industries that the furor surrounding it still continues in 2019.

So what does 2019 have in store?

The year 2019 will probably witness increased emphasis on measures designed to increase the transparency of AI. Considering a case, IBM recently unveiled technology developed to improve the traceability of decisions into its AI OpenScale technology. Bernard Marr writes in Forbes that “This concept gives real-time insights into not only what decisions are being made, but how they are being made, drawing connections between data that is used, decision weighting and potential for bias in information.”

Research and business will also benefit from openness which exposes bias in data or algorithms. This would also solve the ‘black box problem’, where the workings powered by AI seem unfathomable without a thorough understanding of what it’s actually doing. Hence it will be comfortably accepted in the wider society.

The next step would be a deeper infiltration of AI and automation into every business. In 2018, companies began to get a firmer grip on the realities of what AI can and can’t do. Retailers are proficient at grabbing data through receipts and loyalty programs and feeding it into AI engines to work out how to get better at selling us things. Manufacturers use predictive technology to know when a repair is required or when a machine will wear out. In 2019, this technology would be much more trustworthy, as it would be revamped with the learnings it has picked up in its initial deployments.

Business Line says that by 2019, at least 25 percent of employees at all large corporations will communicate with a bot for information. More than half of organizations have invested in VCAs for customer service, as they realize the advantages of automated self-service and the ability to escalate to a human in complex situations

An AI assistant can also semantically understand job descriptions that is fed in and finds relevant matches for the requirement from available job portals and databases. A hiring assistant can also reach out to identified candidates and engage in a chat to pre-qualify them as per company requirements.

AI is out there, ready to be consumed by startups and corporations alike, to solve almost any problem from commuting to visualizing, replacing many mundane human tasks with efficient machines and leaving us humans to make more complex decisions. O’Reilly data says that 51 percent of surveyed organizations already use data science teams to develop AI solutions for internal purposes. Adoption of AI tools would be one the most important AI trends in 2019. Let us wait and watch how it rolls out this year.

This content is not for distribution. Any use of the content without intimation to its owner will be considered as violation.