“Alexa, please automate my warehouse.”

How convenient would it be if it were that simple to automate the warehouse? However, to achieve a similar future, the warehouse needs a brain to process all the information it receives and automatically execute actions to address various scenarios. And that brain is called Artificial Intelligence, or AI.

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    What is Artificial Intelligence?

    Artificial Intelligence (AI) is a branch of computer science that aims to make machines that can mimic the functions and reactions of a human as closely as possible. It can perform human-like tasks such as decision-making, speech recognition, visual perception, and language translation.

    Andrew Ng, founder and lead of the Google Brain project and several AI startups, gives a good explanation of the general idea of present AI capability:

    “If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.”

     

    What Machine Learning Can Do

    A table of what machine learning can do.

    By understanding what AI can and cannot do, you can incorporate it into your strategies. Then, hiring the right talent to customize your business environment and data to automate your operations and have important insights at your fingertips is a matter.

    The Value of Artificial Intelligence in the Warehouse

    Artificial Intelligence generates value in the warehouse through various sub-technologies: machine learning, natural language processing, robotics, and computer vision. Here’s how each functions.

    Machine learning uses algorithms to “learn from experience” and make practical decisions for the warehouse. Using data gathered from sensors, it notices patterns and suggests actions such as faster replenishment of nearly out-of-stock items, shorter walking routes, and better inventory positioning.

    Some AI features enable wearable warehouse technology. Natural language processing makes voice-picking possible so workers can operate hands-free and more safely. Smart glasses are equipped with cameras that use computer vision to recognize barcodes automatically. Also, cameras placed around the warehouse use computer vision to enable end-to-end product tracking.

    Lastly, robotics lends AI a physical presence, spatial awareness, and movement in the real world. AI robots’ capabilities can vary from loading or unloading a pallet to moving cargo around the warehouse and/or performing picking operations.

    “Artificial General Intelligence” refers to AI that can perform any intellectual task a human can do, but it’s still a long way off. The sub-tasks of AI are important steps toward achieving “full AI.” Once achieved, “full AI” has the potential to operate a warehouse almost autonomously.

    Warehouse Efficiency Ebook

    Where is AI in the Warehouse Industry Now?

    In the MHI Annual Industry Report 2022, only 14% of respondents currently use AI technology. This percentage will grow by 73% in the next 5 years. Despite the low number, more than half of the respondents believe that AI can disrupt the industry and create a competitive advantage for their business.

    Warehouse Technology | Artificial Intelligence - Adoption Rates

    S-Curve of Innovation

    Artificial Intelligence is currently between the Ferment and Takeoff stages for the S-Curve. This phase usually indicates that the evolution of technology is slow. However, the current position of AI suggests that the technology is about to cross over to the Takeoff phase, which means that its evolution will likely increase significantly within the next few years.

    S-Curve of Innovation

    Technology Adoption Life Cycle

    Early adopters are currently implementing AI for the technology adoption life cycle. Being adopted by this group means that thought leaders have determined AI’s capabilities are worth investing in despite the financial risks associated.

    Technology Adoption Life Cycle

    Hype Cycle

    For the Hype Cycle, Artificial Intelligence is placed on the Innovation Trigger of Gartner’s Hype Cycle for Supply Chain Execution Strategy 2019. This position means that the technology is still being conceptualized and prototyped. Often, there are no usable products or services of the technology available for individuals or businesses to implement, and commercial viability for it is still unproven.

    Hype Cycle

    Based on the three technology frameworks, Artificial Intelligence still needs a lot of research and development to prove its effectiveness in warehouses. Investing in AI could create a competitive advantage, but staying updated on its evolution is also important.

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