How Machine Learning and Artificial Intelligence are Impacting the Future of Supply Chain

With the growing amounts of data in supply chains, the need for more sophisticated data processing systems is becoming more critical every day. Furthermore, many supply chain industries do not have integrated IT systems, making the situation even more complicated, costly, and inefficient. That’s why many organizations are beginning to adopt Artificial Intelligence (AI) and Machine Learning (ML) to help manage, store, and analyze complex data faster, cheaper, and at a much larger scale.

A lot of business leaders have been talking about AI and machine learning lately, but what are they, exactly? And are they just buzzwords, or are these trends here to stay?

What is Artificial Intelligence?

According to Supply Chain Digital, artificial intelligence can be defined as the use of computers to simulate human intelligence, specifically including learning – the acquisition and classification of information, and reasoning – finding insights into the data. At the core of artificial intelligence is the ability to recognize patterns across the 3Vs of big data (volume, velocity, and variety) and find correlations among diverse data.

What is Machine Learning?

Machine learning is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. With machine learning, computers can learn from experience, adjust to new inputs and perform human-like tasks. Artificial Intelligence and machine learning make it possible for computers to be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data, saving precious time and resources.

But there are many more ways AI and ML are shaping the supply chain industry. Here are some of the benefits you can expect to see in the future:

4 Benefits of AI and Machine Learning in Supply Chain Management:

 

1 – More Accurate Demand Sensing and Forecasting

With ML and AI, accurate forecasting is more achievable because all the data from a wide variety of factors are being tracked and updated in real-time. Organizations that adopt AI and machine learning are able to analyze data quicker and deliver better results. Having readily available data is a huge advantage to make game-time decisions at a moment’s notice, as well as identify better opportunities and avoid risks.

2 – Accelerated and Automated Operations

With the help of AI, businesses are able to plan, execute and automate operations across the entire network. These technologies don’t just easily and efficiently analyze huge volumes of data, they also optimize team workflows, communication, and decisions, which can also have an impact on other areas of business. For example, enhanced operations can lead to faster response times and better experiences for customers.

3 – Integrated Planning and Execution

Accomplishing shared goals and collaborating across teams at an enterprise-sized company can be challenging. But with machine learning and AI, organizations have better insights and intelligence across finance, operations, sales, and supply chain functions, enabling integrated planning and execution.

4 – Enhanced Customer Experiences

Technologies such as AI, big data and predictive analytics are changing the way companies interact with buyers, too. Consumer expectations are at an all-time high. Companies need to deliver personalized, dynamic customer experiences if they want to stay competitive. With ML, businesses are able to quickly access up-to-date consumer data and apply it to get a realistic view of the market, making it easier to answer the question, “What can we make, transport and deliver?”

In the future, data will be even more prevalent and omnipresent than it is today. Machine learning and AI will not just be useful in the supply chain industry, they will be a necessity.

 

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