Digitization and Automation Are Taking Over Supplying

The COVID-19 pandemic has shown us the urgency of supply automation, uncompromisingly and clearly. What role will AI and machine learning play in the process of digital transformation?
The current vulnerability of global supply, the need for 100% transparency and availability of digital technologies have made the majority of companies search for new options and technological means. With chatbots for customer communication management, advanced analytics for planning and predictions, self-driving vehicles or software able to detect and eliminate any ineffective chain elements, the logistic sector will be able to balance the use of robots and human employees and therefore, it will be able to handle potential problems and disruptions much better.
Artificial Intelligence and machine learning
What do the terms artificial intelligence and machine learning mean? And what’s the difference between them? Even though AI and machine learning work on similar principles, their tasks are different.
AI is usually implemented into an already existing system where the purpose is to teach machines to perform human activities. The main goal is to catch up with people, or even perform better. AI is quite sophisticated and is able to process even complex tasks and actively make decisions for achieving the best possible results.
Compared to artificial intelligence, machine learning is relatively simpler and less proactive. Roughly speaking, we can say that the algorithm strives for process optimization based on the principle of trial-error. Machine learning can be perfectly applied when processing wide data sets that would take too long if done manually.
Most common examples of automatization application
Planning and prediction
With the deployment of digital technologies, companies have a complex view on all of their processes at their disposal based on real data. Here, machine learning can be used for statistical analysis, evaluation of historical or environmental factors and rendering of typical behavioral patterns and trends.
Warehouse management
The options of AI utilization within warehouse management are almost limitless. From mechanical hands that sort, select and transfer a load, through software able to monitor and optimize daily movements in the warehouse, to cleaning robots that are able to work in a dynamically changing environment.
Chatbots
Robots for communication with customers are capable of executing huge amounts of customer requirements on a high quality level. Chatbots using AI can, besides routine operations, also handle a more sophisticated, customer-oriented communication and they can also deal with generating invoices or guiding customers through the payment process.
Self-driving vehicles
Even though these vehicles are still in the phase of development, their potential of changing the logistic world is more than obvious. Artificial intelligence will be able to self-drive a vehicle and make decisions based on the current traffic situation, weather or terrain conditions, thanks to a constant stream of data.
Related articles
Jul 11, 2024
Europe’s wind power industry relies on digital technologies
Europe’s wind power industry relies on digital technologies
Jul 11, 2024
Application for WMS? Vysoká efektivita, rychlé aktualizace, maximální variabilnost
Application for WMS? Vysoká efektivita, rychlé aktualizace, maximální variabilnost
Jun 7, 2024