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?<\/p>\n
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.<\/p>\n
What do the terms artificial intelligence and machine learning mean? And what\u2019s the difference between them? Even though AI and machine learning work on similar principles, their tasks are different.\u00a0<\/span><\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n","protected":false},"excerpt":{"rendered":" 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 […]<\/p>\n","protected":false},"author":2869,"featured_media":4333,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13,6],"tags":[],"acf":[],"yoast_head":"\nMost common examples of automatization application<\/h2>\n
Planning and prediction<\/h3>\n
Warehouse management<\/h3>\n
Chatbots<\/h3>\n
Self-driving vehicles<\/h3>\n