Artificial intelligence (AI) is more accessible than ever and is increasingly used to improve business operations and outcomes, not only in transportation and logistics management, but also in diverse fields like finance, healthcare, retail and others. An Oxford Economics and NTT DATA survey of 1,000 business leaders conducted in early 2020 reveals that 96% of companies were at least researching AI solutions, and over 70% had either fully implemented or at least piloted the technology. Nearly half of survey respondents said failure to implement AI would cause them to lose customers, with 44% reporting their company's bottom line would suffer without it. Simply put, AI enables companies to parse vast quantities of business data to make well-informed and critical business decisions fast. And, the transportation management industry specifically is using this intelligence and its companion technology, machine learning (ML), to gain greater process efficiency and performance visibility driving impactful changes bolstering the bottom line.

One of the disruptive technologies that has gained increasingly more attention after the turn of the century is Machine Learning. Machine Leaning – closely related and usually considered as a subfield of Artificial Intelligence (AI) – is the process of automatic detection of usable patterns within data. The detection of these patterns is performed with the help of machine learning algorithms which are specifically tailored to deal with complex and large data sets. Such powerful algorithms have the potential of drastically revolutionizing the way of doing business and how businesses operate. With this article I will provide an overview of opportunities that machine learning algorithms and Artificial Intelligence (AI) pose to the business environment.