The global population is growing at an alarming rate, and with it comes the challenge of finding new ways of producing enough food to feed everyone. The current state of the food production industry calls for a shift in strategy if we want to ensure that everyone has access to healthy and nutritious food in the future. Artificial intelligence (AI) is one of the key tools we need to achieve this goal. With AI, we can tackle complex problems, optimize processes, and produce results that would be much harder or even impossible to do manually. In this article, we will explore how AI will change how we feed the world, offer some valuable insights to farmers, and show where AI currently succeeds in food production and where it still has its limitations.

The advance in technology is present in all areas of our lives, especially in business. In fact, technology is part of practically all the processes that are involved in commercial transactions, industrial projects, undertakings of any kind, etc. It is easy to understand why technology is so necessary, especially in the business area. It not only improves productivity but also provides much-needed tools for international trade, among other things. Today, being at the forefront of technology is more of a necessity than an option.

Every department in a company has its own challenges. In the case of Human Resources, recruitment and onboarding processes, employee orientations, process paperwork, and background checks is a handful and many a time painstaking – mostly because of the repetitive and manual nature of the work. The most challenging of all is engaging with employees on human grounds to understand their needs. As leaders today are observing the AI revolution across every process, Human resources is no exception: there has been a visible wave of AI disruption across HR functions. According to an IBM's survey from 2017, among 6000 executives, 66% of CEO's believe that cognitive computing can drive compelling value in HR while half of the HR personnel believe this may affect roles in the HR organization.

As the manufacturing industry is moving away from the traditional long term service contract to an'Analytics-as-a-Service' model, big data applications are increasingly being used to collect data from manufacturing operations. Using big data, you can accurately predict failure in operations well ahead of time, increasing the service revenue and reducing the cost of service. In addition, you can predict the health of your equipment in real time, and release equipment for maintenance only when necessary. Through the use of neural networks, support vector machines, and decision trees, you can identify complex interdependencies within operational parameters and detect anomalies that lead to equipment failures.