I am Mrignayni, a content strategist and copywriter for B2B tech companies of the world. Earlier, widespread automation meant the introduction of service sector jobs or big stupid machines doing repetitive work in factories. That's not the case a couple of decades down the line, is it? Machines are now capable of breaking down complex jobs into smaller, predictable ones that need very little specialization. What is the future of automation?

Earlier, widespread automation meant the introduction of service sector jobs or big stupid machines doing repetitive work in factories. That's not the case a couple of decades down the line, is it? Machines are now capable of breaking down complex jobs into smaller, predictable ones that need very little specialization. We are on the verge of being outcompeted! What is the future of automation?

Machine learning has been one of the biggest advancements in the history of computing, and now it is believed to be capable of taking on significant roles in the field of big data and analytics. Big data analysis is a huge challenge from the perspective of businesses. For example, activities such as making sense of huge volumes of varied data formats, data preparation for analytics and filtering redundant data can consume a lot of resources. Hiring data scientists and specialists is an expensive proposition and not within every company's means. Experts believe that machine learning is capable of automating many tasks related to analytics – both routine and complex.

An engineer at IBM once told me that the future of information technology could be summed up in a few key terms: mobility, cloud computing, the internet of things, and automation and artificial intelligence. It is worth bearing in mind that automation and artificial intelligence are becoming more and more prominent topics within the public sphere, especially with the emergence of powerful AI like IBM's Watson and DeepMind's AlphaGo. These forms of artificial intelligence, also referred to as robots or bots for short, don't necessarily take up physical space. Instead, they are programs, stored on a desktop or a cloud, that have the ability to learn and adapt to different situations as opposed to earlier programs that were more rigid. Because of their learning capabilities, these robots can perform tasks that were deemed impossible by earlier programmers: Robots can write stories, they can understand human speech, and they can diagnose a patient better than their own doctor can.