Automation with time is becoming a go-term in several industries. From self-driving cars to social media posts, automation has become omnipresent. According to a report, Robotic process automation (RPA) software revenue grew 63.1% in 2018 to $846 million. It became the fastest-growing segment of the global enterprise software market. It is also slated to reach $1.3 billion in revenue by the end of 2019.\r\n\r\nEven though RPA today is invading almost every industry, the major adopters of this tech are banks, insurance companies, telecom firms and utility companies. This is because companies in these sectors usually have legacy systems and RPA solutions get easily integrated with their existing functionalities.\r\n\r\nRPA is often mentioned in the same breath as artificial intelligence, deep learning, machine learning and natural language processing. However, there are differences \u2014 many people think every aspect of automation is artificial intelligence, which is not true. RPA and AI are two horizontal technologies with a different set of goals and interfaces.\u00a0\r\nThe Real Difference Between RPA & AI\r\nAI is basically about a computer\u2019s ability to mimic human mentality \u2014 whether it\u2019s about recognising an image or even solving a problem or a debate.\r\n\r\nYou can take a look at Facebook\u2019s AI Research to understand better. Here, the social media giant feeds the AI system with different images and the machine delivers exacts results. When a photo of a dog is shown to the machine, it not only recognised it as a dog but also recognised the breed.\r\n\r\nRPA is a technology that uses a specific set of rules and an algorithm and based on that it automates a task. While AI is focused more on doing a human-level task, RPA is practically a software that reduces human efforts \u2014 it is about saving the business and white-collar workers\u2019 time. Some of the most common examples of RPA are transferring data from one system to another, payroll processing, forms processing etc.\r\n\r\nEven though AI is steps ahead than RPA, these two techs have the capability to take things to the next level if both are combined. For example, suppose you need your documents to be in a specific format to get them scanned, and RPA does this job. If you use an AI system that would filter out the poorly formatted or unsuitable documents, the work of the RPA would be much easier. And this collaboration is called Automation Continuum.\r\nThe Future\r\nThe rate at which the RPA and AI are evolving, the market definitely looks brighter in the coming years. Even giant companies like IBM, Microsoft and SAP are tapping more and more to RPA. Meaning, they are increasing the awareness and traction of RPA software. Furthermore, new vendors are also emerging and a rapid pace and have started to be marking their presence in the industry.\r\n\r\nHowever, it is not just RPA that is the talk of the talk, the role of AI is also one of the most significant things at present. The idea of Automation Continuum is becoming popular among a lot of organisations. The industry is now witnessing their capabilities and why not \u2014 AI can read, listen, and analyse and then feed data into bots that can create output, package it, and send it off. At the end of the day, RPA and AI are two valuable techs that organisations can use to aid their organisation\u2019s digital transformation.\r\n\r\nLooking into the future, it seems that more than talks about RPA and AI taking human jobs off, the talks about machine becoming humans\u2019 sidekick will be more.