Through natural language processing recruitment

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decisions. Through Natural language processing, recruitment portals have also become very common. These portals help in handling mass hiring whereby human resource managers need to sort thousands of resumes depending on the keywords (Hirschberg and Manning, 2015). e. Robotics Process Automation There has been intensifying interest in robotics and its application of AI technologies. As automation becomes a norm in many organisations, Robotic process automation is a new form of business process automation technology and already in place within organisations and they are benefiting from its outputs. Robotic Process Automation is very useful in maximizing optimal results and more efficient . Reports have indicated that 25
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the top priorities for robotics automation are to focus on continuous improvement, increase the level of automation and develop analytics capabilities. The number of organisations showing interest in robotic process automation has also increased as compared to the past years regarding to improving services and reducing cost (Gami, et al , 2019). f. The Rise in Intelligent Applications When AI meets application development the outcome is intelligent application. These intelligent applications can constantly learn from user interactions and other data sources to become more important and useful. AI has been incorporated into enterprises through the creation of Web applications and mobile applications. AI is helping specifically in prioritizing to-do lists, schedule meetings as well as find hidden insights in data. Those applications is very useful in matter of saving time and more efficient . As such, the use of intelligent applications is expected to rise since most of the world's largest companies are exploiting AI in order to improve customer experience (Joshi, 2018). 4.2 Contribution of AI to technology improvements AI has significantly contributed to technology improvements in the past few years with companies benefiting from its applications. For instance, in the finance industry, loan management has been easier than it was before. A company such as Capital Float uses machine learning internally to automate loan underwriting. By doing so, it is able to offer unsecured business loans to small and medium businesses by collecting all the relevant data from its customers. Generally, the internal software uses machine learning to track 26
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loan repayments and also identify potential loan defaulters. In addition to that, the company also uses machine learning to deliver financial solutions for small and medium enterprises across e-commerce and other digital remittances (Lin, et al, 2018). In the service industry, AI has also been applied to contribute to technology improvements in terms of risk management. In this regard, the Bombay Stock Exchange in India has introduced a data analytics solution that tracks social media shared news which is related to companies listed in the stock exchange. In this case, machine learning is used to detect potential risks of market manipulation and also rumours, and thereby, mitigate such risks.
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