Inteligência artificial aplicada a gestão de pessoas: projeto chatbot

Abstract

The speed of change and the volume of information coming from the V.U.C.A world are recurrent in organizational environment. In this sense, companies seek to improve the Employee Experience and their organizational climate. The challenges of competitiveness and innovation for airlines are constant and increasingly complex due to market dynamics. The digitization of processes is inevitable in the digital transformation of a business and people, culture and organizational communication are part of this construction. The area of artificial intelligence has been evolving very quickly along with computing technologies. The development of machines capable of performing tasks, which until then were exclusively human, such as customer service, for example, has become increasingly common. In this way, chatbots are a technology that has revolutionized the way companies are providing their services, allowing the reduction of personnel costs, standardization of information and a better experience for their end user. Among the various applications is customer service, in which the customer can obtain information, get answers to questions, and carry out operations in an autonomous, practical, and high-quality manner. Thus, it presents a benchmarking with updated information of three companies in the transport sector, highlighting benefits and challenges faced. Subsequently, a practical application in the company GOL Linhas Aéreas is studied in detail with feasibility information, awareness actions, discussion of steps taken, and benefits achieved. Finally, a step-by-step implementation of a chatbot in the HR area was prepared with a respective checklist to verify the main points. It may conclude that this implementation project can present a series of benefits, both tangible and intangible for a transport company and typical fears of employees such as the lack of humanization in service through the lack of human contact did not prove to be valid. The respective results can help in guiding more complex or detailed future projects and research.