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In the digital age, the training in companies can be facilitated through a proper system to the company's demand. A learning platform personalized to the profile of employees can facilitate the selection of training that tailored to their roles. This research aims to investigate the existence of adaptation and personalization of learning management systems (LMS) in enterprise context, that facilitate the selection of learning's content suited for employees' roles. This study focuses on literature reviewto understand the importance of a personalizedLMSin company, especially in selection of content that adequate to role of each employee.

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Many organizations' performance and survival challenges need dynamic capabilities and technology to speed the development of those capabilities. Companies are constantly visiting the strategies used in learning as a crucial element in preparing their workforce for the accelerated changes. Learning Technologies stand as a facilitator of these challenges, which is why they are so important. There is still a good margin of exploration in the field of the learning technologies. The reality is that a reduced number of studies explore the technology as important in accelerating innovation, performance, and competitiveness. The present research will focus on the strategic implementation of learning technologies. The approach we chose to solve this problem is to develop guidelines that support the strategy for implementing technology in the learning field. The approach will allow us to relate the strategy with the challenges and the impact the organization is expected to achieve.

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This position paper provides an overview of the most important practices in the field of Artificial Intelligence (AI) used in educational contexts, with a focus on the main platforms used for teaching (LMS) to support the development of a research work at EduardoMondlane University (UEM) in Mozambique. To that end, definitions and descriptions of relevant terms, a brief historical overview of Artificial Intelligence (AI) in education and an overview of the common goals and practices of using computational methods in educational contexts are provided. The state of the art regarding the adaptation and use of Artificial Intelligence is presented and we discuss the potential benefits and the open challenges. The paper also presents the methodology and key steps which will be developed at UEM to achieve the research goals.

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