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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Categorisation

Introduction

ML and AI have been gradually being adopted in different fields including the HR department. In HR, these technologies are being used in order to optimise and leverage different processes and to prepare the ground for more high-level, analytical and informed decisions. Some of the key applications of AI and ML include the organization of large amounts of HR information. This involves organizing employee information, application for jobs, performance ratings and many other aspects. Here, AI is a game changer with the capacity to transform how HR functions and improve on efficiency and productivity.

Challenges

There are, however, some challenges that come with the integration of ML and AI in HR categorisation. A key issue is that of data privacy and security. Since HR departments possess employee data, it is imperative that such AI and ML applications adhere to the data privacy laws. In addition, the technology used in the process must be able to analyze and interpret various types of data. This includes the challenge of perceived usefulness and usability. Some HR managers might not be familiar with the concept of AI and ML in HR or may not understand the benefits and applications of these technologies which therefore poses a challenge to adoption. Also, there is a problem of bias. If the data that the AI and ML algorithms are trained on is prejudiced in some way then the systems can reinforce or exacerbate these biases during the categorisation process.

AI Solutions

These are the challenges that AI and ML solutions are aimed at solving and how they can transform HR categorisation. For example, there are AI-based HR solutions such as Eightfold. ai which applies machine learning to match candidates to jobs. Another example is IBM’s Watson that applies AI to analyse and interpret employee sentiments derived from feedback surveys. These solutions incorporate advanced algorithms that are capable of working with large and varied datasets and are also developed to prevent bias. In addition, these platforms have integrated secure features to meet the needs of data privacy. Also, the two are also applied in predictive analytics where they are used to categorise possible future events by analysing existing information to enable planning.

Benefits

There is a wide range of advantages that come with the application of AI and ML in HR categorisation. It increases efficiency because AI can work through large amounts of data to categorise it much faster than a human can. This in turns leads to both time and cost efficiencies. This paper also finds that AI and ML also improve the accuracy of categorisation by minimising the possibilities of errors that are likely to occur in the handling of data by humans. The use of these technologies also enable the HR professionals to make better decisions as they will be able to analyse the data that has been organised. Also, AI and ML tools can enable a better employee experience since they can help to categorise employee information to understand their tastes and habits.

Return on Investment

There are significant return on investment (ROI) when implementing AI and ML in the area of HR categorisation. For instance, Unilever made a savings of €1 million in recruitment expenses when the company employed AI for screening and categorizing candidates. Also, AI can help in decreasing the time taken to perform routine tasks thus enabling the HR personnel to work on other important activities. This can result to high levels of employee engagement and productivity thus increasing the returns. Furthermore, the predictive analysis that is provided by AI and ML offers an opportunity for organisations to make better decisions and may result to better business results and increased profitability.

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