AI-based applications bring noticeably more efficient HR processes, as they can be used, for example, to provide and evaluate basic key figures for employees quickly and easily. Examples from recruiting or skill management also show how AI and machine learning (ML) -based tools can support human resources. Artificial intelligence (AI) in human resources has been a trend for years.
Table of Contents
Because of the potential of these new technologies, the development that is emerging here is a logical consequence. AI-based applications bring noticeably more efficient HR processes, as they can be used, for example, to provide and evaluate basic key figures for employees quickly and easily. Examples from recruiting or skill management also show how AI and machine learning (ML) -based tools can support human resources as a talented assistant.
In the HR area, AI is primarily about the automation of workflows and about correlating data from different sources with one another. The aim is, for example, to create regular reports on topics such as salary development and forecasts that are not only based on internal data but also integrate external sources. In this way, strategically essential insights can be gained, for example, on whether the company pays industry-specific wages that also correspond to current benchmarks. This is a decisive factor for the company’s attractiveness as an employer. With the help of AI, internal company data from different departments and functions can also be automatically consolidated, and conclusions can be drawn from the information.
In the area of prescriptive data analysis, AI can also support the creation of reliable forecasts. HR managers can run evaluations across all levels and business areas to derive specific conclusions, for example, future employee needs. External data such as demographic analyzes or weather information can also be used to identify expected economic or seasonal changes in advance – for example, seasonal peak times when more workers are needed in the company.
In skill management and business development, AI-based applications also make it possible to automatically compare the skills of employees that have already been recorded in a structured manner with the requirements that will result from future projects. In this way, HR managers can quickly understand whether and, if so, how many resources are available in-house to cope with new tasks. Another example of IT-supported personnel forecasts is the analyzes of the retirement age. From this, too, further conclusions can be drawn for future employee needs.
For example, in application processes, AI-based applications enable the automated comparison of information in the résumé and cover letter with the skills required in the job advertisement. On this basis, HR managers can then make an initial pre-selection. Then some chatbots automate more and more administrative and work processes in companies. The primary aim here is to efficiently deal with frequently recurring and always the same functions, which manage in dialogue form with a limited number of question and answer options, with the help of voice-based user interfaces. In the initial interview phase, chatbots can be used, for example, to query basic information – such as criteria that the new position requires, such as programming skills, foreign languages , or an adequate degree. In the DGFP study mentioned at the beginning, 70 percent of those questioned support such a use of AI in chatbots and applicants’ pre-selection.
In the long term, machine learning and AI in human resources will become the determining technologies in HR. This development is already becoming apparent. In conjunction with constantly growing amounts of data, ML algorithms enable predictions to become more and more accurate and deliver more precise results. When first approaching applicants or analysis tools for salary comparisons or skill management, approaches such as chatbots are only the tip of the iceberg here.
But it is also a fact: companies will still need staff in the age of AI-supported applications. The study “The Skilling Challenge” published by Ashoka Germany and McKinsey & Company shows, for example, that more jobs are created than lost through automation. However, the requirement profile changes. People will noticeably be less concerned with routine tasks than with monitoring IT processes or the review and further evaluation of the results they receive through intelligent HR analytics solutions.
In general, the human factor will continue to play a significant role in the future, especially in the personnel area. Because many decisive criteria that play an essential role in recruiting processes, for example, elude data-supported analyzes. This includes answering the question of whether the proverbial chemistry between candidate and employer is correct. Personal interviews will also be indispensable for assessing other soft but less decisive factors such as emotional intelligence, charisma, presentation skills, or leadership qualities. So in the future, too, AI will primarily help as an assistant in the provision and processing of information. Humans still make the final decisions.
Google Home Max White Speaker is an AI Smart Speaker that allows users to have… Read More
DisneyPlus.com has become a precious streaming platform for millions worldwide, thanks to its vast library… Read More
In this digital era, almost everyone has a part in Instagram. Many social media platforms… Read More
Have you ever heard of the PNPCODA entry? If you still want it, you will… Read More
In this era of technology and virtual spaces, the term "Hyperverse" has gained grip as… Read More
In rapidly developing dynamic educational geography, searching for innovative ways to engage students in meaningful… Read More