Is about changing and dynamic management, which requires constant revision and updating. Organizational talent management involves areas such as recruitment and selection, talent development and retention, performance evaluation, strategic workforce planning, executive talent assessment, and management of promotions, among others. In each of these areas, there are specific challenges that entail multiple decision-making processes whose outcomes can be very significant and even compromise the sustainability of the company. Some of these challenges include identifying optimal candidates, reducing biases in the selection process, personalizing talent development, and ensuring objectivity in performance evaluation, for example.AI holds promise in automating candidate filtering, predictive turnover risks, facilitating AI-assisted assessment tools, and recommending growth opportunities. However, integrating AI faces significant obstacles, such as biases in data, data privacy and security concerns, and the need for integration with existing systems. This article emphasizes the importance of a careful and considered approach to integrate AI in talent management, ensuring that technology serves as an enabler for achieving organizational goals ethically and sustainably. Undoubtedly, by addressing biases, AI can create more fair, prosperous, and efficient organizations, reducing inequalities, and contributing to economic growth in Society.

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Challenges of Artificial Intelligence in Strategic Decisions: Talent Management

  • Sergio Carol,
  • Patricia Rodriguez-Garcia

摘要

Is about changing and dynamic management, which requires constant revision and updating. Organizational talent management involves areas such as recruitment and selection, talent development and retention, performance evaluation, strategic workforce planning, executive talent assessment, and management of promotions, among others. In each of these areas, there are specific challenges that entail multiple decision-making processes whose outcomes can be very significant and even compromise the sustainability of the company. Some of these challenges include identifying optimal candidates, reducing biases in the selection process, personalizing talent development, and ensuring objectivity in performance evaluation, for example.AI holds promise in automating candidate filtering, predictive turnover risks, facilitating AI-assisted assessment tools, and recommending growth opportunities. However, integrating AI faces significant obstacles, such as biases in data, data privacy and security concerns, and the need for integration with existing systems. This article emphasizes the importance of a careful and considered approach to integrate AI in talent management, ensuring that technology serves as an enabler for achieving organizational goals ethically and sustainably. Undoubtedly, by addressing biases, AI can create more fair, prosperous, and efficient organizations, reducing inequalities, and contributing to economic growth in Society.