Talent Management in the Age of AI: What You Need to Know

Jim van Hulst has worked in several leadership functions at EY, ING Bank, ABN AMRO Bank, and Johnson Controls International. His positions have included Director Talent Management, Global Head Professional Development, and Global Learning Technology Leader. Jim has an MSc. in Learning Technology from the University of Sheffield and a Bachelor of Education from the University of Arnhem/Nijmegen. He also holds a diploma in Business Management and Leadership from the Rotterdam School of Management, and he completed his MBA in 2020 from MSM, The Netherlands. He is a frequently asked speaker and author of numerous articles. Jim founded Jignite recently in 2021.

Jim van Hulst, owner Jignite

What can AI do in Talent Management?


Artificial intelligence (AI) is not a new concept, but it has become more prevalent and powerful in recent years. AI refers to advanced data analysis procedures that allow us to study not just the clean, organized, numerical data that traditional regressions can handle, but also messy, unstructured, non-numerical data too. AI can help us make sense of large and complex datasets, uncover hidden patterns and insights, and automate tedious and repetitive tasks.

AI and Talent Management

One of the areas where AI can have a significant impact is talent management. Talent management is the process of attracting, developing, and retaining the best people for an organization. It involves various functions such as recruitment, performance management, learning and development, succession planning, and employee engagement. Talent management is crucial for organizational success, as it can enhance productivity, innovation, customer satisfaction, and competitive advantage.
However, talent management is also challenging, especially in the current context of the 2022-2023 Great Resignation, where millions of people are voluntarily quitting their jobs and looking for new opportunities. Traditional approaches to winning and keeping talented workers may not be enough in this fiercely competitive market. Moreover, talent management involves dealing with human complexities, such as emotions, motivations, preferences, and biases, which are not easy to measure and understand.

Where can AI help?

This is where AI can help. AI can assist talent management in various ways, such as:

  • Optimizing the recruitment process by comparing employers’ hiring profiles and prospective employees’ skills, qualifications, and personality traits. AI can also help reduce bias and increase diversity in hiring decisions by screening candidates based on objective criteria and removing irrelevant information from resumes. LinkedIn has found that an AI-assisted job search is at least 50% more efficient.
  • Enhancing the development process by providing personalized and adaptive learning experiences for employees. AI can also help identify skill gaps and career aspirations and recommend suitable courses, mentors, and projects for employees to grow and advance. AI-based talent intelligence tools can help HR teams demonstrate their commitment to career management by mapping employee careers within the company based on data from resumes and historical data about skills needed in certain roles.
  • Improving the retention process by monitoring employee engagement, satisfaction, and well-being. AI can also help predict employee turnover and attrition and suggest interventions to prevent or reduce them. AI can further help create a culture of recognition and feedback by enabling timely and meaningful rewards and appraisals for employees.

What you need to know

AI can offer many benefits for talent management, but it is not a silver bullet. There are also some risks and drawbacks that need to be considered, such as:

  • Low trust in AI decision-making. Employees may not trust or accept the outcomes of AI systems, especially if they are not transparent or explainable. Employees may also feel threatened or dehumanized by AI, especially if they perceive it as a replacement or a competitor. Therefore, it is important to involve employees in the design and implementation of AI systems and to ensure that they have a voice and a choice in the process.
  • Bias and ethical concerns. AI systems are not immune to bias, as they may reflect the data and assumptions that are fed into them. Bias can lead to unfair and discriminatory outcomes for employees, such as being overlooked for a promotion or a training opportunity. Therefore, it is important to audit and monitor AI systems regularly, and to ensure that they adhere to ethical principles and standards.
  • Legal risk. AI systems may pose legal challenges, such as who is responsible and accountable for the decisions and actions of AI, and what are the rights and obligations of employees and employers in relation to AI. Therefore, it is important to consult with legal experts and regulators and to establish clear and consistent policies and guidelines for the use of AI in talent management.


AI will transform talent management further in 2024. However, AI is not a substitute for human judgment and interaction. AI should be seen as a partner and a tool that can augment and complement human capabilities and efforts. Talent management is about people, and AI can help us understand and serve them quicker, not perse better.

  • HBR. Where AI Can — and Can’t — Help Talent Management, see link
  • Forbes. Rethinking Talent Management Through AI, see link
  • Gartner. AI in HR: A Guide to Implementing AI in Your HR Organization, see link
  • Cangrade. Artificial Intelligence in Talent Management and the Future of Work, see link

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