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The Role Of AI In Talent Management

In the world of today, talent management without technology is akin to a pizza without cheese – it will surely be ineffective in its functioning and incapable of delivering a sustainable result! Technology is enabling every part, every type of business to function better, building in more capabilities and enhanced efficiency. And with talent management being intrinsic to any progressive business of today, technology has not left this untouched either.

With machines and humans coming together more than ever in the digital age of today, a number of technologies have emerged, offering immense possibilities for human resource professionals. Artificial intelligence (AI) is among the more significant technologies, and simply put, is characterized by:

  • Allocating value-adding work for humans, such as talent development
  • Outsourcing routine, mundane tasks to machines

Is AI a necessity for talent management?

AI and talent management have a close relationship, with AI bringing many advantages, chief among them being fast and accurate outcomes through streamlined HR processes. Employees now expect to see the use of AI in talent management, having seen the advantages it brings to other aspects of daily life, such as online shopping, web browsing, or pop-up chatbots. The following are some functions where HR could put AI to use:

  • Talent acquisition: Recruiters and HR professionals have been using AI to simplify a number of their high-volume, repetitive activities. These include:
  • Screening of resumes
  • Selecting CVs with the use of natural language processing (NLP)
  • Using chatbots to engage candidates
  • Payroll
  • Talent development and learning: AI offers the advantage of learning recommendations personalized to the requirements of particular users, engaging them better and facilitating improved performance. This serves the needs of employees well, as they essentially require learning at the point of need i.e. to solve particular work problems, other than adding to their body of knowledge. By looking through employee interactions, AI analyzes current skillsets and career aspirations, thereby recommending learning needs and nuggets when they are most needed by an employee. It also helps to build employee ownership in the learning process through upskilling and leadership coaching.
  • Engagement and performance: Through analysis of employee interactions on workplace fora, AI attempts to understand employee sentiments. Studying the intranet, emails, and more, it tries to know more about employee opinions and preferences, information that is extremely useful for human resource professionals. This also helps to design performance management systems through detailed feedback on individual and team performance, a further pointer to the relationship between AI and talent management, allowing HR to design platforms for worker engagement that provide positive work interactions.
  • Career progression: The employee journey does not end after the talent acquisition step, and AI has a role to play here. It helps to interlink workforce planning, learning, and performance management systems, which facilitates drawing out better career paths for employees and improving succession planning. Employees are made able to take on more ownership and responsibilities, as they are empowered and can then grow vertically and horizontally in their careers.
  • Recognition and rewards: AI can allow customized performance rewards, allowing employees to select from a bucket of rewards as per their life stage, aspirations, financial situation and other factors.

How can AI be implemented by HR?

For AI to function efficiently, the first step is to get the right data, the core of any good AI algorithm. The following capabilities are essential:

  • Organizing available data: There is a vast amount of data available with every organization, but it is mostly unsorted and no one really knows what data lies where. Human resource professionals must work to assimilate and organize data to provide the right data feeds for AI to work well.
  • Analytics: Data is just data until it is analyzed and critical insights for employees are obtained. The talent development team could choose to hire data scientists and experts or to upskill existing employees for the same so that the right tools and platforms are put in place.
  • Experience and usability: There must be a balance between machine interaction and the human touch. More harm than good can come from a clumsy AI system, and there must be adequate intuitiveness and ease of adoption and usage, along with regular tweaking as needed.
  • Bias-free: AI needs to be trusted by employees, which is possible only if due weight is given to fairness, privacy, confidentiality, and security. The actions of the system must be easy to understand so that HR can act accordingly.

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