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AI recruitment challenges in India include difficulties in technology engagement across generations, interpreting training feedback, and linking it with performance. Restrictive labor laws result in cautious hiring practices, which, combined with a lack of workforce skills, hinders effective AI integration. Policymaking must evolve to address social and ethical concerns of rapid AI deployment.
The AI recruitment challenges faced in India are multifaceted, involving both socio-economic factors and technological barriers. Firstly, given the varying generational demographics in the workplace, some employees may struggle to engage with technology-driven training programs. This disengagement can be attributed to a discomfort with new technologies or a lack of required skills, as noted by Maity (2019). In addition, there are difficulties in correlating training feedback with measurable outcomes such as performance improvement, training transfer, and understanding trainee characteristics.
Furthermore, with India's demanding labor laws, companies are restricted in their hiring and firing capabilities, leading them to hire fewer workers and rely more on AI for recruitment. This can inadvertently exacerbate the challenge of workforce readiness, as Indian workers may lack the necessary skills to work alongside AI-enhanced processes. In this context, the Indian government has an important role to play in reforming labor laws and investing more heavily in education, vocational training, and workforce development programs to enhance skills alignment with AI requirements.
Moreover, while AI has the potential to contribute to the achievement of the United Nations Sustainable Development Goals (SDGs), it is imperative to consider the social and ethical implications of its rapid deployment. Policymaking and regulatory frameworks must keep pace with technological advancements to mitigate potential risks associated with AI, such as undermining human agency and exacerbating socioeconomic divides.
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