AI in Strategic Talent Acquisition
Asif, S., Mathur, A., & Minz, N. K.
Recruitment is being rebuilt around artificial intelligence, but the same systems that promise faster, fairer hiring can also entrench the very biases they are meant to remove. This chapter asks how AI can be steered to widen diversity, deepen inclusion, and strengthen employer branding rather than simply automate old habits at greater speed.
Drawing on interdisciplinary research, it examines how natural language processing, predictive analytics, and machine learning are reshaping practice from resume screening and candidate engagement through to personalised branding and inclusive onboarding. The analysis weighs clear opportunities against ethical risks, among them data privacy, algorithmic bias, transparency, and accountability, and shows how AI can actively support underrepresented groups through anonymised screening, neurodiverse-friendly assessment, and equitable candidate experience design.
Rather than treating speed as the prize, the chapter frames responsible adoption as the goal, closing with a forward look at innovation that stays ethical, design that is inclusive, and genuine human-AI collaboration. Its argument is that these conditions are what allow organisations to build workforces that are resilient, diverse, and truly digitally fluent.
Artificial intelligence is reshaping talent acquisition from screening to onboarding, and this chapter argues its real value lies in advancing diversity, inclusion, and employer branding rather than mere speed. Used with attention to privacy, bias, and transparency, AI can widen access for underrepresented and neurodiverse candidates, but only through ethical design and human-AI collaboration.
- Predictive analytics, natural language processing, and machine learning now run through recruitment, reshaping resume screening, candidate engagement, personalised employer branding, and inclusive onboarding across the whole talent acquisition lifecycle.
- The chapter foregrounds diversity and inclusion, showing how AI can support underrepresented groups through anonymised screening, neurodiverse-friendly assessment, and fair candidate experience design when systems are deliberately built for inclusion.
- Alongside the opportunities, it weighs serious ethical risks, including data privacy, algorithmic bias, transparency, and accountability, treating responsible governance as inseparable from any credible use of AI in hiring.
- It closes by looking ahead to innovation that is ethical, design that is inclusive, and human-AI collaboration, arguing these conditions let organisations build resilient, diverse, and digitally fluent workforces.
Publication Details
Publisher
IGI Global Scientific PublishingAuthor
Asif, S., Mathur, A., & Minz, N. K.
Year
2026
Type
Book Chapter
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