Recruitment in 2030: An Overview of AI-Powered Talent Acquisition and Hiring

This study aims to provide an analysis of the state of recruitment in 2030. In addition, it offers a thorough analysis of AI-powered hiring solutions, stressing their effectiveness, capacity to match candidates, and user experiences while tackling issues like data privacy, equity, and implementation difficulties. Additionally, it examines AI technologies such as video interviews, chatbots, machine learning, Natural Language Processing (NLP), and predictive analytics, giving HR managers advice on how to use AI in talent management and acquisition. The article also covers future HR characteristics and more general HR duties that are necessary for companies to stay innovative and competitive. It also looks at how the Web3 economy and block chain affect hiring practices, pointing out inefficiencies in the way things are done now with ATS, AI, and outside agencies. Through tools for candidate matching, resume screening, interview scheduling, and diversity promotion, the study emphasizes AI's role in maximizing recruitment. It goes on models, research, and real-world instances of AI solutions used in talent acquisition. The potential and difficulties in a globalized and digitalized economy are discussed from the perspective of HR in 2030. Along with examining demographic, economic, and technological developments, the report also looks at the demands for job creation from 2020 to 2030 and the effects of globalization, automation, and other factors on occupations and skills.

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Publication Details

Journal
GBS Impact Journal of Multi Disciplinary Research
Published
2025-01-22
DOI
https://doi.org/10.58419/gbs.v10i2.1022407
Primary Topic
Human Resource and Talent Management
Type
article
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article

Recruitment in 2030: An Overview of AI-Powered Talent Acquisition and Hiring

Shweta Sajjanar, Sonali Kudtarkar
GBS Impact Journal of Multi Disciplinary Research
Human Resource and Talent Management
article

Recruitment in 2030: An Overview of AI-Powered Talent Acquisition and Hiring

Shweta Sajjanar, Sonali Kudtarkar
article en

Abstract

This study aims to provide an analysis of the state of recruitment in 2030. In addition, it offers a thorough analysis of AI-powered hiring solutions, stressing their effectiveness, capacity to match candidates, and user experiences while tackling issues like data privacy, equity, and implementation difficulties. Additionally, it examines AI technologies such as video interviews, chatbots, machine learning, Natural Language Processing (NLP), and predictive analytics, giving HR managers advice on how to use AI in talent management and acquisition. The article also covers future HR characteristics and more general HR duties that are necessary for companies to stay innovative and competitive. It also looks at how the Web3 economy and block chain affect hiring practices, pointing out inefficiencies in the way things are done now with ATS, AI, and outside agencies. Through tools for candidate matching, resume screening, interview scheduling, and diversity promotion, the study emphasizes AI's role in maximizing recruitment. It goes on models, research, and real-world instances of AI solutions used in talent acquisition. The potential and difficulties in a globalized and digitalized economy are discussed from the perspective of HR in 2030. Along with examining demographic, economic, and technological developments, the report also looks at the demands for job creation from 2020 to 2030 and the effects of globalization, automation, and other factors on occupations and skills.

GBS Impact Journal of Multi Disciplinary ResearchVol. 10(2)
KLE Technological University (IN), Hanoi University of Business and Technology (VN)
Openalex Percentile: Top 98%
Human Resource and Talent Management
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Recruitment in 2030: An Overview of AI-Powered Talent Acquisition and Hiring — Shweta Sajjanar, Sonali Kudtarkar · GBS Impact Journal of Multi Disciplinary Research (2025) | TGRS Research Map | TGRS