Inteligência artificial no recrutamento e seleçãopercepções de governança, ética e justiça no processo decisório

Resumo

The advancement of Artificial Intelligence (AI) in Recruitment and Selection (R&S) has been driven by the promise of greater operational efficiency, scalability, standardization, and cost reduction. However, its accelerated incorporation also produces relevant sociotechnical tensions in the dimensions of governance, explainability, ethics, trust, and organizational justice. Given this scenario, this research was guided by the following question: how are companies in the Information Technology (IT) sector employing AI in their R&S processes, and what is the integrated perception of executives, HR managers, and candidates regarding the value generated, transparency, and justice in the decision-making process? The objective of the study was to investigate the adoption of AI in these processes within IT companies in Brazil, from the triadic perspective of senior executives, Human Resources professionals, and candidates. Methodologically, a qualitative, exploratory, and descriptive approach was adopted, using semi-structured interviews conducted with 38 participants linked to 13 organizations in the sector. The empirical material was subjected to Content Analysis until theoretical saturation was reached. The results revealed a significant asymmetry: although the adoption of AI is supported by business cases, productivity indicators, and competitive survival pressures, there are still practical governance gaps to ensure Responsible Artificial Intelligence (RAI). Algorithmic opacity, the absence of explainable criteria, and the possibility of reproducing discriminatory patterns compromise trust in the selection process. From the candidates' perspective, unilateral automation, the lack of structured feedback, and insufficient communication reduce the perception of interactional justice and affect the employer brand. As a practical contribution, the study proposes an interpretative framework and an Analytical Convergence Matrix for the responsible adoption of AI in R&S, articulating organizational capabilities, algorithmic governance, human supervision, and perceived justice. Furthermore, it offers managerial guidelines for companies to structure more transparent, auditable, and humanized selection processes, through explainability policies, restricted use of job-related data, continuous human supervision, training for HR teams, and organizational change management. It is concluded that AI can generate value by expanding the efficiency of R&S, provided its adoption is accompanied by concrete mechanisms of governance, human curation, and the preservation of the decision-making process's legitimacy.

Ficha do documento

Tipo

Dissertação

Ano

2026

Instituição

Fundação Getulio Vargas

Fonte

Repositório da FGV

Idioma

Português

Acesso

Acesso aberto

Identificador

oai:repositorio.fgv.br:10438/40518

Temas

EconomiaDesenvolvimento EconômicoTecnologiaDadosGovernança

Palavras-chave

Inteligência artificialRecrutamento e seleçãoGovernança de TIJustiça organizacionalÉtica algorítmicaArtificial intelligenceRecruitment and selectionIT governanceOrganizational justiceAlgorithmic ethicsAdministração de empresasPessoal - RecrutamentoPessoal - Seleção e admissãoMercado de trabalho - Efeito de inovações tecnológicasODS 10: Redução das desigualdadesODS 5: Igualdade de gêneroODS 8: Trabalho decente e crescimento econômico