Strategic Human Resources Management and Artificial Intelligence: A Practice-Oriented Forecast with an Emphasis on the Brazilian Context

Edvalter B. Holz ()
Additional contact information
Edvalter B. Holz: Insper Institute of Education and Research

Chapter Chapter 9 in HRM, Artificial Intelligence and the Future of Work, 2024, pp 171-191 from Springer

Abstract: Abstract Artificial Intelligence (AI) has been lauded as a revolution in Human Resources (HR). However, the discussion primarily revolves around promises, potentially represents a setback for Strategic Human Resources Management (SHRM), and fosters irresponsible experimentation. In this context, this chapter offers a forecast of how SHRM and AI could become intertwined based on the theoretical perspective of imbrication, with an emphasis on the Brazilian context. This involves aligning SHRM’s significant objectives with AI’s intrinsic features, leveraging AI-driven opportunities in SHRM, establishing enduring routines for AI-driven SHRM, and integrating AI as a fundamental organization dimension. The overarching conclusion suggests that substantial changes in HR owing to AI might require years to materialize and investments beyond technology alone or might not manifest on a significant scale. In the Brazilian context, this endeavour will require additional effort due to the lack of a systemic perspective, shortage of technology professionals, ineffective management practices and hybridism. SHRM leaders can leverage the country’s technological momentum, the international gig economy, and the flexibility and plasticity of Brazilian organizational cultures.

Keywords: Artificial intelligence; Brazil; Leadership; Sociomateriality; Strategic human resources management (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-62369-1_9

Ordering information: This item can be ordered from
http://www.springer.com/9783031623691

DOI: 10.1007/978-3-031-62369-1_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().