Revolutionizing Talent Acquisition in Indonesia's E-Commerce Industry: The Transformative Impact of AI and Machine Learning

Background The potential for artificial intelligence (AI) to transform healthcare cannot be ignored, and the development of AI technologies has increased significantly over the past decade. Furthermore, healthcare systems are under tremendous pressure, and efficient allocation of scarce healthcare resources is vital to ensure value for money. Health economic evaluations (HEEs) can be used to obtain information about cost-effectiveness. The literature acknowledges that the conduct of such evaluations differs between medical technologies (MedTechs) and pharmaceuticals, and poor quality evaluations can provide misleading results. This systematic review seeks to map the evidence on the general methodological quality of HEEs for AI technologies to identify potential areas which can be subject to quality improvements. We used the 35-item checklist by Drummond and Jefferson and four additional checklist domains proposed by Terricone et al. to assess the methodological quality of full HEEs of interventions that include AI. Results We identified 29 studies for analysis. The included studies had higher completion scores for items related to study design than for items related to data collection and analysis and interpretation of results. However, none of the studies addressed MedTech-specific items. Conclusions There was a concerningly low number of full HEEs relative to the number of AI publications, however the trend is that the number of studies per year is increasing. Mapping the evidence of the methodological quality of HEEs of AI shows a need to improve the quality in particular the use of proxy measures as outcome, reporting, and interpretation of the ICER.

show abstract

Revolutionizing Recruitment: The Role of Artificial Intelligence in Talent Acquisition

Raji N,

George,

Iyer

et al. 2024

ShodhKosh J. Vis. Per. Arts

View full text Add to dashboard Cite

The rapid advancements in Artificial Intelligence (AI) are transforming various sectors, and talent acquisition is no exception. This research paper exploring how AI-driven tools are reshaping the way organizations attract, evaluate, and hire talent. With the global competition for top talent intensifying, the need for efficient, data-driven hiring strategies is critical. AI technologies, including machine learning, natural language processing, and predictive analytics, have become pivotal in streamlining tasks such as resume screening, candidate matching, and interview scheduling, significantly reducing time-to-hire and improving candidate experiences. This paper conducts a thorough analysis of AI's integration into talent acquisition, AI’s benefits, challenges, and ethical considerations. Key findings show that AI reduces hiring time by up to 50%, enhances candidate engagement through automation, and allows for more informed hiring decisions. Despite its potential, organizations must carefully manage the ethical challenges AI poses to ensure fair and transparent recruitment practices. In conclusion, AI has the potential to revolutionize talent acquisition, but its success depends on thoughtful implementation and continuous evaluation to mitigate risks and maximize benefits.

show abstract

Revolutionizing Talent Acquisition in Indonesia's E-Commerce Industry: The Transformative Impact of AI and Machine Learning

Cited by 6 publications

References 29 publications

SkillSync: Evaluating Candidates for Communication and Problem-Solving Proficiency

SkillSync: Evaluating Candidates for Communication and Problem-Solving Proficiency

Landscape and challenges in economic evaluations of artificial intelligence in healthcare: a systematic review of methodology

Revolutionizing Recruitment: The Role of Artificial Intelligence in Talent Acquisition

Contact Info

Product

Resources

About