The new normal: The status quo of AI adoption in SMEs

Journal of Small Business Management, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 35

Published: Aug. 13, 2024

The recent surge in the adoption of artificial intelligence (AI) by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, existing literature reveals a fragmented landscape that hinders our understanding how SMEs use AI. We address this through systematic review wherein we analyze 106 peer-reviewed articles on AI categorize states trends into eight clusters: (1) compatibility, (2) infrastructure, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, (8) ecosystem: according to technology–organization–environment model. Our provides valuable insights identifies gaps literature, notably overlooking identification as pivotal driver neglecting legal requirements. study clarifies implementation within SMEs, offering holistic theoretically grounded perspective empower researchers practitioners facilitate more effective application SME sector.

Language: Английский

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Digital Strategies for Modern Workplaces and Business Through Artificial Intelligence Techniques

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 231 - 258

Published: June 14, 2024

AI has significantly transformed human resources (HR) by enhancing recruitment, talent acquisition, employee engagement, performance management, learning, and HR analytics. This chapter explores the convergence of AI, highlighting its potential to revolutionize modern workplaces. The recruitment processes have been enhanced in strategies such as efficiently identifying top candidates mitigating unconscious bias. Automated candidate screening, scheduling interviews, answering frequently asked questions, improving experience done. personalized learning development initiatives, delivering targeted training programs, skill gaps, providing timely feedback facilitated. AI-powered systems provide real-time insights into metrics, enabling proactive feedback. By analyzing vast datasets, algorithms can identify patterns trends, facilitating data-driven decision-making evaluations goal setting.

Language: Английский

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AI Capability and Sustainable Performance: Unveiling the Mediating Effects of Organizational Creativity and Green Innovation with Knowledge Sharing Culture as a Moderator

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7466 - 7466

Published: Aug. 29, 2024

The purpose of this study is to investigate the role AI capability (AIC) on organizational creativity (OC), green innovation (GI), and sustainable performance (SP). It also aims mediating roles OC GI, as well moderating knowledge sharing culture (KNC). This used quantitative methodology utilized a survey collect data from 421 employees in different organizations Bangladesh. We structural equation modeling (SEM) technique analyze data. finds that significantly influences OC, SP. GI work mediators, KNC serves moderator among suggested relationships. notable for its novelty examining multiple unexplored aspects current body research. research provides valuable insights policymakers practitioners regarding effective integration enhance competitiveness.

Language: Английский

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Fostering sustainability through technological brilliance: a study on the nexus of organizational STARA capability, GHRM, GSCM, and sustainable performance

Discover Sustainability, Journal Year: 2024, Volume and Issue: 5(1)

Published: Oct. 14, 2024

This study aims to investigate the influence of Organizational Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA) capabilities on Green Human Resource Management (GHRM) practices, Supply Chain (GSCM) also its direct impact Sustainable Performance (SP) outcomes within manufacturing landscape Bangladesh. A quantitative approach was employed, gathering data from 395 employees in Bangladeshi sector through a survey questionnaire using seven-point Likert scale. Structural equation modeling (SEM) utilized analyze data, focusing testing hypotheses related relationships between organizational STARA capabilities, GHRM, GSCM, SP. The found positive (OSC) All were accepted, GHRM ← (β = 0.210), GSCM 0.247), SP 0.135). Additionally, it revealed that mediate relationship research contributes filling existing gap literature by providing empirical evidence integration with specifically context sector. It highlights mediating role enhancing sustainable performance capabilities. findings this offer valuable insights for organizations operating sector, suggesting strategies leveraging enhance sustainability, efficiency, competitiveness. Policymakers stakeholders can use these formulate policies initiatives promote adoption practices manufacturing.

Language: Английский

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Enhancing top managers' leadership with artificial intelligence: insights from a systematic literature review

Review of Managerial Science, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Language: Английский

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Leveraging AI in recruitment: enhancing intellectual capital through resource-based view and dynamic capability framework

Journal of Intellectual Capital, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 25, 2025

Purpose The rapid evolution of artificial intelligence (AI) is revolutionizing organizational operations and altering competitive landscapes. This study examines the influence resources on AI adoption in recruitment, focusing their role achieving advantage through effective implementation. Design/methodology/approach research utilizes a cross-sectional quantitative approach, applying partial least squares structural equation modeling (PLS-SEM) to data from 290 human resource (HR) professionals. It grounded resource-based view (RBV) dynamic capability framework (DCF). Findings results reveal that HR competencies open innovation significantly capabilities, which are essential for integration, supported by financial support information technology (IT) infrastructure. These capabilities enable adoption, leading advantage. Research limitations/implications this captures current landscape providing snapshot present scenario rapidly evolving technological environment. Practical implications offers professionals managers strategic guidance effectively integrating into recruitment processes. By enhancing competencies, fostering collaboration ensuring sufficient infrastructural support, organizations can navigate challenges secure landscape. Social reduce biases, enhance diversity improve fairness standardized assessments. However, as technologies evolve, continuous oversight ensure ethical use modify systems needed, further reducing biases addressing societal concerns AI-driven Originality/value introduces novel underscores importance expertise with advanced tools successful A key contribution not only facilitate integration but also accuracy, accountability configure most suitable collaborating developers meet specific needs organization.

Language: Английский

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Empowering human resource management through artificial intelligence: A systematic literature review and bibliometric analysis

International journal of production management and engineering, Journal Year: 2025, Volume and Issue: 13(1), P. 59 - 76

Published: Jan. 31, 2025

Drawing on a systematic literature review and bibliometric analysis, this article examines the burgeoning field of Artificial Intelligence (AI) integration into Human Resource Management (HRM) practises. By evaluating 77 selected articles from two extensive databases, Scopus Web Science, study illuminates dynamic intersection AI technologies HRM, encapsulating profound implications for organisational individual aspects HR This analysis delineates three primary thematic areas: AI's transformative role in emerging paradigm human-AI collaboration, nuanced challenges opportunities presented by research contributes to academic discourse mapping current state applications identifying gaps proposing directions future research, emphasising need ethical frameworks strategic enhance Through scholarly endeavour, we aim offer comprehensive overview that aids practitioners researchers navigating complexities reshaping HRM towards more efficient, ethical, innovative

Language: Английский

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A Bibliometric Review on the Use of Artificial Intelligence in Human Resources Management

Advances in human resources management and organizational development book series, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 46

Published: Jan. 31, 2025

This study aims to investigate studies on the use of artificial intelligence in human resources management last 10 years using bibliometric method. By searching keywords “Human Resources Management”, Resource Resources”, Resource”, “Artificial Intelligence”, “Machine Learning”, “Deep Narrow General Super “Generative Artificial AI”, and their abbreviations such as HRM, AI, so Web Science Core Collection database July 22, 2024, 47,955 scholar works have been accessed. The filtering process has yielded a data set consisting 949 publications, which analyzed analysis method by software, VOSviewer with version 1.6.20. reveals leading authors institutions significant contributions provides holistic view AI applications highlighting both opportunities challenges an interdisciplinary perspective.

Language: Английский

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Revolutionizing HRM: a review of human-robot collaboration in HRM functions and the imperative of change readiness

Business Process Management Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Purpose The purpose of the paper is to conduct a review literature on human-robot collaboration across different functions and activities human resource management (HRM) discuss its importance for change readiness in organizations. Design/methodology/approach A bibliometric analysis was conducted identify emerging research themes fields resources (HR) robotics, including readiness. Based initial results analysis, systematic subsequently performed gain more specific understanding various HRM Findings from highlight that technological progression HRM, such as AI-driven staffing training techniques, improves effectiveness personalization but raises concerns about privacy job scrutiny. AI robotics performance evaluation enhance objectivity reduce subjectivity, which can lead disengagement. Generational differences, cultural factors emotional quotient complicate adopt new technologies. emphasizes balancing with employee involvement meaningfulness ensure successful implementation engagement. Originality/value This synthesizes existing research, literature, theoretical concepts models, best practices strategies implementing functions. It highlights gaps current suggests areas future advance field HRM. By doing so, this enhances while offering practical insights essential effective management.

Language: Английский

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Challenges of Adopting Artificial Technology in Human Resource Management Practices

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 81 - 102

Published: Feb. 21, 2025

In this study, the challenges faced by organisations in integrating artificial intelligence (AI) into human resource management (HRM) practises are examined. For that, AI can bring significant benefits, including increasing efficiency and decision-making HR processes, namely recruitment, performance evaluation talent development. Its adoption, however, presents many technological infrastructure, data privacy, ethical, organizational culture. This chapter investigates these barriers, particularly importance of proper changes trade-off between element AI's capabilities. The article discusses strategies for overcoming challenges, practising ethical AI, security employee study offers actionable insights attempting to leverage HRM a way that succeed at both operational dimensions.

Language: Английский

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