Evidence map›Paper›PMID 41310126›Full record

ArticleScientific reports2025

AI-Savvy leadership for enhancing AI utilization and employee engagement among digital natives in the EdTech sector.

Majdi Anwar Quttainah, Priyanka Sadhna, Arun Aggarwal, Pratima Daipuria, Bhavna Bhardwaj, Ishani Sharma

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Majdi Anwar QuttainahCollege of Business Administration, Kuwait University, Kuwait City, Kuwait.ORCID 0000-0002-6280-1060
Priyanka SadhnaGL Bajaj Institute of Management & Research, Greater Noida, Uttar Pradesh, India.ORCID 0000-0002-8068-5083
Arun AggarwalChitkara Business School, Chitkara University, Rajpura, Punjab, India. arunaggarwal.mba@gmail.com.ORCID 0000-0003-3986-188X
Pratima DaipuriaJagan Institute of Management Studies, Delhi, India.ORCID 0000-0002-0289-4373
Bhavna BhardwajGL Bajaj Institute of Management & Research, Greater Noida, Uttar Pradesh, India.
Ishani SharmaChitkara Business School, Chitkara University, Rajpura, Punjab, India.ORCID 0009-0009-3439-5980

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study aims to examine the impact of artificial intelligence (AI)-savvy leadership on employee engagement in the education technology (EdTech) sector, with a specific focus on digital natives. It also explores the mediating role of AI utilization in this relationship, providing insights into fostering employee engagement through technology-driven leadership in contemporary workplaces. A quantitative approach was employed, collecting data from 281 digital natives working in EdTech companies in Delhi NCR, India. Using a validated survey instrument, the study measured constructs including AI-savvy leadership, AI utilization, and employee engagement. The data were analyzed using structural equation modeling (SEM) to test the hypothesized relationships and evaluate mediation effects. The results reveal that AI-savvy leadership positively influences AI utilization at work (β = 0.504, t = 11.332, p < 0.05), having effect size of 0.349; AI utilization at work positively influences employee engagement (β = 0.299, t = 4.451, p < 0.05), having an effect size of 0.079. AI utilization fully mediates the relationship between AI-savvy leadership and employee engagement. The study unfolds no influence of AI-savvy leadership on employee engagement; these findings highlight the pivotal role of leadership in facilitating effective AI integration and addressing the engagement challenges of digital natives in technology-driven workplaces. This study contributes to the emerging literature on AI-savvy leadership by integrating the Technology Acceptance Model (TAM) and JD-R theory. It emphasizes the necessity of strategic leadership in aligning AI capabilities with organizational goals and emerging workforce needs. The findings provide actionable insights for managers and policymakers in leveraging AI to create engaging work environments, particularly for the youngest demographic cohort in the workforce.

Indexed as

Artificial IntelligenceLeadershipWork EngagementAdultFemaleHumansIndiaMaleMiddle AgedSurveys and QuestionnairesWorkplaceAI savvy leadershipAI utilizationArtificial intelligence (AI)Digital nativesEdtechEmployee engagement

Identifiers

PMID41310126
PMCPMC12749433

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.