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Awareness of AI both unnerves and energises creative workers: employees who notice AI report greater job insecurity but also higher engagement, and engagement—rather than insecurity—most strongly predicts higher self-rated performance, suggesting net productivity effects depend on whether engagement gains outweigh insecurity losses.

Artficial Intelligence and Creative Worker In Indonesia: The Double Edge Sword Effect

Daini Unifianto Fauzi, Riani Rachmawati · August 11, 2026 · Bulletin of Social Studies and Community Development

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In a cross-sectional survey of 227 Indonesian creative workers, greater AI awareness is associated with higher job insecurity and higher work engagement; engagement strongly predicts self-rated performance and mediates a positive AI→performance link while job insecurity negatively mediates AI→engagement.

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The increasing adoption of artificial intelligence (AI) in the workplace has raised concerns about its implications for employees, particularly creative workers, who are considered vulnerable to technological disruption. This study aimed to examine the influence of AI awareness on individual work performance, mediated by job insecurity and work engagement, among creative workers in Indonesia. A quantitative approach was employed through a cross-sectional survey of 227 creative workers from various creative occupations in Indonesia using a structured questionnaire. Data were analyzed using Structural Equation Modeling (SEM) with LISREL version 8.80 to examine both direct and indirect relationships among the proposed variables. The findings revealed that AI awareness positively affected job insecurity (β = 0.62, t = 7.95) and work engagement (β = 0.23, t = 2.42), while job insecurity negatively influenced work engagement (β = −0.26, t = −2.81). Furthermore, work engagement positively affected individual work performance (β = 0.72, t = 7.56). Work engagement significantly mediated the relationship between AI awareness and individual work performance (t = 2.21), whereas job insecurity significantly mediated the relationship between AI awareness and work engagement (t = −2.03). However, the serial mediating effect of job insecurity and work engagement on the relationship between AI awareness and individual work performance was not significant (t = −1.95). These findings indicate that creative workers perceive AI as a double-edged phenomenon: although it raises concerns regarding job continuity, it may also stimulate engagement that supports performance. By integrating the STARA awareness framework and the Job Demands–Resources theory, this study contributes to the current body of research on employees' psychological responses to AI-driven transformation. It offers practical insights to help organizations foster adaptive attitudes toward AI while maintaining employee engagement and performance amid ongoing technological transformation. Keywords: AI awareness; Job insecurity; Work engagement; Individual work performance; Creative workers.

Summary

Main Finding

AI awareness among creative workers acts as a “double-edged” stimulus: it increases job insecurity but also raises work engagement. Higher work engagement strongly predicts better individual work performance. Job insecurity reduces engagement, and it mediates (negatively) the AI awareness → engagement link; work engagement mediates (positively) the AI awareness → performance link. A serial mediation pathway (AI awareness → job insecurity → engagement → performance) was not statistically significant.

Key Points

Sample: 227 creative workers in Indonesia (various creative occupations).
Methods: Cross-sectional survey; Structural Equation Modeling (LISREL 8.80).
Direct effects (standardized β, t):
- AI awareness → Job insecurity: β = 0.62, t = 7.95 (positive, large).
- AI awareness → Work engagement: β = 0.23, t = 2.42 (positive, small–moderate).
- Job insecurity → Work engagement: β = −0.26, t = −2.81 (negative, modest).
- Work engagement → Individual work performance: β = 0.72, t = 7.56 (positive, large).
Mediation:
- Work engagement significantly mediates AI awareness → Individual performance (t = 2.21).
- Job insecurity significantly mediates AI awareness → Work engagement (t = −2.03), producing a negative indirect effect on engagement.
- Serial mediation via job insecurity then engagement on the AI awareness → performance path was not significant (t = −1.95; borderline).
Theoretical framing: STARA awareness framework and Job Demands–Resources (JD–R) theory.

Data & Methods

Design: Quantitative, cross-sectional survey of 227 Indonesian creative workers.
Measurement: Structured questionnaire capturing AI awareness, perceived job insecurity, work engagement, and individual work performance (self-report).
Analysis: Structural Equation Modeling using LISREL 8.80 to estimate direct and indirect (mediated) relationships; t-values reported for inference.
Limitations to note:
- Cross-sectional design limits causal inference.
- Single-country, sector-specific sample (creative industries in Indonesia) limits generalizability.
- Self-reported measures risk common-method bias.
- Serial mediation result was borderline (t ≈ −1.95), suggesting further study with larger/longitudinal samples is warranted.

Implications for AI Economics

Labor supply and productivity:
- AI awareness can increase worker engagement that boosts individual performance—implying potential productivity gains from AI adoption not only via automation but also via increased worker motivation when AI is perceived as enabling.
- Simultaneous increases in job insecurity can undermine engagement; net productivity effects will depend on whether engagement gains outweigh insecurity losses.
Human capital and wage dynamics:
- Firms and policymakers should incentivize complementary human-capital investments (training, reskilling) to convert AI awareness into productive engagement rather than insecurity-driven withdrawal. This affects returns to skills and future wage structure in creative occupations.
Inequality and sectoral heterogeneity:
- Creative workers perceive mixed effects; heterogeneity across occupations and skill levels may produce uneven distributional outcomes. Policymakers should monitor which subgroups face the largest insecurity-driven declines in engagement and performance.
Organizational adoption and macro outcomes:
- Organizational policies that reduce perceived job insecurity (transparent communication, participatory implementation of AI, retraining guarantees) are likely to magnify the positive engagement→performance channel and thus increase the aggregate productivity benefits of AI.
Policy recommendations:
- Invest in targeted reskilling/upskilling programs for creative sectors.
- Support transition policies (temporary income support, job-placement services) to mitigate insecurity effects that could lower engagement and productivity.
- Encourage firm-level practices that treat AI as a job-complement (augmenting creativity) rather than a pure substitute.
Research implications for AI economists:
- Need for longitudinal and experimental studies to separate causal directions (e.g., whether AI deployment raises engagement over time or only when accompanied by supportive HR practices).
- Quantify macroeconomic impact: aggregation of micro-level engagement and insecurity effects to estimate net effects on sector productivity, employment, and wage dynamics.
- Explore heterogeneity across countries, sectors, and task types to inform targeted labor-market and industrial policies.

Assessment

Paper Typecorrelational Evidence Strengthlow — All relationships are based on a single cross-sectional self-report survey (n=227) from one country and sector, so observed associations may reflect reverse causation, omitted confounders, and common-method bias rather than causal effects. Methods Rigormedium — The paper uses appropriate statistical tools (SEM) to estimate direct and indirect paths and reports effect sizes and t-values, but rigor is limited by cross-sectional design, reliance on self-reported measures, likely convenience sampling, and absence of robustness checks (e.g., alternative identification, longitudinal tests, or objective performance measures). SampleA cross-sectional survey of 227 creative-sector workers in Indonesia (various creative occupations); measures are self-reported: AI awareness, perceived job insecurity, work engagement, and individual work performance; sampling approach not specified (likely convenience or non-probability). Themeshuman_ai_collab productivity labor_markets skills_training org_design IdentificationCross-sectional observational associations estimated with Structural Equation Modeling (LISREL 8.80); mediation inferred from contemporaneous self-report variables with no exogenous variation, instruments, or longitudinal design to support causal claims. GeneralizabilitySingle-country: Indonesia, Sector-specific: creative industries only, Small sample size (n=227) limits subgroup analysis, Likely non-probability/convenience sampling (sampling frame unclear), Self-reported measures and cross-sectional design limit external and causal generalizability

Claims (8)

Claim	Direction	Outcome	Confidence & Evidence	Details
AI awareness is positively associated with perceived job insecurity among Indonesian creative workers. Automation Exposure	positive	Perceived job insecurity	Reading fidelity high Study strength medium	n=227 β = 0.62 0.3
AI awareness is positively associated with work engagement among creative workers. Worker Satisfaction	positive	Work engagement	Reading fidelity high Study strength medium	n=227 β = 0.23 0.3
Perceived job insecurity is negatively associated with work engagement. Worker Satisfaction	negative	Work engagement	Reading fidelity high Study strength medium	n=227 β = −0.26 0.3
Work engagement is strongly positively associated with individual work performance. Output Quality	positive	Individual work performance	Reading fidelity high Study strength medium	n=227 β = 0.72 0.3
Work engagement significantly mediates the positive relationship between AI awareness and individual work performance. Output Quality	positive	Individual work performance	Reading fidelity high Study strength medium	n=227 t = 2.21 0.3
Job insecurity significantly mediates the relationship between AI awareness and work engagement, producing a negative indirect effect on engagement. Worker Satisfaction	negative	Work engagement	Reading fidelity high Study strength medium	n=227 t = −2.03 0.3
The serial mediation pathway from AI awareness through job insecurity and work engagement to individual work performance is not statistically significant. Output Quality	null_result	Individual work performance	Reading fidelity high Study strength low	n=227 t = −1.95 0.15
The study suggests that AI awareness may generate simultaneous engagement-related productivity benefits and insecurity-related risks, so the net productivity effect depends on the relative strength of these channels. Developer Productivity	mixed	Individual work performance	Reading fidelity high Study strength low	n=227 0.15