📈 economics

Unlocking Artificial Intelligence Driven Perceived Business Growth Through Organizational Readiness and Employee Development in Saudi Enterprises

Drawing on the Resource-Based View and Technology–Organization–Environment frameworks, this study of Saudi enterprises demonstrates that Artificial Intelligence adoption drives perceived business growth primarily through the mediating role of organizational readiness and sustainable employee development, thereby aligning digital transformation with key Sustainable Development Goals.

Original authors: Hashed Mabkhot, Anfal Alduhailan, Ammar Mabkhot

Published 2026-10-09

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CC BY 4.0

Original authors: Hashed Mabkhot, Anfal Alduhailan, Ammar Mabkhot

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

In the modern business world, technology is often viewed as a standalone solution, a tool that can be switched on to instantly improve efficiency and profit. Yet, the most successful organizations understand that technology does not operate in a vacuum. It requires a foundation of preparedness—the right leadership, financial backing, and a culture that embraces change—and it demands a workforce capable of wielding these new tools. This interplay between the machine and the human is at the heart of a growing field of study that examines how artificial intelligence transforms companies. The core question is not merely whether a company buys the software, but whether it builds the environment and trains the people necessary to make that software work. When a business invests in artificial intelligence, it is essentially betting on a future where human skills and digital capabilities grow together, creating a competitive edge that is difficult for others to copy.

Researchers in Saudi Arabia recently set out to understand exactly how this process works in practice, specifically within the rapidly evolving economic landscape of their country. They focused on a specific chain of events: how the adoption of artificial intelligence and the readiness of an organization to handle it lead to actual business growth. Crucially, they investigated whether the development of employees acts as the missing link in this chain. The study, conducted across public and private sectors in the Eastern Province of Saudi Arabia, surveyed 250 employees and managers. These participants came from diverse industries, including education, oil and gas, and government services, and represented a mix of experience levels, with a significant portion holding advanced degrees and over fifteen years of professional experience. The goal was to move beyond simple assumptions and measure the real-world connections between buying technology, preparing the company, training the staff, and seeing the business grow.

The investigation revealed a clear and powerful story about how these elements fit together. The researchers found that when a company adopts artificial intelligence, it directly boosts the perception of business growth. This makes sense, as these tools help streamline operations and improve decision-making. However, the study showed that the story does not end there. The act of adopting these advanced systems also forces a change in the workforce. As machines take over routine tasks, employees are compelled to learn new skills, such as data analysis and complex problem-solving. This shift creates a direct demand for employee development. The data showed that organizations that actively use artificial intelligence also tend to invest more heavily in training their people, creating a cycle where technology drives learning, and learning, in turn, drives better use of technology.

Perhaps the most significant finding was the role of the organization itself. A company cannot simply buy software and expect results; it must be ready. This readiness involves having strong leadership support, adequate financial resources, and a culture that is open to change. The study confirmed that organizations with high levels of readiness not only grow faster but also create an environment where employees are more likely to receive training and develop their skills. In fact, the research demonstrated that employee development acts as a vital bridge. It is the pathway through which both the adoption of technology and the readiness of the organization translate into tangible business growth. Without this human element, the potential of the technology remains untapped. The study suggests that the most successful growth comes from a combination of all three factors: the technology, the organizational support, and the continuous upskilling of the workforce.

The researchers concluded that for businesses in Saudi Arabia, and likely elsewhere, the path to sustainable growth is not a straight line from investment to profit. Instead, it is a synergistic process where technological assets and human capabilities reinforce each other. The data indicated that while the direct impact of technology is strong, the indirect impact through employee development is equally critical. This means that a company that invests in artificial intelligence but neglects to train its people will not see the full benefits. Conversely, a company that prepares its organization and invests in its people creates a fertile ground where technology can flourish. The study aligns with broader global goals for decent work and economic growth, suggesting that the future of business lies in augmenting human potential rather than replacing it. By understanding that technology, readiness, and people are inextricably linked, leaders can build organizations that are not only efficient but also resilient and ready for the future.

Technical Summary: Unlocking Artificial Intelligence Driven Perceived Business Growth Through Organizational Readiness and Employee Development in Saudi Enterprises

Problem Statement
While Artificial Intelligence (AI) is recognized as a strategic asset capable of transforming operational processes and competitive advantage, existing literature often treats AI adoption, organizational readiness, employee development, and business performance as isolated relationships. A significant gap exists in understanding how these factors interact within an integrated framework, particularly in emerging digital economies like Saudi Arabia. Specifically, the mediating mechanism of employee development between AI adoption/organizational readiness and Perceived Business Growth (PBG) remains insufficiently explicated. Furthermore, there is a need to align technological transformation with Sustainable Development Goals (SDGs), specifically SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure), to ensure that AI implementation supports human capital sustainability rather than causing skill obsolescence.

Methodology
This study employs a quantitative, cross-sectional research design to investigate structural relationships among AI Adoption, Organizational Readiness for AI, Employee Development, and PBG within Saudi enterprises.

Sample: The study utilized a non-probability convenience sampling technique targeting operational and managerial staff in public and private sector organizations in the Eastern Province of Saudi Arabia. The final analytical sample consisted of 250 valid responses.
Measures: Data were collected using a five-point Likert scale. Constructs were measured via adapted multi-item scales: AI Adoption (5 items), Organizational Readiness (6 items), Employee Development (6 items), and PBG (7 items).
Analysis: The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The analysis followed a two-stage approach: first evaluating the measurement model for reliability and validity (Cronbach's alpha, Composite Reliability, Average Variance Extracted, and HTMT ratios for discriminant validity), and second, assessing the structural model using bootstrapping (5,000 resamples) to test direct and indirect hypotheses. Common Method Bias (CMB) was assessed via Variance Inflation Factor (VIF) values.

Key Results
The empirical analysis, based on an integrated Resource-Based View (RBV) and Technology–Organization–Environment (TOE) framework, yielded the following findings:

Model Fit and Variance: The structural model demonstrated strong explanatory power, with the predictors collectively accounting for 81.9% of the variance in Perceived Business Growth ( $R^2 = 0.819$ ) and 51.0% of the variance in Employee Development ( $R^2 = 0.510$ ).
Direct Relationships: All five direct hypotheses were supported ( $p < 0.05$ $p < 0.05$ ):
- AI Adoption has a strong positive effect on PBG ( $\beta = 0.712$ ) and Employee Development ( $\beta = 0.613$ ).
- Employee Development has a positive effect on PBG ( $\beta = 0.175$ ).
- Organizational Readiness for AI positively affects PBG ( $\beta = 0.136$ ) and Employee Development ( $\beta = 0.205$ ).
Mediation Effects: Employee Development was identified as a complementary partial mediator in two key pathways:
- Between Organizational Readiness and PBG ( $\beta = 0.036, p = 0.032$ ).
- Between AI Adoption and PBG ( $\beta = 0.107, p = 0.002$ ).
Effect Sizes: AI Adoption exerted a very large effect on PBG ( $f^2 = 1.459$ ) and a large effect on Employee Development ( $f^2 = 0.666$ ). Organizational Readiness showed small effect sizes on both Employee Development ( $f^2 = 0.074$ ) and PBG ( $f^2 = 0.083$ ).

Key Contributions

Theoretical Integration: The study extends the RBV–TOE perspective by integrating technological assets, organizational context, and human-capability factors into a single explanatory model. It posits that while TOE explains the contextual capacity to absorb AI, RBV explains how these integrated resources transform into business value through human capital.
Mediating Mechanism: The research explicitly identifies Employee Development as a critical human-capital pathway that links AI adoption and organizational readiness to business growth, addressing the gap regarding how technological investments translate into perceived organizational value.
Contextual Relevance: By focusing on Saudi enterprises, the study provides empirical evidence within the context of Saudi Vision 2030, demonstrating how digital transformation aligns with national economic goals.

Significance and Claims
The authors claim that the study confirms AI adoption, organizational readiness, and employee development are synergistically bound in driving perceived business growth. The findings suggest that realizing value from AI depends not merely on acquiring technological assets but on building supportive organizational contexts and strengthening human capabilities.

Strategic Implication: The study highlights the necessity of combining AI investment with organizational readiness and continuous workforce upskilling. It argues that investing in AI infrastructure without parallel investment in digital culture and employee skills will prevent optimal enterprise development and undermine sustainable workplace transformations.
Sustainability Alignment: By framing digital transformation within SDG 8 and SDG 9, the study asserts that workforce augmentation ensures technological progress supports inclusive, resilient, and sustainable economic growth rather than leading to skill obsolescence.
Limitations: The authors modestly note that the cross-sectional design limits causal inference and that the use of self-reported data for PBG may introduce subjective bias. They suggest future research should employ longitudinal designs, probability sampling across diverse regions, and objective financial metrics.

Technical Summary: Unlocking Artificial Intelligence Driven Perceived Business Growth Through Organizational Readiness and Employee Development in Saudi Enterprises

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