IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/9y86p.html

The adoption of technologies in The Kingdom of Saudi Arabia’s Sovereign Wealth Fund in propelling its attainment of Vision 2030 goals

Author

Listed:
  • Alqublan, Loulwa Fadel

    (Confidential Government)

Abstract

This research investigates the role of artificial intelligence (AI) and digital technologies (DTs) in the Public Investment Fund's (PIF) Vision Realisation Programme (VRP) and their impact on the Kingdom of Saudi Arabia's progress toward achieving its Vision 2030 strategy. The study employs sentiment, empirical, and semi-empirical analyses to examine the adoption of AI and DTs in the PIF's portfolio companies before and after the inception of Vision 2030. Sentiment analysis is utilised to textually analyse the profiles of PIF's portfolio companies in both periods. Empirical analysis reveals a statistically significant difference in the adoption of AI and DT terminologies. Where empirical evidence was implausible to obtain due to data limitations, semi-empirical analysis is employed, yielding results consistent with the study's hypothesis. This paper extends its focus to the macroeconomic level, demonstrating a positive impact of AI and DTs on the Kingdom of Saudi Arabia’s macroeconomic indicators. Notably, the study challenges existing literature by revealing that AI adoption does not negatively affect employment, providing a novel insight on the relationship between AI and the labour force. This departure from previous literature emphasises the need for further exploration of AI's implications on employment. This study’s key findings align with existing literature on sovereign wealth funds (SWFs), affirming that integrating AI and DTs enhances investment outcomes. While existing literature employs qualitative assessments, this research fills a substantial gap by offering a country-specific empirical analysis of the impact of the PIF on the country’s macroeconomy. The study provides structured analyses, contributing in-depth knowledge on various aspects of broader debates on AI and DT adoption. The inclusive conceptual framework presented in this research suggests avenues for future research and diverse applications across countries.

Suggested Citation

  • Alqublan, Loulwa Fadel, 2023. "The adoption of technologies in The Kingdom of Saudi Arabia’s Sovereign Wealth Fund in propelling its attainment of Vision 2030 goals," OSF Preprints 9y86p, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:9y86p
    DOI: 10.31219/osf.io/9y86p
    as

    Download full text from publisher

    File URL: https://osf.io/download/6591aad4f31e13650182de0f/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/9y86p?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiang, Kai & Xin, Baogui & Santibanez Gonzalez, Ernesto D.R., 2025. "Can industrial intelligence promote net-zero development? An analysis of resource dependence," The North American Journal of Economics and Finance, Elsevier, vol. 78(C).
    2. Dr. Chris Daniel Wong & Dr. Nicole Foo & Dr. Stephen T. Homer & Dr. Chua Keng Soon & Dr. Soon Ee Hooi, 2025. "AI Unlocking the Potential of NGOs," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(7), pages 5184-5197, July.
    3. repec:rjr:romjef:v::y:2025:i:3:p:5-23 is not listed on IDEAS
    4. Maryna Henrysson & Ranjula Bali Swain & Ashok Swain & Francesco Fuso Nerini, 2024. "Sustainable Development Goals and wellbeing for resilient societies: shocks and recovery," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    5. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    6. Xi Liu & Yugang He & Renhong Wu, 2024. "Revolutionizing Environmental Sustainability: The Role of Renewable Energy Consumption and Environmental Technologies in OECD Countries," Energies, MDPI, vol. 17(2), pages 1-21, January.
    7. Aurélie Halsband, 2022. "Sustainable AI and Intergenerational Justice," Sustainability, MDPI, vol. 14(7), pages 1-11, March.
    8. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    9. Stéphanie Camaréna, 2021. "Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    10. Simon Ofori Ametepey & Clinton Aigbavboa & Wellington Didibhuku Thwala & Hutton Addy, 2024. "The Impact of AI in Sustainable Development Goal Implementation: A Delphi Study," Sustainability, MDPI, vol. 16(9), pages 1-76, May.
    11. Venkat Ram Reddy Ganuthula, 2025. "AI-enabled individual entrepreneurship theory: redefining scale, capability, and sustainability in the digital age," Journal of Innovation and Entrepreneurship, Springer, vol. 14(1), pages 1-21, December.
    12. Jinyi Li & Zhen Liu & Guizhong Han & Peter Demian & Mohamed Osmani, 2024. "The Relationship Between Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies for Sustainable Building in the Context of Smart Cities," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    13. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    14. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    15. Lee, Chien-Chiang & Zou, Jinyang & Chen, Pei-Fen, 2025. "The impact of artificial intelligence on the energy consumption of corporations: The role of human capital," Energy Economics, Elsevier, vol. 143(C).
    16. Raghu Raman & Ricardo Vinuesa & Prema Nedungadi, 2021. "Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    17. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).
    18. Martins, Flavio Pinheiro & De-León Almaraz, Sofía & Botelho Junior, Amilton Barbosa & Azzaro-Pantel, Catherine & Parikh, Priti, 2024. "Hydrogen and the sustainable development goals: Synergies and trade-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    19. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    20. Raluca-Giorgiana (Chivu) Popa & Ionuț-Claudiu Popa & David-Florin Ciocodeică & Horia Mihălcescu, 2025. "Modeling AI Adoption in SMEs for Sustainable Innovation: A PLS-SEM Approach Integrating TAM, UTAUT2, and Contextual Drivers," Sustainability, MDPI, vol. 17(15), pages 1-17, July.
    21. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:9y86p. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.