IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v10y2024i12p423-444.html
   My bibliography  Save this article

AI in Decision Making: Transforming Business Strategies

Author

Listed:
  • Simon Kaggwa

    (Department of Finance, Hult International Business School, Boston, USA)

  • Tobechukwu Francisa Eleogu

    (Total Energies Marketing Nigeria PLC, Nigeria)

  • Franciscamary Okonkwo

    (Onesubsea (a SLB CCompany), Nigeria)

  • Oluwatoyin Ajoke Farayola

    (Financial Technology and Analytics Department, Naveen Jindal School of Management, Dallas, Texas, USA)

  • Prisca Ugomma Uwaoma
  • Abiodun Akinoso

    (Sheffield Hallam University, United Kingdom)

Abstract

This paper delves into the transformative impact of Artificial Intelligence (AI) on strategic business decision-making, offering a nuanced perspective on how AI is reshaping the corporate world. The primary purpose of this study is to explore the emergence and evolution of AI within the realm of business strategy, examining its role in disrupting traditional decision models and enhancing business agility. This study systematically analyzes academic and industry sources through a meticulous literature review, providing a comprehensive understanding of AI’s multifaceted role in business. The methodology adopted is a systematic literature review, which serves as a robust framework for evaluating source credibility and synthesizing insights. This approach enables a thorough examination of AI’s integration into business management, its influence on corporate performance metrics, and its potential in fostering inclusive business practices. The study also addresses the unique challenges and opportunities presented by AI in the business context. Key findings reveal that AI is not merely a technological tool but a strategic asset that significantly redefines business decision-making. The integration of AI into business strategies demonstrates substantial potential in enhancing corporate performance and promoting sustainable business practices. The study concludes that AI is a cornerstone in business evolution, offering unparalleled opportunities for innovation and efficiency. Recommendations advocate for a balanced approach to AI integration, emphasizing the need for businesses to align AI with their core values and strategic objectives. As AI continues to evolve, its role in business decision-making is expected to shape the corporate landscape significantly.

Suggested Citation

  • Simon Kaggwa & Tobechukwu Francisa Eleogu & Franciscamary Okonkwo & Oluwatoyin Ajoke Farayola & Prisca Ugomma Uwaoma & Abiodun Akinoso, 2024. "AI in Decision Making: Transforming Business Strategies," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 10(12), pages 423-444, January.
    • Handle: RePEc:bjc:journl:v:10:y:2024:i:12:p:423-444
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-10-issue-12/423-444.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrsi/articles/ai-in-decision-making-transforming-business-strategies/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fotis Kitsios & Maria Kamariotou, 2021. "Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    2. Agne Paulauskaite-Taraseviciene & Ingrida Lagzdinyte-Budnike & Lina Gaiziuniene & Vilma Sukacke & Laura Daniuseviciute-Brazaite, 2022. "Assessing Education for Sustainable Development in Engineering Study Programs: A Case of AI Ecosystem Creation," Sustainability, MDPI, vol. 14(3), pages 1-22, February.
    3. Navaneetha Krishnan Rajagopal & Naila Iqbal Qureshi & S. Durga & Edwin Hernan Ramirez Asis & Rosario Mercedes Huerta Soto & Shashi Kant Gupta & S. Deepak & Muhammad Ahmad, 2022. "Future of Business Culture: An Artificial Intelligence-Driven Digital Framework for Organization Decision-Making Process," Complexity, Hindawi, vol. 2022, pages 1-14, July.
    4. Robert Dobre & Daniel Bulin & Maria-Cristina Iorgulescu & Iulia Monica Oehler-Sincai & Olimpia State, 2020. "Artificial Intelligence Sector: The Next Technology Bubble? A Comparative Analysis with Dotcom Based on Stock Market Data," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 22(76), pages 24-37, June.
    5. Felipe Arenas-Torres & Miguel Bustamante-Ubilla & Roberto Campos-Troncoso, 2021. "The Incidence of Social Responsibility in the Adoption of Business Practices," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
    6. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," Sustainability Nexus Forum, Springer, vol. 29(3), pages 217-230, December.
    7. Amine Belhadi & Sachin Kamble & Samuel Fosso Wamba & Maciel M. Queiroz, 2022. "Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework," International Journal of Production Research, Taylor & Francis Journals, vol. 60(14), pages 4487-4507, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pascal Muam Mah, 2024. "National AI Strategies," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1196-1215.

    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. Satyabrata Aich & Ayusha Thakur & Deepanjan Nanda & Sushanta Tripathy & Hee-Cheol Kim, 2021. "Factors Affecting ESG towards Impact on Investment: A Structural Approach," Sustainability, MDPI, vol. 13(19), pages 1-14, September.
    2. Chowdhury, Soumyadeb & Ren, Shuang & Richey, Robert Glenn, 2025. "Leveraging artificial intelligence to facilitate green servitization: Resource orchestration and Re-institutionalization perspectives," International Journal of Production Economics, Elsevier, vol. 281(C).
    3. Chotia, Varun & Cheng, Yue & Agarwal, Reeti & Vishnoi, Sushant Kumar, 2024. "AI-enabled Green Business Strategy: Path to carbon neutrality via environmental performance and green process innovation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    4. Roy, Sanjit K. & Tehrani, Ali N. & Pandit, Ameet & Apostolidis, Chrysostomos & Ray, Subhasis, 2025. "AI-capable relationship marketing: Shaping the future of customer relationships," Journal of Business Research, Elsevier, vol. 192(C).
    5. Javier Cañavate & Elisa Martínez-Marroquín & Xavier Colom, 2025. "Engineering a Sustainable Future Through the Integration of Generative AI in Engineering Education," Sustainability, MDPI, vol. 17(7), pages 1-16, April.
    6. Xueyan Wang & Hong Wu & Lu Lu, 2021. "A Novel Service Provision Mode for Sustainable Development of the Telecom Industry," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
    7. Jun Cui, 2025. "The Explore of Knowledge Management Dynamic Capabilities, AI-Driven Knowledge Sharing, Knowledge-Based Organizational Support, and Organizational Learning on Job Performance: Evidence from Chinese Tec," Papers 2501.02468, arXiv.org.
    8. Felipe Arenas-Torres & Miguel Bustamante-Ubilla & Roberto Campos-Troncoso, 2021. "Diversity of the Board of Directors and Financial Performance of the Firms," Sustainability, MDPI, vol. 13(21), pages 1-11, October.
    9. Muhammad Zafar Yaqub & Abdullah Alsabban, 2023. "Industry-4.0-Enabled Digital Transformation: Prospects, Instruments, Challenges, and Implications for Business Strategies," Sustainability, MDPI, vol. 15(11), pages 1-33, May.
    10. Jiachen Li & Xiu Jin, 2024. "The Impact of Artificial Intelligence Adoption Intensity on Corporate Sustainability Performance: The Moderated Mediation Effect of Organizational Change," Sustainability, MDPI, vol. 16(21), pages 1-21, October.
    11. Paraskevi Boufounou & Magdalini Mavroudi & Kanellos Toudas & Georgios Georgakopoulos, 2022. "Digital Transformation of the Greek Banking Sector in the COVID Era," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
    12. Lijuan Wu & Shanyue Jin, 2022. "Corporate Social Responsibility and Sustainability: From a Corporate Governance Perspective," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    13. Elisa Barbieri & Luigi Capoani, 2025. "Renewable Energy, Resilience, Digitalization, and Industrial Policies in Seaborne Transport," Energies, MDPI, vol. 18(5), pages 1-28, February.
    14. Justyna Łapińska & Iwona Escher & Joanna Górka & Agata Sudolska & Paweł Brzustewicz, 2021. "Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland," Energies, MDPI, vol. 14(7), pages 1-20, April.
    15. Koliousis, Ioannis & Al-Surmi, Abdulrahman & Bashiri, Mahdi, 2024. "Artificial intelligence and policy making; can small municipalities enable digital transformation?," International Journal of Production Economics, Elsevier, vol. 274(C).
    16. Shahzad, Muhammad Farrukh & Xu, Shuo, 2024. "Antecedents of international entrepreneurship and emerging technologies help to achieve sustainable development goals: Moderating role of global mindset," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    17. Pan, Martin & Li, Daozheng & Wu, Hanrui & Lei, Pengfei, 2024. "Technological revolution and regulatory innovation: How governmental artificial intelligence adoption matters for financial regulation intensity," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    18. Ravneet Kaur & Rajesh Singh & Anita Gehlot & Neeraj Priyadarshi & Bhekisipho Twala, 2022. "Marketing Strategies 4.0: Recent Trends and Technologies in Marketing," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    19. Manikandan Rajagopal & Ramkumar Sivasakthivel, 2024. "An Empirical Framework Using Weighted Feed Forward Neural Network for Supply Chain Resilience (SCR) Strategy Selection," SN Operations Research Forum, Springer, vol. 5(2), pages 1-19, June.
    20. Talaei-Khoei, Amir & Yang, Alan T. & Masialeti, Masialeti, 2024. "How does incorporating ChatGPT within a firm reinforce agility-mediated performance? The moderating role of innovation infusion and firms’ ethical identity," Technovation, Elsevier, vol. 132(C).

    More about this item

    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:bjc:journl:v:10:y:2024:i:12:p:423-444. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrsi/ .

    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.