Exploring the Relationship between Artificial Intelligence and Business Performance

https://doi.org/10.22146/ijccs.86697

Ninda Lutfiani(1*), Irwan Sembiring(2), Iwan Setyawan(3), Adi Setiawan(4), Untung Rahardja(5), Sulistio Sulistio(6)

(1) University of Raharja
(2) Satya Wacana Christian University
(3) Satya Wacana Christian University
(4) Satya Wacana Christian University
(5) University of Raharja
(6) University of Raharja
(*) Corresponding Author

Abstract


The integration of Artificial Intelligence (AI) into business operations has garnered significant attention due to its potential impact on business performance. However, the relationship between AI adoption and business performance remains not fully understood. This article comprehensively analyzes this relationship through three key aspects: the acceptance and implementation of AI within organizations, the impact of AI on various dimensions of business performance, and the potential challenges associated with AI adoption. In this study, we employ SmartPLS as an analytical tool to evaluate the relationships between identified factors and the impact of AI adoption on business performance. Our findings reveal that several factors influence the adoption and implementation of AI, including data availability, organizational culture, leadership support, technical expertise, and ethical considerations. Moreover, AI adoption significantly influences business performance metrics such as productivity, efficiency, revenue, and customer satisfaction. Nonetheless, challenges arising from AI adoption, including shifts in job roles, data privacy, and security concerns, also require substantial attention. In conclusion, successful AI adoption and implementation necessitate careful consideration of organizational, technical, and ethical factors. This research provides valuable insights for business leaders and researchers seeking a deeper understanding of the relationship between Artificial Intelligence and business performance.

Keywords


Artificial Intelligence; SmartPLS; Business Performance

Full Text:

PDF


References

M. Haenlein and A. Kaplan, “A brief history of artificial intelligence: On the past, present, and future of artificial intelligence,” Calif Manage Rev, 2019, doi: 10.1177/0008125619864925.

T. Davenport, A. Guha, D. Grewal, and T. Bressgott, "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, vol. 48, pp. 24-42, 2020, doi: 10.1007/s11747-019-00696-0.

M. H. Jarrahi, “Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making,” Bus Horiz, 2018, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0007681318300387

W. Ertel, Introduction to artificial intelligence. books.google.com, 2018. [Online]. Available: https://books.google.com/books?hl=en&lr=&id=geFHDwAAQBAJ&oi=fnd&pg=PR5&dq=introduction+to+artificial+intelligence&ots=3Fay87fC0s&sig=9w2YdfEPoXmfcykjanbdKIBXigs

A. I. Canhoto and F. Clear, “Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential,” Bus Horiz, 2020, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0007681319301570

A. Juliandi, "Structural equation model based partial least square SEM-PLS Menggunakan SmartPLS," Jurnal Pelatihan SEM-PLS Program Pascasarjana Universitas Batam, vol. 1617, 2018

E. Shook and M. Knickrehm, “Reworking the revolution: Are you ready to compete as intelligent technology meets human ingenuity to create the future workforce? Accenture.” 2019.

M. Chui, J. Manyika, M. Miremadi, N. Henke, R. Chung, P. Nel, and S. Malhotra, "Notes from the AI frontier: Applications and value of deep learning," McKinsey global institute discussion paper, April, 2018.

S. Ransbotham, P. Gerbert, M. Reeves, D. Kiron, and M. Spira, "Artificial intelligence in business gets real," MIT sloan management review, 2018, [Online]. Available: https://sloanreview.mit.edu/projects/artificial-intelligence-in-business-gets-real/

J. Howard, "Artificial intelligence: Implications for the future of work," American journal of industrial medicine, vol. 62, no. 11, pp. 917-926, 2019, Wiley Online Library.

L. Floridi, J. Cowls, M. Beltrametti, R. Chatila, P. Chazerand, V. Dignum, C. Luetge, R. Madelin, U. Pagallo, F. Rossi, and others, "An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations," Ethics, governance, and policies in artificial intelligence, pp. 19-39, 2021, Springer, doi: 10.1007/978-3-030-81907-1_3.

C. Pettey and R. van der Meulen, “Gartner Says Global Artificial Intelligence Business Value to Reach $1.2 Trillion in 2018,” Gartner, Apr. 25, 2018.

A. S. Rao and G. Verweij, “Sizing the prize: What’s the real value of AI for your business and how can you capitalise,” PwC Publication, PwC, 2018.

V. A. Anggraini and A. Hananto, "The role of social media marketing activities on customer equity drivers and customer loyalty," AFEBI Management and Business Review, vol. 5, no. 1, pp. 1-15, 2020, [Online]. Available: http://journal.afebi.org/index.php/ambr/article/view/299

A. Chouiekh and others, "Deep convolutional neural networks for customer churn prediction analysis," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), vol. 14, no. 1, pp. 1-16, 2020, IGI Global, [Online]. Available: https://www.igi-global.com/article/deep-convolutional-neural-networks-for-customer-churn-prediction-analysis/240241

P. M. Mah, I. Skalna, and J. Muzam, “Natural Language Processing and Artificial Intelligence for Enterprise Management in the Era of Industry 4.0,” Applied Sciences, 2022, [Online]. Available: https://www.mdpi.com/2076-3417/12/18/9207

H. Nozari, M. Fallah, H. Kazemipoor, and S. E. Najafi, "Big data analysis of IoT-based supply chain management considering FMCG industries," Бизнес-информатика, vol. 15, no. 1 (eng), pp. 78-96, 2021, [Online]. Available: https://cyberleninka.ru/article/n/big-data-analysis-of-iot-based-supply-chain-management-considering-fmcg-industries

A. A. H. Ahmadini, U. M. Modibbo, A. A. Shaikh, and I. Ali, "Multi-objective optimization modelling of sustainable green supply chain in inventory and production management," Alexandria Engineering Journal, vol. 60, no. 6, pp. 5129-5146, 2021, Elsevier, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1110016821002416

H. Fatemidokht, M. Kuchaki Rafsanjani, B. B. Gupta, and C.-H. Hsu, "Efficient and secure routing protocol based on artificial intelligence algorithms with UAV-assisted for vehicular ad hoc networks in intelligent transportation systems," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 7, pp. 4757-4769, 2021, IEEE, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9312485/

J. F. H. Jr, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications, 2021.

A. A. Khan, “The Influence of Artificial Intelligence on Improving the Talent Acquisition Processes Within an Organisation,” Available at SSRN 4191986, 2022, [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4191986

M. R. Lavery, P. Acharya, S. A. Sivo, and L. Xu, "Number of predictors and multicollinearity: What are their effects on error and bias in regression?" Communications in Statistics-Simulation and Computation, vol. 48, no. 1, pp. 27-38, 2019, Taylor & Francis, doi: 10.1080/03610918.2017.1371750.

T. J. F. H. Ramayah, J. Cheah, F. Chuah, H. Ting, and M. A. Memon, "Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0," An updated guide and practical guide to statistical analysis, 2018, Pearson Kuala Lumpur, Malaysia.



DOI: https://doi.org/10.22146/ijccs.86697

Article Metrics

Abstract views : 1 | views : 0

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2025 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Copyright of :
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing
and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs


View My Stats1
View My Stats2