Impact of Artificial Intelligence (AI) Towards the Quantity Surveying (QS) Professions: A Systematic Review
Abstract
Artificial intelligence (AI) is a key driving force of the fourth technology revolution, and it has become a trend in a variety of professional industries, including the construction sector like BIM. The emergence of ChatGPT has led to numerous research investigating the possibility that using AI chatbots in the workplace will be more productive. Nevertheless, there have been limited studies and no holistic understanding of the feasibility of the new and emerging AI technology in the Quantity surveying (QS) industry. With an assistance of AI chatbot, the role of QS will have significant changes. This research aims to review the existing research on the impacts of AI on QS and if it will eliminate the need for QS. Eighteen (18) relevant journal papers were carefully selected using the PRISMA statement. A thematic analysis was carried out to determine the relevant topic's themes and sub-themes. This study presents three (3) major themes: types, limitations, and impacts, followed by twenty-one (21) sub-themes. The research findings suggest that while AI chatbots have the potential to influence the QS professions, the specific nature and significance of these impacts remain uncertain, warranting further investigation.
References
Abioye, S. O., Oyedele, L. O., Akanbi, L., Ajayi, A., Davila Delgado, J. M., Bilal, M., Akinade, O. O., & Ahmed, A. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44. https://doi.org/https://doi.org/10.1016/j.jobe.2021.103299
Adamska, B.A., Blahak, D., & Abanda, F.H. (2020). Blockchain in construction practice. Collaboration and integration in construction, engineering, management and technology, 339-343. https://doi.org/10.1007/978-3-030-48465-1_57
Chen, X., Chang-Richards, A. Y., Pelosi, A., Jia, Y., Shen, X., Siddiqui, M. K., & Yang, N. (2022). Implementation of technologies in the construction industry: a systematic review. Engineering, Construction and Architectural Management, 29(8). https://www.emerald.com/insight/content/doi/10.1108/ECAM-02-2021-0172/full/html
Digwatch. (2023, Nov 15). What’s the future of AI services? https://dig.watch/updates/whats-the-future-of-ai-services
Emaminejad, N., & Akhavian, R. (2022). Trustworthy AI and robotics: Implications for the AEC industry. Automation in Construction, 139. https://www.sciencedirect.com/science/article/pii/S0926580522001716
Fan, X., & Li, J. (2023). Artificial Intelligence-Driven Interactive Learning Methods for Enhancing Art and Design Education in Higher Institutions. Applied Artificial Intelligence, 37(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2023.2225907
Gu, T.T., Zhang, S.F., & Cai, R.R. (2022). Can Artificial Intelligence Boost Employment in Service Industries? Empirical Analysis Based on China. Applied Artificial Intelligence, 36(1), 1080-1097. https://doi.org/10.1080/08839514.2022.2080336
Gupta, A., Hathwar, D., & Vijayakumar, A. (2020). Introduction to AI Chatbots. International Journal of Engineering Research & Technology (IJERT), 9(07), 255-258. https://www.researchgate.net/publication/342880348_Introduction_to_AI_Chatbots
Heo, S., Han, S., Shin, Y., & Na, S. (2021). Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry. Applied Sciences, 11(22). https://www.mdpi.com/2076-3417/11/22/10919
Khalef, R., & El-adaway, I.H. (2021). Automated identification of substantial changes in construction projects of airport improvement program: Machine learning and natural language processing comparative analysis. Journal of Management in Engineering, 37(6). https://doi.org/10.1061/(ASCE)ME.1943-5479.0000959
Khodabakhshian, A., Puolitaival, T., & Kestle, L. (2023). Deterministic and Probabilistic Risk Management Approaches in Construction Projects: A Systematic Literature Review and Comparative Analysis. Buildings, 13(15). https://www.mdpi.com/2075-5309/13/5/1312
Kor, M., Yitmen, I., & Alizadehsalehi, S. (2023). An investigation for integration of deep learning and digital twins towards Construction 4.0. Smart and Sustainable Built Environment, 12(3). https://www.emerald.com/insight/content/doi/10.1108/SASBE-08-2021-0148/full/html
Maphosa, V., & Maphosa, M. (2023). Artificial intelligence in higher education: a bibliometric analysis and topic modeling approach. Applied Artificial Intelligence, 37(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2023.2261730
Mengist, W., Soromessa, T., & Legese, G. (2020). Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX, 7, 1-11. https://www.sciencedirect.com/science/article/pii/S221501611930353X
Mironova, L.I., Fomin, N.I., & Vilisova, A.D. (2021). Issues of invention in the construction sector in conditions of its digitalization. Russian Journal of Construction Science and Technology, 7(2). https://elar.urfu.ru/bitstream/10995/114748/1/rjcst-2021-2-05.pdf
Momade, M. H., Durdyev, S., Estrella, D., & Ismail, S. (2021). Systematic review of application of artificial intelligence tools in architectural, engineering and construction. Frontiers in Engineering and Built Environment, 1(2). https://www.emerald.com/insight/content/doi/10.1108/FEBE-07-2021-0036/full/html
Mustapa, M., Nurhuda, S., & Wahid, A. (2006, Jun 21-25). Bills of Quantities - Are They Still Useful and Relevant Today? [Paper Presentation]. International Conference on Construction Industry, Padang, Indonesia.
https://www.researchgate.net/publication/237112437
Olatunde, N. A., Gento, A. M., Okorie, V. N., Oyewo, O. W., Mewomo, M. C., & Awodele, I. A. (2023). Construction 4.0 technologies in a developing economy: awareness, adoption readiness and challenges. Frontiers in Engineering and Built Environment, 3(2). https://www.emerald.com/insight/content/doi/10.1108/FEBE-08-2022-0037/full/html
Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial Intelligence and Human Resources Management: A Bibliometric Analysis. Applied Artificial Intelligence, 36(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2022.2145631
Rampini, L., & Cecconi, F.R. (2022). Artificial intelligence algorithms to predict Italian real estate market prices. Journal of Property Investment & Finance, 40(6). https://www.emerald.com/insight/content/doi/10.1108/JPIF-08-2021-0073/full/html
RISM. (n.d.). Quantity Surveying Division (QS). https://rism.org.my/quantity-surveying-division-qs/
Rahmani, F.M., & Zohuri, B. (2024). Artificial Intelligence at Work: Transforming Industries and Redefining the Workforce Landscape. Journal of Economics and Management Research, 5(2), 1-4. https://www.researchgate.net/publication/378393032_Artificial_Intelligence_at_Work_Transforming_Industries_and_Redefining_the_Workforce_Landscape
SC Quantity Surveyors. (n.d.). Procurement. https://www.scquantitysurveyors.com/services/procurement/
Sierra-Correa, P., & Kintz, J. R. C. (2015). Ecosystem-based adaptation for improving coastal planning for sea-level rise: A systematic review for mangrove coasts. Marine Policy, 51, 385-393. https://www.sciencedirect.com/science/article/pii/S0308597X14002462
Singh, A., Dwivedi, A., Agrawal, D., & Singh, D. (2023). Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability. Operations Management Research, 16, 1667-1683. https://link.springer.com/article/10.1007/s12063-022-00344-x
Ting, S.-H., Ng, Y.-J., & Neelam, M. (2021). Neelam MahaLakshmi (2021) Aspects of Artificial Intelligence in Karthikeyan. 250-256. https://www.researchgate.net/publication/358119068
Tjebane, M. M., Musonda, I., & Okoro, C. (2022). Organisational Factors of Artificial Intelligence Adoption in the South African Construction Industry. Frontiers in Built Environment, 8, 1-17. https://doi.org/10.3389/fbuil.2022.823998
Wao, J. O. (2015). Predicting the Future of Quantity Surveying Profession in the Construction Industry. Journal of Construction Project Management and Innovation, 5 (2). https://www.researchgate.net/publication/295147875
Waqar, A., Andri, Qureshi, A. H., Almujibah, H. R., Tanjung, L. E., & Utami, C. (2023). Evaluation of success factors of utilizing AI in digital transformation of health and safety management systems in modern construction projects. Ain Shams Engineering Journal, 14(11). https://www.sciencedirect.com/science/article/pii/S2090447923004409
Xu, Z. (2022). Human Judges in the Era of Artificial Intelligence: Challenges and Opportunities. Applied Artificial Intelligence, 36(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2021.2013652
Adamska, B.A., Blahak, D., & Abanda, F.H. (2020). Blockchain in construction practice. Collaboration and integration in construction, engineering, management and technology, 339-343. https://doi.org/10.1007/978-3-030-48465-1_57
Chen, X., Chang-Richards, A. Y., Pelosi, A., Jia, Y., Shen, X., Siddiqui, M. K., & Yang, N. (2022). Implementation of technologies in the construction industry: a systematic review. Engineering, Construction and Architectural Management, 29(8). https://www.emerald.com/insight/content/doi/10.1108/ECAM-02-2021-0172/full/html
Digwatch. (2023, Nov 15). What’s the future of AI services? https://dig.watch/updates/whats-the-future-of-ai-services
Emaminejad, N., & Akhavian, R. (2022). Trustworthy AI and robotics: Implications for the AEC industry. Automation in Construction, 139. https://www.sciencedirect.com/science/article/pii/S0926580522001716
Fan, X., & Li, J. (2023). Artificial Intelligence-Driven Interactive Learning Methods for Enhancing Art and Design Education in Higher Institutions. Applied Artificial Intelligence, 37(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2023.2225907
Gu, T.T., Zhang, S.F., & Cai, R.R. (2022). Can Artificial Intelligence Boost Employment in Service Industries? Empirical Analysis Based on China. Applied Artificial Intelligence, 36(1), 1080-1097. https://doi.org/10.1080/08839514.2022.2080336
Gupta, A., Hathwar, D., & Vijayakumar, A. (2020). Introduction to AI Chatbots. International Journal of Engineering Research & Technology (IJERT), 9(07), 255-258. https://www.researchgate.net/publication/342880348_Introduction_to_AI_Chatbots
Heo, S., Han, S., Shin, Y., & Na, S. (2021). Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry. Applied Sciences, 11(22). https://www.mdpi.com/2076-3417/11/22/10919
Khalef, R., & El-adaway, I.H. (2021). Automated identification of substantial changes in construction projects of airport improvement program: Machine learning and natural language processing comparative analysis. Journal of Management in Engineering, 37(6). https://doi.org/10.1061/(ASCE)ME.1943-5479.0000959
Khodabakhshian, A., Puolitaival, T., & Kestle, L. (2023). Deterministic and Probabilistic Risk Management Approaches in Construction Projects: A Systematic Literature Review and Comparative Analysis. Buildings, 13(15). https://www.mdpi.com/2075-5309/13/5/1312
Kor, M., Yitmen, I., & Alizadehsalehi, S. (2023). An investigation for integration of deep learning and digital twins towards Construction 4.0. Smart and Sustainable Built Environment, 12(3). https://www.emerald.com/insight/content/doi/10.1108/SASBE-08-2021-0148/full/html
Maphosa, V., & Maphosa, M. (2023). Artificial intelligence in higher education: a bibliometric analysis and topic modeling approach. Applied Artificial Intelligence, 37(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2023.2261730
Mengist, W., Soromessa, T., & Legese, G. (2020). Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX, 7, 1-11. https://www.sciencedirect.com/science/article/pii/S221501611930353X
Mironova, L.I., Fomin, N.I., & Vilisova, A.D. (2021). Issues of invention in the construction sector in conditions of its digitalization. Russian Journal of Construction Science and Technology, 7(2). https://elar.urfu.ru/bitstream/10995/114748/1/rjcst-2021-2-05.pdf
Momade, M. H., Durdyev, S., Estrella, D., & Ismail, S. (2021). Systematic review of application of artificial intelligence tools in architectural, engineering and construction. Frontiers in Engineering and Built Environment, 1(2). https://www.emerald.com/insight/content/doi/10.1108/FEBE-07-2021-0036/full/html
Mustapa, M., Nurhuda, S., & Wahid, A. (2006, Jun 21-25). Bills of Quantities - Are They Still Useful and Relevant Today? [Paper Presentation]. International Conference on Construction Industry, Padang, Indonesia.
https://www.researchgate.net/publication/237112437
Olatunde, N. A., Gento, A. M., Okorie, V. N., Oyewo, O. W., Mewomo, M. C., & Awodele, I. A. (2023). Construction 4.0 technologies in a developing economy: awareness, adoption readiness and challenges. Frontiers in Engineering and Built Environment, 3(2). https://www.emerald.com/insight/content/doi/10.1108/FEBE-08-2022-0037/full/html
Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial Intelligence and Human Resources Management: A Bibliometric Analysis. Applied Artificial Intelligence, 36(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2022.2145631
Rampini, L., & Cecconi, F.R. (2022). Artificial intelligence algorithms to predict Italian real estate market prices. Journal of Property Investment & Finance, 40(6). https://www.emerald.com/insight/content/doi/10.1108/JPIF-08-2021-0073/full/html
RISM. (n.d.). Quantity Surveying Division (QS). https://rism.org.my/quantity-surveying-division-qs/
Rahmani, F.M., & Zohuri, B. (2024). Artificial Intelligence at Work: Transforming Industries and Redefining the Workforce Landscape. Journal of Economics and Management Research, 5(2), 1-4. https://www.researchgate.net/publication/378393032_Artificial_Intelligence_at_Work_Transforming_Industries_and_Redefining_the_Workforce_Landscape
SC Quantity Surveyors. (n.d.). Procurement. https://www.scquantitysurveyors.com/services/procurement/
Sierra-Correa, P., & Kintz, J. R. C. (2015). Ecosystem-based adaptation for improving coastal planning for sea-level rise: A systematic review for mangrove coasts. Marine Policy, 51, 385-393. https://www.sciencedirect.com/science/article/pii/S0308597X14002462
Singh, A., Dwivedi, A., Agrawal, D., & Singh, D. (2023). Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability. Operations Management Research, 16, 1667-1683. https://link.springer.com/article/10.1007/s12063-022-00344-x
Ting, S.-H., Ng, Y.-J., & Neelam, M. (2021). Neelam MahaLakshmi (2021) Aspects of Artificial Intelligence in Karthikeyan. 250-256. https://www.researchgate.net/publication/358119068
Tjebane, M. M., Musonda, I., & Okoro, C. (2022). Organisational Factors of Artificial Intelligence Adoption in the South African Construction Industry. Frontiers in Built Environment, 8, 1-17. https://doi.org/10.3389/fbuil.2022.823998
Wao, J. O. (2015). Predicting the Future of Quantity Surveying Profession in the Construction Industry. Journal of Construction Project Management and Innovation, 5 (2). https://www.researchgate.net/publication/295147875
Waqar, A., Andri, Qureshi, A. H., Almujibah, H. R., Tanjung, L. E., & Utami, C. (2023). Evaluation of success factors of utilizing AI in digital transformation of health and safety management systems in modern construction projects. Ain Shams Engineering Journal, 14(11). https://www.sciencedirect.com/science/article/pii/S2090447923004409
Xu, Z. (2022). Human Judges in the Era of Artificial Intelligence: Challenges and Opportunities. Applied Artificial Intelligence, 36(1). https://www.tandfonline.com/doi/full/10.1080/08839514.2021.2013652
Published
2024-11-01
How to Cite
ZHI XIN, Ng; FOO YEU, Wong; YEE LIN, Lee.
Impact of Artificial Intelligence (AI) Towards the Quantity Surveying (QS) Professions: A Systematic Review.
International Journal of Business and Technology Management, [S.l.], v. 6, n. S2, p. 212-226, nov. 2024.
ISSN 2682-7646.
Available at: <https://myjms.mohe.gov.my/index.php/ijbtm/article/view/27928>. Date accessed: 05 dec. 2024.
Issue
Section
English Section
