{"id":8306,"date":"2022-05-18T08:09:59","date_gmt":"2022-05-18T05:09:59","guid":{"rendered":"https:\/\/blogit.lab.fi\/labfocus\/?p=8306"},"modified":"2022-05-18T08:10:00","modified_gmt":"2022-05-18T05:10:00","slug":"global-construction-and-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/blogit.lab.fi\/labfocus\/en\/global-construction-and-artificial-intelligence\/","title":{"rendered":"Global construction and artificial intelligence"},"content":{"rendered":"\n

Global construction and development industry is facing one of its greatest challenges yet \u2013 the emergence of cognitive technologies. How are leaders equipped to manage the adoption of AI, in what is known to be one of the most anti-change industries?<\/p>\n\n\n\n

\"\"
Image 1. The emergence of cognitive technologies means a global challenge. (MacKenzie 2018)<\/figcaption><\/figure>\n\n\n\n

As part of master\u2019s thesis <\/a>a worldwide sample of over 1200 construction and development business executives were approached with a survey regarding the joint role of artificial intelligence and leadership. A grand total of 54 respondents replied, from 24 countries \u2012 all members of upper management.<\/a> The coverage of the research was up to 0,56 percent of the global residential construction market when measured in raw revenue exposure \u2013 the combined annual revenues of participating companies were from 14.9 to 24.6 billion USD altogether. From these respondents, 79.6% were active users of AI \u2013 some examples of these use cases were business strategy, human relations, construction site and safety related issues (Kirjalainen 2022, 69\u201270).<\/a>\u00a0<\/p>\n\n\n\n

The survey was ensued by empirical research, then complemented by semi-structured interviews with some of the said executives. Similarly, corresponding set of interviews was conducted with AI and engineering experts from Aalto University, University of Helsinki, VTT Technical Research Centre of Finland & FCAI Finnish Center for Artificial Intelligence, and Mangosuthu University of Technology of South Africa (Kirjalainen 2022).<\/p>\n\n\n\n

\"[Alt
Image 2. Construction industry is traditionally known as one of the anti-change industries. (andrechinn 2009)<\/figcaption><\/figure>\n\n\n\n

Knowledge is power<\/h2>\n\n\n\n

The aim of the research was to achieve an understanding why some companies manage to gain financial benefits from the use of AI while majority of adopters struggle with it. Throughout the research, many observations and indications towards probable causes were discovered. One of these many discoveries was the gap in the knowledge base between high performers and low performers \u2013 the latter showed tremendous lack of understanding over the subtleties of the trade whereas high performers excelled in methodology mastery.<\/p>\n\n\n\n

Judging by the results and theoretical material, leaders should be conscious about their lack of knowledge and act accordingly (Chamorro-Premuzic et al. 2018). This observation went beyond the limits of businesses themselves, as the lack of available research, academia, and journals regarding the subject was noticeable. Some experts agreed this lack of dedicated educational material to be a barrier for wider AI adoption in the field of construction and development (Haupt 2022; Toivonen 2022).<\/p>\n\n\n\n

Leadership is important, almost always<\/h2>\n\n\n\n

All levels of research \u2013 theory, survey, and semi-structured interviews – determined management\u2019s involvement in AI related projects to be crucial. However, according to experts, success can be achieved solely using off-the-shelf AI technologies thus excluding the upper management entirely (Toivonen 2022; Mucha 2022). \u00a0Arguably, achieving a significant improvement on profitability requires a considerable investment of resources (Balakrishnan et al. 2020, 5). The very nature of leadership is likely to face profound changes, as the power structure between man and machine shifts \u2013 yet the research failed to record such ongoing movements (Fountaine et al. 2020, 65; Noponen 2019, 47-48).<\/p>\n\n\n\n

\n

Authors<\/p>\n\n\n\n

Otto Kirjalainen<\/strong> is master\u2019s student at LAB University of Applied Sciences in the Faculty of Business.<\/p>\n\n\n\n

Brett Fifield<\/strong> is a Principal Lecturer at LAB University of Applied Sciences in the Faculty of Business.<\/p>\n\n\n\n

This study was supported by Rakennusteollisuus, also known as The Confederation of Finnish Construction Industries RT.<\/p>\n<\/div><\/div>\n\n\n\n

References<\/h2>\n\n\n\n

Andrechinn. 2009. Construction time. WordPress. Cited 11 May 2022. Available at https:\/\/wordpress.org\/openverse\/image\/94b831a8-11e8-4584-a629-af3615cf736e<\/a><\/p>\n\n\n\n

Balakrishnan, T., Chui, M, Hall, B. & Henke, N. 2020. Global survey: The state of AI in 2020. McKinsey & Company. Cited 10 Feb 2022. Available at https:\/\/www.mckinsey.com\/business-functions\/mckinsey-analytics\/our-insights\/globalsurvey-the-state-of-ai-in-2020<\/a><\/p>\n\n\n\n

Chamorro-Premuzic, T.; Wade, M. & Jordan, J. 2018. As AI Makes More Decisions, The Nature of Leadership Will Change. Article in Harvard Business Review. Harvard Business School Publishing Corporartion. Cited 5 May 2022.<\/a> Available at https:\/\/hbr.org\/2018\/01\/as-ai-makes-more-decisions-the-nature-of-leadership-willchang<\/a><\/p>\n\n\n\n

Fountaine, T., McCarthy, B. & Saleh, T. 2019. Building the AI-Powered Organization. Technology isn\u2019t the biggest challenge. Culture is. In Harvard Business Review. Harvard Business School Press. Cited 11 May 2022. Restricted access at http:\/\/web.a.ebscohost.com.ezproxy.saimia.fi\/ehost\/detail\/detail?vid=3&sid=39f76099- 0375-43da-9f1e079f69974fc2%40sessionmgr4008&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#AN=1 37120578&db=bsh<\/a><\/p>\n\n\n\n

Haupt, T. 2022. Research Professor. Mangosuthu University of Technology. South Africa. Online interview. 15.2.2022.<\/p>\n\n\n\n

Kirjalainen, O. 2022. The Relationship of Leadership and Artificial Intelligence in Construction and Development Industry: A Mixed Methods Research. Master\u2019s Thesis. LAB University of Applied Sciences. Cited 11 May 2022. Available at https:\/\/urn.fi\/URN:NBN:fi:amk-202205036913<\/a><\/p>\n\n\n\n

MacKenzie, M. 2018. Machine Learning & Artificial Intelligence. WordPress. Cited 11 May 2022. Available at https:\/\/wordpress.org\/openverse\/image\/4984f318-2feb-4256-ad42-a70de04807b4<\/a><\/p>\n\n\n\n

Mucha, T. 2022. Doctoral Researcher. Aalto University School of Science and Technology. Finland. Online interview. 15.2.2022.<\/p>\n\n\n\n

Noponen, N. 2019. Impact of Artificial Intelligence on Management. In Auvinen, T., Takala, T., Vesa, M., Tienari, J., Sajasalo, P., Heikkinen, S. Helms Mills, J. & Kallinen-Kuisma, M. (Eds.). Electronic Journal of Business Ethics and Organization Studies. Business and Organization Ethics Network (BON). pp. 43\u201250. Cited 11 May 2022. Available at https:\/\/jyx.jyu.fi\/handle\/123456789\/66617<\/a><\/p>\n\n\n\n

Toivonen, H. 2022. Professor of Computer Science, Vice Dean of Faculty of Science. Works on artificial intelligence (AI), data science and computational creativity. University of Helsinki. Online interview. 18.2.2022.<\/p>\n\n\n\n

\n\n\n\n

<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Global construction and development industry is facing one of its greatest challenges yet \u2013 the emergence of cognitive technologies. How are leaders equipped to manage the adoption of AI, in what is known to be one of the most anti-change industries? 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