Developing Strategic AI Integration for Sustainable Construction Assignment Sample

CHAPTER 1 INTRODUCTION

Background

Digital transformation refers to integrating and adopting the latest technology that helps in enhancing the overall operations of business entity. AI refers to the science of making smart and intelligent machines. Sustainability emphasises on undertaking business activities without creating negative impact on social, environment and economic aspect of the country. This proposal is based on creating a framework For AI integration that aids in reducing the negative impact on the environment.

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Aim and objectives

Aim

Objectives:

• To identify the best practices and potential barriers in integrating AI within the construction industry's digital transformation efforts.
• To develop a phased roadmap for construction firms, detailing steps for AI adoption and digital transformation with an emphasis on sustainability.
• To provide actionable strategies for construction firms to overcome challenges in AI integration and digital transformation

Research question

Q.1 What are various barriers and obstacles in integrating AI within construction industry?

Q.2 What are the steps for integrating AI within construction industry for promoting sustainability? 

Rationale

The current research is based create framework for AI integration as to enhance sustainability within the construction industry by improving the productivity. This considered as research issue because sustainability is the major requirement of each industry and plays a crucial role in enhancing overall sales as well as profitability of the business entity (Wamba-Taguimdje et al, 2020). In the current times, AI has adopted in each function of the business entity which creates necessity to identify its influences on Sustainable practices within the construction industry. The concerned industry has been claimed for negatively impact the environment which requires firm to identify potential impact of the AI on enhancing sustainability. Thematic approach will be used by the researcher to shed light on the significance of AI in improving sustainability within UK construction industry.

Significance

The study conducted on the AI integration and sustainability will help firm in identifying the potential role of technology in promoting the sustainability. This concept helps in creating awareness regarding the negative impact of not including technology on the firm’s operations (Mhlanga, 2021). Initiating the current study will help in identifying all the challenges that restrict successful implementation of AI. Further, this will help other organization in taking proactive actions so that negative impact and all the challenges could be overcame and sustainability could be effectively promoted within the industry.

Structure

• Chapter 1: Introduction

 This chapter discusses the aims & objective behind the study and provides information regarding the necessity of conducting study on the research topic.

• Chapter 2: Literature review

The second chapter of dissertation includes the analysis of the already published information regarding the research issues. This includes depicting both positive and negative aspect to the research issue.

• Chapter 3: Research methodology

This section includes various methodology and approach for determining most accurate information related to research issue.

• Chapter 4: Findings & Discussion

The fourth chapter includes representing data in structured manner and provide interpretation of the collected information.

• Chapter 5: Conclusion & Recommendations

The last chapter of dissertation provide the summary of the entire chapter and includes suggestion for resolving research issues.

CHAPTER 2: LITERATURE REVIEW

Various barriers and obstacles in integrating AI within Construction industry

Based on the view point of Turner et al, (2020), it has determined that lack of collection of data and use of fragmented data has reduces the efficiency of AI training. This fragmented data result in providing inadequate information to AI that eventually result in creating obstacle in successful utilization of AI.  According to the view point of Abioye et al, (2021) there are large number of challenges and issues that create obstacles in the successful integration of AI within the construction industry. Employee’s resistance is the major issue in successful integration of AI as technology has resulted into the termination of jobs of large number of workers. Introduction of new technology also requires employees to develop new skills and technique that result in developing the fear of losing job. This insecurity has resulted in creating barrier while adopting AI which leads negative impact on firm’s working. On the other hand, Regona et al, (2022) stated that AI integration will support in reducing the work burden on the employees and support in enhancing overall productivity. AI integration will help in completing the repetitive task that result in allowing the time for undertaking the crucial activities. For example; Morgan Sindall has initiated AI technology for automated the routine task that result in providing scope to focuses on more crucial decisions. This helps in providing the better satisfaction to customer that aid in enhancing the overall financial and profitability position of firm.

Based on the view point of You and Feng (2020), it has depicted that data security and ethical issues are the major challenge that create obstacle in the successful integration of AI within constructing industry. Task undertaken through AI technology generally increase the risk of biasness, discrimination, transparency and accountability. This reduces the accuracy and validity of the activity results which further creates obstacle in the successful integration. On the critical point of view, Turner et al, (2020) stated that effective and accurate framework has been established that helps in ensuring that AI has been utilized in the trustworthy responsible and trustworthy manner.

Further Darko et al, (2020) asserted that budget and cost concern is another crucial challenge that creates issues in the successful integration of AI within the construction industry. AI integration requires organization to provide adequate training to the employees for learning new techniques, develops infrastructure for utilizing AI which requires high cost investment by the business entity. This result into increasing overall expenditure by the business entity which further leads negative impact on the firm’s financial position. For example: Morgan sindall has invested over 10 million pound for adopting AI and undertaking digital transformation which result into negative impact on the firm’s financial and profitability position.

However, Alaloul et al, (2020) professed that AI integration helps in reducing the wastes of the business entity that assists in creating the positive impact on the overall budget of the organization. AI integration also helps in reducing the need of the employees that lead reduction in the overall organization’s cost and enhances profitability of the business entity. Sacks, Girolami and Brilakis (2020) asserted that skills shortage is another major issue that restricts the successful integration of the AI within construction industry. New technology requires skilled and competent employees that could successful adoption of new technology and techniques for using AI technology. The shortage of required skills reduces organization’s motivation to adopt new technology that results in negatively impacting on digital transformation within the industry.

On the other hand, Delgado et al, (2019) firm needs to establish effective T&D session so that required skills could be developed and business entity could be able to adopt the AI technology in their operations. Maskuriy et al, (2019) explicated that regulatory compliance is another major issue that restricts firm in effectively adopting the latest technology and negatively impact on the overall working of the construction industry. Government has established various new reforms that include AI act 2024 which promotes safety, transparency, robustness, security and fairness. This creates obligation for the firm to effectively monitor as well as control their operations and align activity to the regulation so that required obligation could be fulfilled. These guidelines restrict firm to adapt AI and create issues in the effective digital transformation.

However, Wang (2020) professed that following government guidelines helps in effectively aligning firm’s operation that result in overcoming legal obligation and enhances overall reputation of the business entity. This helps in attracting the large number of customer towards the firm that result in increasing overall financial and profitability position of the business entity. According to the view point of Li, Greenwood and Kassem (2019) data confidentiality and compatibility are also the crucial obstacles in the successful integration of AI technology within the operations of business entity. There is a high amount of data secrecy issues that faced while using AI. The current infrastructure of business entity may not be compatible for the technology which creates issues in successful integration of AI technology.  This requires firm to develop the current infrastructure & architecture within organization and need to maintain confidentiality which requires high expenditure by the business entity. Thus, high level of organizational expenditure negatively impacts the firm’s overall profitability.

To develop a phased roadmap for construction firms, detailing steps for AI adoption and digital transformation with an emphasis on sustainability by improving productivity

Nowadays in all sectors, Artificial intelligence (AI) is a powerful technology with a range of capabilities, which are beginning to become apparent. In the current times, construction organizations face pressure to embrace new and emerging technologies as well as reinforce processes and tools to increase productivity. Adoption of AI and focusing towards the digital transformation is beneficial for the construction companies because it helps in enhancing the safety and risk management, reduces costs, reinforcing processes and enhanced operational efficiency, better customer experience and increase collaboration, timely project completion. Initial, partial and final are considered as three significant stages of adopting AI strategies. As said by Regona et al, (2022), for the adoption of AI and digital transformation in effective way the construction sector require to focus on recruiting AI expert and creation of database for training. In addition to this, at partial stage for the adoption of emerging technologies the construction sector require to allocate the fund for AI teams, purchase equipment’s of data collection and monitoring (Pan and Zhang, 2021).  On the other hand, at final stage the construction companies require to collect real-time data, execution of enhanced project management strategies and timely procurement of materials as per site progress.  AI has significant impact on the construction firms because it helps in transforming the business operation towards the sustainability. AI in the construction sector helps in enhancing the overall efficiency and makes it more sustainable. AI in the construction sector also helps in saving time, increase productivity and reduce costs of raw materials.  Adoption of AI is beneficial in the construction sector because it helps in increase the productivity by 50% (McKinsey Digital, 2023).

For achieving sustainability in order to protect the environment, it can be important for the construction organizations to place emphasis on the adoption of AI and digital transformation. As per the view of Baduge et al, (2022), for developing the phased roadmap of the construction companies, it is significant for the construction organizations to follow all steps for the implementation of AI and digital transformation.   Cultivating the employees that is ready to accept the change is considered as first step for the AI adoption and digital transformation.  For adopting emerging technologies the construction companies can require to conduct the training and development programs that cater to diverse learning needs within multigenerational workers (Abioye et al, 2021).  Implementation of this step is the beneficial for the construction companies because it aids in bridging the knowledge gap as well as builds confidence among the workers by enhancing their skills.

 As critically argued by Sacks, Girolami and Brilakis  (2020),  if the construction companies do not conduct training and development for the employees, in the context of emerging technologies, then they are unable to gain knowledge and skills from which they are fail to adopt AI for completing projects. The construction companies encourage mentorship programs to enable knowledge sharing between newer and experienced employees. In the construction sector, the younger generation are most likely to adopt emerging technologies in order to provide sustainable projects to the customers (Turner et al, 2020).   In addition to this, tailored training programs helps in creating the culture of continuous learning within the construction companies. Influencing and encouraging employees to improve their skills with the training & development opportunities will help in promoting the sense of engagement and empowerment which ultimately leads more adoptable and agile employees. 

Apart from this, for achieving the sustainability the construction sector will need to emphasis on implementing the predictive maintenance with AI.  As critically contended by Yaseen et al, (2020), in the present times, the construction sector seeks for the transformation towards green and more sustainable practices so they recognize electrification as alternative traditional equipment with the fuel powered. For example, Morgan Sindhall is also focusing on the electrification while adopting AI and digital transformation to accomplish sustainability because it helps in providing various benefits such as lower operating costs, reduces carbon emission and enhances the energy efficiency. Along with this, for maintaining the predictive maintenance through AI, the construction companies are focusing on adopting AI algorithms (Yigitcanlar et al, 2020). Adoption of this step proves to be beneficial for the construction companies because it allows them schedule maintenance activities, optimize equipment performance and reduces down time. 

On the other hand, for adopting AI and digital transformation in effective way in order to phased out road maps. As per the thought of Pena et al, (2021), for the adoption of AI and digital transformation, the construction company will need to set up pilot projects. Instead of mere testing the construction sector will need to include their team members in early adoption stages where they can directly interact with the emerging technologies. On the critical note Himeur et al (2023), if the construction companies are not placing emphasis on the interaction of AI and transformation towards the digital transformation then it negatively impacts the overall operation as well as satisfaction and experience of the customers.  Furthermore, this approach allows the construction companies to gain the first-hand insights and impression which considered as useful for gaining understanding regarding the ways of integration of AI into the culture and workflows (Regona et al, 2022).

 Apart from this, another step for AI adoption is partner with tech sector. For transforming towards the digital and execution of AI the construction sector will need to reach out to the vendors who are specializing in the implementation of technologies.  As critically contended by Pan and Zhang (2021), these partners’ helps in bring the wealth of experience and knowledge that are tailored to solve the unique issues and opportunities within the sector.  Implementation of this step is beneficial for the construction sector because it helps the construction organizations to achieve sustainability and gain competitive advantage over the competitors as well as increase satisfaction and improve experience of the customers.        

Impact of AI and digital transformation on sustainability within construction industry

Based on the view point of Feroz, Zo and Chiravuri (2021) it has claimed that AI has created both positive and negative impact in promoting sustainability within construction industry of UK.  AI supports in waste management as it helps in managing and reducing the waste that leads to effectively promoting sustainability. This technology helps in predicting the accurate amount of resources and material that will be required and focus on ensuring that resources are optimally utilized. For example: Morgan Sindall has initiated AI that helps in suggesting the accurate amount of resources and helps in the proper utilization of resources that result in reducing the wastages. Firm has used this technology with the aim of reducing wastages that result in saving the firm’s cost and decreasing the negative impact on the natural resources.

On the critical point of view Abioye et al, (2021) explicated that AI integration has resulted into increasing electricity consumption that negatively impact on sustainability of the firm. AI applications require extensive training which needs to process the large amount of data which uses high electricity. In this instance, Morgan Sindall has claimed that over 21% of the electricity consumption has increased which has resulted into negatively impact the sustainability within the country. Kulkov et al, (2024) stated that AI integration has resulted into decreasing the overall cost of business entity that encourages firm to invest in CSR activity. It has identified that firm with high and effective profits usually invest towards adopting the sustainable activity. AI has helped in automated the routine task and reduces the overall wastage of business entity that resulted into increase in the financial position of an organisation. This helps firm to invest towards safeguarding environment and society which results in promoting sustainability.

On the critical point of view, Oláh (2020) said that AI integration has resulted in terminating the large amount of job and increases unemployment rate within country which negative impact on the society. For example: Morgan Sindall has terminated over 2500 employees in year 2023 due to the introduction of technology that negatively impacts the society result in inefficiency in promoting sustainability. Further, Llopis-Albert, Rubio and Valero (2021) stated that AI adoption has resulted in providing method through which fuel consumption and emission could be decreased resulted in positively impacting on the natural resources. This technology focuses on suggesting the alternative method through which goals could be achieved without creating negative impact on the environment. For example; Morgan Sindall has initiated AI as the carbon calculator tool that helps in measuring the carbon emission and involve towards suggesting measure to reduce carbon emission.

However, Akinosho (2020) professed that AI provide measures without evaluating practicability of the measures that result in reducing the applicability of such ways. The measures suggested by AI technology are not cost effective that restrict company from promoting sustainability within its operations. Based on the view point of Brock and Von Wangenheim (2019) it has determined that AI integration help in enhancing sustainability by building and designing operations. This technology assists form the design phase to construction and ultimate operation phases. AI help in creating model that are sustainable as well pleasing as it provide suggestion after evaluating various factors such as ventilation, energy consumption and natural light. Further, AI has capability in processing large amount of data in less time and provides accurate result which leads to effective completion of project planning stage.

On the critical point view, Van Wynsberghe, (2021) described that AI integration has increased the electronic waste that is creating negative impact on the sustainability. It has estimated that due to in introduction of AI; the electronic waste form construction industry has increased by 18% which is estimated to reach 120 million metric tonnes by year 2050.  This includes the disposal of mercury, cadmium, mercury which is negatively impacting on the soil and other natural resources. Further, Sepasgozar (2021) professed that AI integration has resulted in providing accurate estimation regarding long term maintenance sustainability of the technology. AI in construction industry help in providing information regarding the failure of the technology that helps in timely replacement and maintenance of the technology. This also reduces the scope of replacement and repair by effectively managing the technology that results in saving cost of the organization and support in promoting sustainability. On the critical point of view, Brunetti et al, (2020) asserted that AI generally provide data based on the historic analysis but did not focuses on the present condition of the machinery that results in increasing unnecessary expenses for the business entity.

Literature Gap

Earlier study has been conducted to identify the importance of AI for effective achieving organization’s goals within the construction industry of UK.  Concentration has not been paid on allaying the influence of such technology in promoting sustainability within the Industry. The present study will focus on identify the role of AI in enhancing sustainability and it will also depict on various challenges and obstacles that are restricting firm from effectively adopting AI and support in adopting effective measures to overcome obstacles.

CHAPTER 3: RESEARCH METHODOLOGY

Introduction

Research methodology means a process, technique that is used to recognize, select and evaluate information about the research topic. To make the study effective and successful correct research methods should be used. The current chapter will outline the different kind of research method, approaches that can be used into the research study and also the reason of selection of method.

Research Type

It refers to diverse kind of methods that has been used for conducting the research study. It is choose according to the goals, timeline and purpose of the study. The two major types of research is qualitative and quantitative research.  The Qualitative research refers to a procedure of gathering non-numerical data to get in-depth understanding of the concept, experiences and opinion. In contrary to this, quantitative research refers to a method of gathering and evaluating numerical data (Ahmad et al, 2019). In the present study, to recognize the influence of AI integration and digital transformation in improving overall sustainability, both qualitative and quantitative research is used. The researcher chooses quantitative research type as it furnishes more reliable and accurate data which is useful for the purpose of the study. In addition, qualitative research is used to gain better understanding of the specific phenomenon.

Research Approach

Research approach is the process that is selected by the researcher to gather, evaluate as well as interpret data. There are two kinds of research approach namely inductive and deductive approach. Inductive research approach is a kind of bottom-up approach in which theories developed and general conclusion made based on particular data or observations.  On the other hand, deductive research approach refers to top-down approach. In this researcher build hypothesis and then test it via data as well as observation.  In the current study, researcher has been used combination of both approaches.  The inductive research approach is advantageous in searching new probability in data as well as forecasting the cause behind the certain happening correspondingly help in enhance better understanding of the research problem (Chandra et al, 2019). In addition, the deductive approach advantageous in providing precise data which is helpful in get clear outcome. Deductive research approach furnish an opportunity to apply the research outcome in the broader context correspondingly aids in attain better insight into the research problem.

Research Philosophy

Research Philosophy means set of assumption and beliefs that direct the researcher in design and implementation. Two different kind of research philosophy are positivism and Interpretivism.  Positivism philosophy focuses on scientific evidences such as statistics and experiments, it not emphasis on social context and human perception (Alharahsheh and Pius, 2020). On the other hand the Interpretivism philosophy emphasis on the importance of reason, context and human behavior. In the research study to identify the influence of AI integration and digital transformation in enhancing sustainability in construction industry of UK, the research has been selected mixture of both philosophies. The reason of selection of mixture of philosophy is to produces effective and comprehensive finding as well as to get in-depth understanding of the subject matter.

Data Collection

Data collection is a procedure of gathering the information and data to attain the deeper understanding of the specific subject matter as well as to implement the research in an accurate and effective manner.  Primary and secondary are the two major data collection method. Primary data collection is a process of gathering first-hand information via the individual who experience the research problem (Mazhar et al, 2021). Inversely, secondary data collection method refers to gathering the information related to particular phenomenon with the help of previously conducted research such as books, article, government statistics, journals and so more. It is a cost and time effective data collection method. In context of present study, to evaluate the impact of AI integration on decline negative environmental impact, the researcher has been used combination of both data collection method. The reason of selection of both method is that it furnish wide variety of the information. This leads to enhance overall efficiency as a result researcher able to attain the objectives of study significantly. Primary data collection method has been used to collect data according to the objective of the research problem as a result survey will be conducted on 100 managers of construction industry. In addition, secondary sources is also used that will include published data, articles, journals related to the area of study.

Sampling

Sampling means selection of the group from which the primary data gathered for the purpose of the research problem.  The two most effective method of selecting sample involves probability and non-probability method. In the context of probability method, sample selected from the population as per the principle of the randomization, in this researcher select the respondent regardless of any predetermined perception. Conversely, non-probability sampling the researcher selects the sample based on the subject.  Within the probability method, the opportunity of selection is fixed and furnish to each individual while it is not clear in the non-probability method (Rahman, 2023). To identify the impact of AI integration in reducing negative environmental impact, a probability sampling method has been selected by the researcher. In the context of this, 100 managers from construction industry selected and information has been collected via help og questionnaire. The reason of selection of the method is maintaining the authenticity and accuracy of the result as this method decline and mitigates the scope of biasness. Thus, to attain the accurate and reliable information regarding the research problem, researcher selected the random sampling method.

Data Analyzing

Data analysis is a process of analyzing, converting and transforming the raw data for the purpose of clear understanding as well as to obtain depth information related to research problem. It is an important practice, if data is not evaluated properly then there is no chance of successful outcome.  There are two methods of data analysis: SPSS and thematic.  In the thematic method, themes are created based on the objectives and then evaluated them as per the collected responses. The thematic method is mainly used for the purpose of analyzing the qualitative data in which researcher closely examine the data to identify common themes and patterns (Terry and Hayfield, 2020). On the other hand, SPSS is a  statistical software use to analyzing data in which first data entered and then evaluated by applying the different statistical function (Abu-Bader, 2021).

To achieve the aim of evaluating impact of AI integration nd digital transformation on decline negative environmental impact both data analyzing method SPSS and thematic used. In the thematic analysis method, hypothesis is testing by using deductive approach and themes are creates using inductive approach. The reason of selection of both methods includes evaluating the data in accurate and effective manner. The main reason of selection of the SPSS method includes that it furnish more scientific and reliable output that help in attain the objective easily. In addition, the thematic data analysis helps in understand and interpreted outcome easily with the help of charts and graphs.

Ethical Consideration

In research study, ethical consideration implies a set of principles that direct and support research design and practices. For the researcher, it is essential to follow rules and regulation at the time of gathering data from the respondents. The most important ethical aspect that researcher have followed while conducting the present study is taking written consent. The researcher signs the consent form from the respondent that represent that data provided by participant use by the researcher in the study. While collecting primary data from the respondent, it is essential that scholar clearly informed the respondent about the purpose of the study as well as associated risk and benefits (Broesch et al, 2020). Researcher must provide freedom to participant to voluntary involve in survey as well as leave the study at any point of time.

In the context of current research study, scholar also focuses on maintaining the confidentiality of the participant by effectively utilizes the digital tools and techniques at the time of implementing research. To keep the respondent data confidential, scholar stored the signed consent form in the locked file drawer and keeps the survey file password protected. It is an essential principle that requires to be followed by scholars at the time of working on the study.  Therefore, it is a great responsibility of the researcher to keep the personal information of the respondent safe. Along with this, while collecting the data from the secondary sources, several precaution is considered such as data collect from the online website that are published after the year 2020, the major focus given on collection of data from the authentic and official sites. Thus, all this ethical consideration aids in making the research reliable and accurate.

Limitation

Research limitation is considered as a shortcoming that can be practical or theoretical, that is usually remaining outside the control of the researcher. In the successful completion of the present study, several kinds of research limitation occur. In the present research study, the one of the major limitation is selection of the suitable sample as the topic is wide as a result there is requirement of collection of the accurate data.  The main issue is related to which individual needed to be choose as the sample. The limitation address by the researcher by using the probability method as it is a best way to select sample without any bias.

In addition, the other limitation is regarding to lack of time and budget as the time allocated for the present research study was limited. However, via the effective time management skill, scholar of the current research study able to meet the necessary standard as a result able to attained the outcome. To address the limitation effectively within the study secondary data sources is used as  it is time and cost effective method for the collection of wide amount of data related to research problem. Also, to save the time thematic data analysis is used as representation of data in charts aids in rapid interpretation. Thus, with the good time management skill, the researcher planned all activities in advance as a result help in enhancing overall efficiency as well as accomplished research on time.

Reliability and Validity

Reliability within the research means the accuracy of the gathered data while validity refers to appropriateness of data in the current time.  To complete the study efficiently and effectively, it is important to consider the reliability and validity factor. To maintain the reliability of the present study data collected according to research objective (Sürücü and Maslakci, 2020). Also, the researcher has used the secondary data which is published after the year 2020, no data is taken in the study that is published before 2020. It is essential to consider this factor as too old data make the research outcome invalid.  Also to make the study reliable and valid only data taken from the copyright or patent sites and proper keywords is used relating to the research topic.

Conclusion

In the end, it is articulated that adherence of the appropriate method is necessary for the research. The above chapter concluded that to identify the impact of AI integration on the decline negative environmental impact the combination of qualitative and quantitative research is used. For collection of the data primary and secondary sources used. To collect first-hand information survey conducted on 100 managers of construction industry. Within the study researcher consider all ethics and ensure reliability and validity of study.

CHAPTER 4: DATA ANALYSIS AND FINDINGS

FINDINGS

Statistics
		"Do you work in construction and/or Construction Industry related sector	"Which area of the Construction/Construction Industry you participate?	How many years of work experience do you have in the industry?	How many people work in your company?	Are you familiar with the use of ANY AI and/or AI Supporting tech2logies (IOT, Back-Office Analytics etc) in construction and /or construction related industry?	If yes, please mention the technologies that you know and their usage as you know below –	How would you rate your understanding of AI tech2logies?	Does your work involve, you perform repetitive tasks?	Do you think with using A.I will boost your productivity?	Do you actively collect and report data for all the activities and tasks performed?	Does the company you are employed in, Make use of A.I?	Does your company invest in upgradation and digitization to latest tech2logies?	How  do you think it is to hire AI experts to facilitate AI integration in construction?	What do you think is more suitable for AI adaptation:	Do you think backend data like contract documents, BOQ, tenders, Project reports are readily available in the office?	Do you agree with the strategy of using AI for back-office document management and data handling in the initial stage?	Which type of organization do you believe is most capable of 2ly adopting AI in the construction industry?		Please rank the following in order of their ability to adopt AI in the construction industry, from most capable (1) to least capable (3)		Do you believe that allocating funds for AI team and data management is feasible for construction firms?		Do you think improving the backend processes using AI in the intial phase will boost confidence to further invest in A.I?		How 2 do you think implementing smart wearables, drones, and IoT sensors for automated work-progress data collection at onsite would be?		How important do you think it is to train employs for use of A.I in construction?		How 2 do you think providing training to employs in A.I it will boost the adaption and implementation of A.I in construction?		Would real-time project monitoring and data-driven decision-making significantly improve project outcomes and boost productivity?		Do you think your firm will benefit by implementing real-time data collection and optimization of schedules as proposed in the final stage?		What do you perceive as the biggest barrier to AI integration in construction?		Arrange in order (from most important to least): What do you perceive as the barrier to AI integration in construction		Overall, how 2 would you be to adopt this three-stage AI strategy in your organization?
N	Valid	100	84	100	100	1	0	99	1	100	100	100	100	100	100	100	100		100		100		99		1		100		100		100		100		100		100		100		99
	Missing	0	16	0	0	99	100	1	99	0	0	0	0	0	0	0	0		0		0		1		99		0		0		0		0		0		0		0		1
Mean		1.1600	3.6905	2.1900	1.83	1.0000		1.74	3.0000	2.7200	1.1400	1.0600	1.1200	1.4400	1.1700	1.8100	1.7800	1.2100		1.1100		1.36		1.0000		1.8000		1.4100		1.7800		1.5900		1.6800		1.2400		1.2800		2.74
Median		1.0000	4.0000	2.0000	2.00	1.0000		2.00	3.0000	3.0000	1.0000	1.0000	1.0000	1.0000	1.0000	2.0000	2.0000	1.0000		1.0000		1.00		1.0000		1.0000		1.0000		2.0000		1.5000		2.0000		1.0000		1.0000		2.00
Mode		1.00	5.00	2.00	2	1.00		2	3.00	3.00	1.00	1.00	1.00	1.00	1.00	2.00	2.00	1.00		1.00		1		1.00		1.00		1.00		2.00		1.00		2.00		1.00		1.00		2
Std. Deviation		.36845	1.73536	.88415	.378			.442		.77954	.34874	.23868	.32660	.49889	.37753	.72048	.41633	.40936		.31447		.677				.95346		.79258		.78599		.66810		.72307		.63755		.66788		1.337

• Frequency Table

"Do you work in construction and/or Construction Industry related sector
		Frequency	Percent
Valid	Yes	84	84.0
	No	16	16.0
	Total	100	100.0

"Which area of the Construction/Construction Industry you participate?
		Frequency	Percent
Valid	Design	9	9.0
	Planning/costing/estimation	23	23.0
	Procurement	5	5.0
	Contracts	7	7.0
	Execution	30	30.0
	Safety	8	8.0
	HR	2	2.0
	Total	84	84.0
Missing	System	16	16.0
Total		100	100.0

How many years of work experience do you have in the industry?
		Frequency	Percent
Valid	Less than 2years	17	17.0
	3-5 years	58	58.0
	5-10	17	17.0
	11-20 years	5	5.0
	More than 20 years	3	3.0
	Total	100	100.0

How many people work in your company?
		Frequency	Percent
Valid	Small (fewer than 50 employees)	17	17.0
	Medium (50-250 employees)	83	83.0
	Total	100	100.0

Are you familiar with the use of ANY AI and/or AI Supporting tech2logies (IOT, Back-Office Analytics etc) in construction and /or construction related industry?
		Frequency	Percent
Valid	yes	1	1.0
Missing	System	99	99.0
Total		100	100.0

If yes, please mention the technologies that you know and their usage as you know below –
		Frequency	Percent
Missing	System	100	100.0

How would you rate your understanding of AI tech2logies?
		Frequency	Percent
Valid	Excellent	26	26.0
	Good	73	73.0
	Total	99	99.0
Missing	System	1	1.0
Total		100	100.0

Does your work involve, you perform repetitive tasks?
		Frequency	Percent
Valid	3.00	1	1.0
Missing	System	99	99.0
Total		100	100.0

Do you think with using A.I will boost your productivity?
		Frequency	Percent
Valid	Yes	6	6.0
	No	30	30.0
	3.00	50	50.0
	4.00	14	14.0
	Total	100	100.0

Do you actively collect and report data for all the activities and tasks performed?
		Frequency	Percent
Valid	Yes	86	86.0
	No	14	14.0
	Total	100	100.0

Does the company you are employed in, Make use of A.I?
		Frequency	Percent
Valid	yes	94	94.0
	No	6	6.0
	Total	100	100.0

Does your company invest in up gradation and digitization to latest tech2logies?
		Frequency	Percent
Valid	Yes	88	88.0
	No	12	12.0
	Total	100	100.0

How  do you think it is to hire AI experts to facilitate AI integration in construction?
		Frequency	Percent
Valid	Very Important	56	56.0
	Important	44	44.0
	Total	100	100.0

What do you think is more suitable for AI adaptation:
		Frequency	Percent
Valid	Company appointing an independent person to collect data for A.I	83	83.0
	Train the existing employs to adapt data collection and reporting	17	17.0
	Total	100	100.0

Do you think backend data like contract documents, BOQ, tenders, Project reports are readily available in the office?
		Frequency	Percent
Valid	yes	35	35.0
	No	51	51.0
	3.00	12	12.0
	4.00	2	2.0
	Total	100	100.0

Do you agree with the strategy of using AI for back-office document management and data handling in the initial stage?
		Frequency	Percent
Valid	Yes	22	22.0
	No	78	78.0
	Total	100	100.0

Which type of organization do you believe is most capable of 2ly adopting AI in the construction industry?
		Frequency	Percent
Valid	Large Construction companies	79	79.0
	Small contractors	21	21.0
	Total	100	100.0

Please rank the following in order of their ability to adopt AI in the construction industry, from most capable (1) to least capable (3)
		Frequency	Percent
Valid	1.00	89	89.0
	2.00	11	11.0
	Total	100	100.0

Do you believe that allocating funds for AI team and data management is feasible for construction firms?
		Frequency	Percent
Valid	Yes	74	74.0
	No	14	14.0
	Unsure	11	11.0
	Total	99	99.0
Missing	System	1	1.0
Total		100	100.0

Do you think improving the backend processes using AI in the intial phase will boost confidence to further invest in A.I?
		Frequency	Percent
Valid	Yes	1	1.0
Missing	System	99	99.0
Total		100	100.0

How 2 do you think implementing smart wearables, drones, and IoT sensors for automated work-progress data collection at onsite would be?
		Frequency	Percent
Valid	Very effective	57	57.0
	Effective	6	6.0
	Somewhat effective	37	37.0
	Total	100	100.0

How important do you think it is to train employs for use of A.I in construction?
		Frequency	Percent
Valid	Very Important	78	78.0
	Important	3	3.0
	Neutral	19	19.0
	Total	100	100.0

How 2 do you think providing training to employs in A.I it will boost the adaption and implementation of A.I in construction?
		Frequency	Percent
Valid	Very effective	37	37.0
	Effective	53	53.0
	Somewhat effective	7	7.0
	Not very effective	1	1.0
	Not effective at all	2	2.0
	Total	100	100.0

Would real-time project monitoring and data-driven decision-making significantly improve project outcomes and boost productivity?
		Frequency	Percent
Valid	Yes	50	50.0
	No	42	42.0
	3.00	7	7.0
	4.00	1	1.0
	Total	100	100.0

Do you think your firm will benefit by implementing real-time data collection and optimization of schedules as proposed in the final stage?
		Frequency	Percent
Valid	Yes	41	41.0
	No	55	55.0
	4.00	3	3.0
	5.00	1	1.0
	Total	100	100.0

What do you perceive as the biggest barrier to AI integration in construction?
		Frequency	Percent
Valid	Cost	87	87.0
	Lack of expertise	2	2.0
	Technological limitations	11	11.0
	Total	100	100.0

Arrange in order (from most important to least): What do you perceive as the barrier to AI integration in construction
		Frequency	Percent
Valid	1.00	84	84.0
	2.00	4	4.0
	3.00	12	12.0
	Total	100	100.0

Overall, how 2 would you be to adopt this three-stage AI strategy in your organization?
		Frequency	Percent
Valid	Very willing	19	19.0
	Willing	33	33.0
	Neutral	16	16.0
	Unwilling	17	17.0
	Very unwilling	14	14.0
	Total	99	99.0
Missing	System	1	1.0
Total		100	100.0

DISCUSSION

Based on the findings, it has determined that research has been conducted on the respondent that has worked in the construction industry. This will help in gaining more accurate information and support in identifying effective framework for the AI implementation. It has further identified that large number of respondent belongs to the execution sector which will help firm in effectively undertaking the implementation of AI in the organization. It has also depicted that large number of respondent are unaware of the use of AI integration within the construction industry. Further large number of respondent believes that the AI technology is effective for the construction industry.

In the support Chowdhury et al, (2023) stated that AI support in undertaking the entire repetitive task that provide time to employees to concern on crucial activities. For example: Morgan sindall has adopted AI which help in project planning, ensure safety and focuses on overall controlling quality of services. Further, it has derived from the finding that that construction industry involves large number of repetitive task that requires huge amount of time such as entering data, recording employee’s performance. It has also believed that AI integration helps in improving overall performance and productivity of the employees.

Holmström (2022) stated that AI provides scope to employees to involve in high value activities which result in overall growth and development of the workers.  This technology helps in better planning and effective resource allocation that improve overall worker’s productivity. It has further identified that large number of companies has involved in collection and reporting all the data. Burström et al, (2021) asserted that this collection and reporting data assist in effectively analysing the performance of the employees based on which effective action could be taken.  From the findings it has depicted that AI has been used in large number of company. For example: Morgan Sindall has initiated AI with the view of reducing wastages by effectively monitoring process and ensuring high quality services.

Findings also depicted that along with AI integration, company are also focusing over effectively upgrading the technology as this will help in maintaining stability in the dynamic environment. On the other hand, Chan (2023) stated that this advancement has resulted in enhancing overall cost for the business entity. It has identified that rather than providing training to existing employees it is better to hire AI expert. In this support Muhie and Woldie (2020) explicated that training session are costlier and it does not guaranteed that all employees will able to learn the techniques. Further, it is very time consuming activity to train the existing workers’ instead of which new employees should be hired. It has identified that backend data and project report are not easily available and requires high amount of time for managing the same.

In the Morgan sindall, AI has been adopted for managing the back office document which help in gaining all the information at the particular place and also assists in maintaining confidentiality of information. It has also determined that effective training should be provided to the employees that will help in reducing cost of hiring new employees. Lipkova et al, (2022) stated that for hiring expert firm needs to pay a high amount of money where as providing training will help in fulfilling personal need of workers that leads to improving overall productivity. This training will also help in increasing employee’s confidence results in enhancing overall adaptability of the workers. It has also determined form findings that informed decision help in improving overall productivity and outcome of the project.

Makarius et al, (2020) stated that AI help in evaluating dada without any biasness and human error result in better outcome. It has further determined that cost is the major issues that restrict firm in effectively adopting AI in their operation. Morgan sindall has invested over 215 pound for the integrating AI that has resist in negatively impacting on overall profitability of the business entity. Hennigh et al, (2021) stated that integrating new technology requires firm to invest towards infrastructure development that has resulted in negatively impacting on firm’s overall financial position. IT has also determined that employees are interested in adopting new technology as this will help in enhancing their knowledge and support in improving overall productivity and performance.     

CHAPTER 5: CONCLUSION AND RECOMMENDATIONS

Conclusion

By summing up the report, it has identified developing AI integration will help in enhancing overall sustainability within construction industry. From the secondary research, it has identified that cost, data security, employees resistance are major issues in effectively implementing AI technology in the operations. For effectively determined the impact of AI framework, mixed research has been conducted by the researcher. Under this both quantitative and qualitative research methodology has bane selected that aids in enhancing understanding by evaluating numerical and descriptive information regarding the problem. Further a survey has been conducted on the 100 employees and SPSS technique has been used to evaluate to data. It has identified that large number of employees believes that AI integration will result in providing effective time to employees by automating the routine task.

It has also determined that skilled employees should be hired rather than providing training to exiting employees as it will increase cost for the organization and negatively impact on firm budget. Large number of backed activities is undertaken within technology and integrating AI in data management will help in gaining most effective data that will result in taking more accurate and informed decision. Further, it has identified that employees training is also necessary as it will assails in providing them growth opportunity that result in enhancing overall productivity. Further training helps in improving overall adaptation skill that results in ensuring stability in the dynamic environment. It has also identified that data driven decision making support in effectively allocating resources which eventually leads to gaining accurate an optimum outputs. It has identified that cost that biggest challenges in AI integration that restrict firm in effectively establishing sustainability. Development new infrastructure, providing training to employees and gaining new technology will result in increasing cost for the business entity that result in reducing overall profits of the business entity.

Recommendations

From the above analysis, it has determined that there are various measures and strategies that should be adopted by the construction industry for effective AI integration:

• Company should involve towards providing training session to the employees that will help in avoiding the situation of workers’ resistance and aids in effective implementation of AI.
• Further, manager should concentrate over developing infrastructure of the business entity that aids in effective working of AI technology.
• Manager should also emphasis over detailed examination of the workflow that will aids in identifying the areas in which AI could be efficiency implement. This will also aids in determining upcoming opportunity and support in optimising use of AI.
• The AI should be integrated from the project planning stage so that will help in determining the viability of the project and support in avoiding financial loses.
• Manager should also focuses on updating the technology so that privacy issues within the AI could be resolved and unethical practices could be avoided by the business entity.
• Before integrating, AI firm should focuses over determining the cost implications of the AI so that sustainability could be attained without hampering the financial and profitability position of the business entity.

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