## 2 Literature Review
### Artificial Intelligence (AI)-Based Digital Twins (DTs): Benefits and Challenges
#### 2.3.2 Artificial Intelligence (AI)-Based Digital Twins (DTs): Challenges  
Despite the substantial benefits of implementing AI-based DTs, the literature identifies several critical challenges that might hinder their successful implementation, as shown in Table 4. These challenges include the complexity of AI algorithms, issues related to data quality, limited understanding of AI capabilities, ethical concerns, and data privacy and security risks. Addressing these obstacles is essential for the successful integration of AI-based DTs. To this end, as shown in Table 5, various studies have proposed solutions such as implementing training and education programs, providing access to case studies and best practices, offering financial incentives or subsidies, enhancing technical support from vendors, and strengthening measures to ensure data privacy and security. These strategies aim to mitigate the identified challenges and promote the broader adoption of AI-based DTs technologies. For example, a review of 88 articles identified significant obstacles hindering the implementation of AI-based DTs. According to [PERSON] et al. (2024) [45], a key challenge is the lack of demand from clients in both developed and developing countries. To address this issue, the study recommended that access to case studies and best practices could play a pivotal role in raising awareness and increasing demand. Moreover, the high implementation costs represent another significant barrier. In this regard, technical support from vendors was proposed as a potential solution to alleviate financial constraints. Lastly, data privacy and security concerns remain critical issues that must be resolved to foster broader adoption and build trust in AI-based DT technologies. These findings highlight the need for targeted strategies to overcome these challenges and successfully integrate AI-based DTs across industries.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**No.** & **Benefits** & **References** \\ \hline
1 & AI facilitates digital twins in modeling complex & [10] \\  & real-world systems & [10] \\
2 & Facilitates strategic decision making & [9; 10; 60; 61] \\
3 & AI capabilities to improve analytics & [9; 10] \\ \hline \hline \end{tabular}
\end{table}
Table 3: Benefits of integrating AI-based DTs.  
The literature review highlights the growing prominence of DT technology and its integration with AI across various industries. While the transformative potential of AI-based DTs is thoroughly documented, their application in the construction sector remains underdeveloped compared to industries such as manufacturing. AI-based DTs offer substantial advantages, including the ability to model complex systems, enhance decision-making, and improve data analytics, all of which play a critical role in optimizing construction processes by reducing delays, minimizing resource waste, and boosting efficiency. However, several significant obstacles hinder their broader adoption, including the complexity of AI algorithms, challenges with data quality, a limited understanding of AI functionality, ethical considerations, and concerns about data privacy and security. Addressing these barriers requires a combination of targeted solutions, including training initiatives, access to case studies and best practices, financial incentives, and robust technical support. These strategies are crucial for promoting the adoption of AI-powered DT technologies, enabling the construction industry to fully harness their transformative potential.