果冻传媒

Identifying and Overcoming Key Challenges in AI Adoption

Dzhusupova started her research by assessing the barriers that the Engineering, Procurement, and Construction (EPC) industry faces when trying to use Artificial Intelligence.

She highlighted issues like people's reluctance to change, challenges in fitting AI into current systems, and the need for different strategies based on how prepared a company is to use AI. The researcher then created specific plans to help EPC companies successfully integrate AI based on where they currently stand in their AI journey.

Practical AI Applications for Enhanced Efficiency

A major part of this research was creating and testing practical applications of Artificial Intelligence that can help automate important tasks in EPC projects.

Dzhusupova鈥檚 research showed that AI can make project operations better by automatically checking the quality of engineering plans and improving how material costs are estimated.

These AI tools can help companies use their resources more effectively, lower costs, and increase the overall quality of their work, providing them with significant business benefits and a competitive edge in the industry.

Real-World Impact of AI in EPC

Dzhusupova鈥檚 thesis further demonstrated how AI applications could help solve the complicated problems that arose in real-world EPC projects.

By using real examples and research, the study proved that AI could change the way projects were managed and executed in the EPC field.

This work not only built on existing academic knowledge but also provided useful advice for industry professionals, making it easier for them to apply AI in their projects.

Using AI: A Way to Improve EPC Projects

In conclusion, Dzhusupova鈥檚 research demonstrated how important it is for the EPC industry to embrace new digital technologies, especially AI.

By using AI in a smart way, companies could greatly improve the efficiency and safety of their projects, helping them remain competitive in a fast-changing world. This research provided a clear guide for adopting AI and highlighted its real benefits in making large projects more effective.

Ultimately, it encouraged ongoing innovation and improvements in AI that would help the EPC industry become even better at what it did.


Title of PhD thesis:
Supervisors: prof.dr.ir. J. Bosch, Prof. Dr. H. Holmstr枚m Olsson

Short interview with Rimma Dzhusupova:

What is the most important finding from your research, and how could it affect society in a way that everyone can understand?
鈥淭he most relevant outcome from my research is the development of AI applications that automate manual tasks and support core processes in large-scale engineering and construction projects. These applications improve project efficiency, enhance accuracy, reduce costs, and allow human resources to focus on more strategic tasks. The broader societal impact lies in showing on real cases how AI can transform the engineering profession by automating repetitive tasks, thereby giving engineers more space to focus on uniquely human activities, such as creativity and innovation.鈥�

What was the most significant finding from your research, and what aspects turned out to be most important to you?
鈥淭he most significant finding from my research was proving the tangible benefits of AI integration in the engineering and construction sector. It demonstrates how AI can bridge the gap between theoretical potential and practical application, delivering real-world value in operational contexts.鈥�

What was your motivation to work on this research project?
鈥淢y motivation to work on this research project grew from recognizing the potential of AI in the engineering and construction industry within the energy sector. This traditionally conservative industry, despite numerous white papers and roadmaps outlining AI鈥檚 transformative potential, has seen very few real-life implementations. This gap revealed a clear niche in research that could directly influence decisions on AI implementation and deployment in the sector.鈥�

What was the greatest obstacle that you met on the PhD journey?
鈥淭he greatest obstacle I faced during my PhD was the gap between the hype surrounding AI and the low readiness of companies to integrate it. While AI is seen as transformative, many organizations lacked the digital infrastructure and were unprepared for the structural changes required for implementation. This disconnect between high expectations and practical readiness made it challenging to demonstrate AI's real-world value and align the company stakeholders, where the research was conducted, with realistic outcomes.鈥�

What are your plans for after your PhD research?
鈥淪ince I am already working in the industry as an AI lead within an engineering and construction company while pursuing my PhD, my plan is to continue bridging the gap between academic research and practical implementation. My intentions are to stay connected with 果冻传媒 and share my knowledge and practical experience with the next generation of master鈥檚 and bachelor鈥檚 students through mentoring and guest lecturing.鈥�