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This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study aims to explore how achieving a harmonious work–life balance (WLB) can enhance the business performance of women entrepreneurs in the United Arab Emirates (UAE). Using border theory as a framework, it investigates the specific challenges and strategies these entrepreneurs use to manage their dual roles in professional and personal domains.

This qualitative study uses in-depth interviews with 50 women entrepreneurs across various ages, nationalities and business types in the UAE. Purposeful sampling was used to ensure a diverse range of viewpoints.

The study finds that maintaining a WLB is crucial for the success and growth of women entrepreneurs in the UAE. A balanced work-life leads to higher job satisfaction, improved work quality and increased customer satisfaction, which collectively drive business success. Conversely, a lack of WLB results in stress, burnout and reduced productivity, negatively impacting business outcomes. Thus, WLB is essential for the well-being, efficiency and overall success of women entrepreneurs.

This research extends border theory by examining how women entrepreneurs, a unique workforce segment, balance their professional and personal lives in the UAE’s distinct socio-cultural context. It offers new insights into the challenges and strategies of achieving WLB, highlighting the significant role of family support and technology in this process. The study also underscores the importance of WLB for women’s entrepreneurship, contributing to broader discussions on gender, work–life integration and entrepreneurial success.