Integrating AI Technologies into Academic Writing and Research Workflows in Science and Technology: A Productivity Enhancing Approach
Year: 2026
Type: article
Study design: Observational Study
Abstract: Academic writing in science and technology demands structured expression, evidence-based reasoning, and the ability to manage complex ideas and large volumes of information. However, these processes are often time-consuming and challenging. This study examined the integration of Artificial Intelligence (AI) technologies into academic writing and research workflows in science and technology as a productivity-enhancing approach. Specifically, it explored the awareness of AI tools among scholars and their perceived usefulness in improving research output. Guided by the Technology Acceptance Model (TAM), a sample of 364 respondents was selected using the Taro Yamane formula. Data were collected through structured questionnaires and analyzed using descriptive statistics, mean scores, and standard deviations. Findings revealed high awareness and frequent use of AI tools such as ChatGPT, Grammarly, Grammarly Plagiarism Checker, EndNote, Turnitin, Excel Plugins, Python Libraries, and SciBERT/Semantic Scholar. Respondents reported that AI tools significantly improve the quality of academic writing, reduce grammar and referencing errors, accelerate task completion, and allow greater focus on creative and experimental work. The results also indicated that AI tools are generally easy to learn and integrate into existing research workflows. The study concludes that AI has become a valuable ally in enhancing the efficiency, accuracy, and creativity of academic writing and research in science and technology. It recommends targeted training, institutional investment in AI resources, and the establishment of clear ethical guidelines to ensure responsible adoption.
Source: Advances in Research
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7155220803
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