May 08, 2026
Prompt Engineering in Corporate Tourism Project Management
Jaqueline Martini Gomes; Denis Bruno Viríssimo
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Technological evolution and globalization have reinforced the role of project management in organizational growth and performance. In an increasingly volatile, uncertain, complex, and ambiguous scenario, this approach has become an essential tool for professionals who need to adapt quickly to changes (Moura et al., 2023). Efficient project management is fundamental for the organization’s survival in a competitive market, strengthening organizational management as a competitive differentiator (Carneiro and Souza, 2020). Given this dynamic context, the definition and structuring of projects become essential to ensure their efficient execution. A project is characterized as a temporary endeavor undertaken to create a unique product, service, or result (PMI, 2021). Its temporary nature implies that it has a well-defined beginning and end, and it can be an isolated initiative or integrate a program or portfolio of projects (PMI, 2021).
One sector that strongly demands project management is tourism, which involves strategic planning of infrastructure, events, and services to meet an increasingly demanding and connected audience (Alves, 2024). Tourism is characterized by the temporary movement of people outside their usual environment for up to one consecutive year (Guizi, 2024). This mobility drives economic sectors, especially the service sector, promoting local development, income generation, increased employability, and social advancement (Guizi, 2024). Corporate tourism is one of the most profitable segments of the sector, requiring companies to develop innovative strategies to maintain competitiveness (Ferreira, 2014). Understanding customer profiles and developing effective solutions are essential factors for meeting market needs.
Despite the growing importance of project management, many companies still face difficulties in formalizing and standardizing strategic documents, resulting in project delays and failures. Challenges in project management include non-compliance with deadlines, cited in 60.2% of responses in sectoral surveys, while inadequately defined scope appears as a significant obstacle in 39.5% of cases (Terribili Filho, 2013). Both problems are directly related to the elaboration of project documents, highlighting the importance of precision and standardization in documentation to avoid future bottlenecks. As a resource to improve this routine, artificial intelligence has become a fundamental pillar in project management, enhancing workflow optimization, efficient resource allocation, and improved decision-making (Weng, 2023). By automating repetitive tasks, artificial intelligence not only reduces manual effort and the incidence of human errors but also frees up project managers to focus on higher-impact strategic activities.
Professionals who used artificial intelligence as a complement to their activities completed 12% more tasks, were 25% faster, and achieved 40% higher performance (Dell’Acqua et al., 2023). An essential practice for improving accuracy and effectiveness in using artificial intelligence is prompt engineering. This is defined as the science and art of designing, formatting, and optimizing conversational commands to enhance interaction with artificial intelligence or machine learning models (Schmidt et al., 2024). This process involves creating stimuli or instructions through natural language inputs, which guide systems in generating specific and relevant responses.
Comparative studies between the application of artificial intelligence and a project manager for the elaboration of the project plan show that both have strengths and weaknesses, indicating complementarity in the planning process (Barcaui and Monat, 2023). Artificial intelligence plays a crucial role in increasing project efficiency by reducing deadlines, improving cost control, and optimizing resources (Hossain et al., 2024). For the creation of effective commands, a structure based on role, request, context, format, and tone is proposed (Bainey, 2024). Well-crafted prompts optimize time, communication, and decision-making, reinforcing prompt engineering as a strategic tool aligned with the use of generative artificial intelligence.
To deepen the subject studied, an exploratory research was conducted with the objective of understanding prompt engineering and generative artificial intelligence applied to the elaboration of management documents. Bibliographic research based on already published materials, such as books, journals, and academic texts, was adopted. The procedure was configured as a case study, understood as an empirical investigation focused on the in-depth analysis of a phenomenon in its real context (Gil, 2017). Quantitative and qualitative analysis techniques were applied to broaden the understanding of the object. In quantitative research, categories are defined in advance, while in qualitative research, initial categories undergo continuous revisions to achieve a broader understanding (Gil, 2017).
Two surveys were conducted with collaborators from different areas of the corporate tourism sector, who act punctually or collaboratively on project-related initiatives. Data collection was carried out through structured questionnaires to ensure standardization. The first survey measured the efficiency of using generative artificial intelligence in supporting document elaboration. Participants evaluated the assertiveness and feasibility of the content, in addition to timing manual production compared to AI-assisted production. This procedure allowed for qualitative insights into clarity, adherence, and usefulness, as well as quantitative data on elaboration time.
The second survey focused on the qualitative evaluation of the generated documents. Experts with experience in project management analyzed the materials and issued critical opinions regarding clarity, adherence, and practical usefulness. This stage provided an additional layer of validation that reinforced methodological consistency. The ChatGPT-4 model was used for prompt configuration, developing structured instructions for the Project Charter, Project Breakdown Structure, and Meeting Minutes. Prompt engineering was applied to ensure that the responses were accurate, relevant, and aligned with the proposed objective, allowing for customization according to the field of application (Nascimento, 2024; Singh et al., 2024).
The definition of prompts was based on consolidated methods. Role-Playing Prompting was used to instruct the artificial intelligence to adopt the role of a senior project manager with experience in corporate tourism (Nascimento, 2024; Kong et al., 2024). Few-shot Prompting consisted of providing explicit examples of the expected structure, with detailed instructions on format and mandatory elements (Nascimento, 2024; Sahoo et al., 2025). Zero-shot Prompting was employed in tests to evaluate the model’s ability to perform tasks based solely on its prior knowledge (Singh et al., 2024). Finally, Iterative Prompting allowed for progressive refinement of commands after each interaction to increase the clarity and quality of responses (Nascimento, 2024; Sahoo et al., 2025).
The elaboration of prompts was guided by three fundamental documents. The Project Charter formalizes the initiative’s start and assigns authority to the manager (PMI, 2021). The Project Breakdown Structure organizes the scope into successive levels of detail to facilitate management (PMI, 2021). The Meeting Minutes formally record discussed matters and decisions made, being essential for traceability (Molina et al., 2021). The generated documents were based on a hypothetical project titled Implementation of the Intelligent Copilot for Corporate Travel, which simulates the adoption of an artificial intelligence tool for internal use by travel consultants. The project included deliverables such as policy templates, backlog structuring, communication campaigns, and training, with a planned schedule between May and December 2025.
During prompt configuration, it was identified that the model presented limitations in replicating specific formatting in text files, which required more careful commands. The tool was also used to evaluate the clarity of the prompts themselves to identify interpretation bottlenecks. The tests and data collection involved professionals from multiple departments, reflecting a realistic corporate environment scenario. Participants received the same standardized inputs and prompts, and were instructed to prepare the documents manually and, subsequently, with the support of artificial intelligence, recording the time spent on each step. After receiving the text, they made the necessary adjustments and evaluated the quality and fidelity of the material.
The research sample consisted of professionals from different areas linked to the corporate tourism sector. A predominance of participants aged between 26 and 35 years was observed, followed by the group up to 25 years old. Regarding project experience, most indicated up to one year of activity, followed by those with experience between one and three years. All respondents stated they already use generative artificial intelligence tools in professional or personal activities, which contributes to the legitimacy of the responses. Approximately 81% of participants declared using these tools for more than six months, evidencing a continuous usage history that favors the evaluation of prompt application.
The practical stage included a balanced distribution among the types of documents tested. In manual production, 29% of participants took more than two hours to complete the task, 29% indicated up to two hours, 28% pointed to a duration of up to one hour, and 14% reported completion in up to 30 minutes. This data highlights the high dedication required by the traditional method. Cross-analysis between execution time and experience revealed that beginners concentrate on deadlines exceeding two hours, while seniors show greater performance variation. The learning curve directly influences productivity in the manual method.
In contrast, 67% of participants completed the document generation with the support of artificial intelligence in less than five minutes. Another 24% indicated a time between five and ten minutes, while only 9% took ten to 20 minutes. This significant reduction in production time reinforces the potential of automation. Unlike the manual process, assisted production showed homogeneous results regardless of the professional’s experience level. The technology reduced the learning curve and equalized productivity, neutralizing the discrepancies observed in the traditional method.
Regarding the need for adjustments, for 33% of participants, the generated content was ready for use. The majority, representing 53%, made only minor adjustments to spelling or formatting, while 14% needed to alter significant parts. No participant reported the need to rewrite the document entirely, indicating a high level of usability. The assertiveness of the content was evaluated as excellent by 76% of respondents, good by 19%, and regular by 5%. There were no negative evaluations, reinforcing the perceived quality.
The solution’s acceptance was high, with 71% of participants stating they would definitely recommend using the prompt to other professionals. The remaining 29% indicated recommendation with reservations. Participants reported adequate adherence of the content to the work context, highlighting clarity and organization. Suggestions for improvement focused on visual adjustments and dividing prompts into smaller blocks to facilitate processing. The need to make content more detailed for individuals who did not directly participate in the project was also emphasized.
The results converge with previous studies that evaluated project plans developed by artificial intelligence and by certified managers (Barcaui and Monat, 2023). In that comparison, artificial intelligence produced a broader analytical structure, with 13 deliverables versus six from the human. The iterative prompt refinement process was decisive in elevating the quality of the deliverables. Although technology offers greater speed, human intervention remains essential for market contextualization and definition of specific objectives, reinforcing the importance of the human-supervised approach to ensure organizational alignment.
The external perception of project management professionals who did not participate in the initial stage validated the consistency of the documents. This control group showed a higher concentration in the age groups of 26 to 45 years, representing professionals in intermediate career stages. Approximately 46% of these professionals have more than three years of experience in projects, which contributes to consistent analyses. Regarding the use of artificial intelligence, 46% have been using the tools for more than six months. The evaluation of this group confirmed the homogeneity in the analysis of different documentary models.
Assertiveness was classified as excellent by 52% of external specialists and as good by 44%. Only 4% considered the content regular. Regarding recommendation, 78% indicated that they would certainly recommend the use of prompts. This data corroborates the effectiveness of prompt engineering in reducing deadlines and improving accuracy. Significant gains in efficiency and quality were observed, with deadline reductions of up to 20% and improved resource allocation by up to 35% (Hossain et al., 2024).
The application of prompt engineering favors document standardization and contributes to error mitigation. The use of generative artificial intelligence as a tool for continuous refinement is essential for obtaining satisfactory results. Limitations were observed related to the model’s difficulty in reproducing certain formats, which indicates that the quality of the results is conditioned by the precision of the instructions and the model’s training. Critical review and human experience are indispensable to ensure documentary compliance and the evolution of the prompts used.
From an applied perspective, prompt engineering can be incorporated as a strategic support tool in corporate tourism companies, strengthening operational efficiency and qualifying decision-making. The space for professionals to act more analytically on the generated documents expands opportunities for continuous improvement and greater added value to deliverables. Time savings exceeding 90% in the elaboration of strategic documents represent an unprecedented productivity gain for the project management area.
It is recommended to conduct research with broader samples and apply it to real cases of complex projects to consolidate the applicability of the solution. Expanding the use of prompt engineering in different project management documentation formats may reveal new possibilities for automation and optimization. The balanced integration of technology and human expertise enhances process reliability and ensures that organizational objectives are achieved with greater precision and less operational effort.
It is concluded that the objective was achieved, demonstrating that prompt engineering integrated with generative artificial intelligence is a consistent and effective alternative for optimizing the elaboration of project management documents in the corporate tourism sector. The results showed a drastic reduction in document production time, while maintaining high levels of assertiveness and technical quality. The solution was widely accepted by experienced and novice professionals, equalizing productivity and mitigating common standardization flaws. Human intervention remains fundamental for refining commands and strategic contextualization, consolidating technology as an indispensable support for operational efficiency and innovation in contemporary project management.
Bibliographic References:
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Executive summary from the Final Course Work of the Specialization in Project Management of the MBA USP/Esalq
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