Generative artificial intelligence in the elaboration of the Communication Management Plan and the Stakeholder Matrix in projects

doi:10.22167/2675-6528-202602682

Article

September 30, 2026

Generative artificial intelligence in the elaboration of the Communication Management Plan and the Stakeholder Matrix in projects

Generative Artificial Intelligence in the Elaboration of the Communication Management Plan and the Stakeholder Matrix in Projects

Andressa Pereira Bernardo Ximenes; Maria Valeria Espinos Guerra Martins

DOI: 10.22167/2675-6528-202602682

Article derived from a Course Conclusion Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Summary

Communication failures represent one of the main causes of project failure, a scenario aggravated by the increasing complexity of environments and the need for continuous alignment. In this context, generative artificial intelligence (AI) has emerged as a transformative opportunity in project management. The research aimed to analyze the contribution of generative AI in the elaboration of the Communication Management Plan and the Stakeholder Matrix, evaluating its practical viability and the professionals’ acceptance of the technology. A quali-quantitative approach was adopted, combining a literature review, practical application of generative AI in the construction of a Stakeholder Matrix for a fictitious project, and an exploratory survey with 10 professionals in the field. The results indicated that communication failures are recurrent and that few use formalized plans. Generative AI demonstrated the ability to support initial structuring, format standardization, and language adaptation, although with limitations in strategic tasks. Professionals expressed openness to adopting the technology, conditioned on training and clear organizational policies. It was concluded that generative AI is a promising tool for optimizing communication management in projects, contributing to the understanding of its benefits, limitations, and conditions for safe and effective incorporation.

Keywords: Project Management; Generative AI; Artificial Intelligence; Stakeholder Matrix; Communication Plan.

1. Introduction

Communication is widely recognized as one of the fundamental pillars of project management, with its failures being among the most recurrent causes of failure in organizations of various sizes and sectors. Surveys by the Project Management Institute (PMI) (2014) with 400 organizations revealed that 64.2% of companies identified communication as one of the most frequent problems in their projects. Furthermore, 44% pointed to it as the main deficiency in management. PMI-Rio research reinforces this perspective, indicating that communication is the second biggest factor of problems in projects, surpassed only by deadline non-compliance, and it is also the second least discussed factor in the planning phase. This data highlights a structural gap between the recognized importance of communication and the attention effectively devoted to it in project management practice.

This gap is exacerbated by the growing complexity of project environments, which involve multiple stakeholders, intense information flows, and the need for continuous alignment between teams. In this context, tools such as the Communication Management Plan and the Stakeholder Matrix become essential for structuring and standardizing information flows throughout the project lifecycle, contributing to the alignment of expectations and the clear definition of responsibilities among those involved. The exploratory research conducted for this work corroborates this perspective, indicating that most professionals do not use or rarely use a formalized Communication Management Plan, and points to information overload, communication noise, and lack of channel standardization as main challenges.

In view of this scenario, generative artificial intelligence (AI) emerges as a promising alternative to support the construction and execution of the Communication Management Plan. As pointed out by Vanzolini (2024), AI applied to project management contributes to the automation of repetitive tasks, allowing managers to direct their attention to strategic activities, while the use of real-time data improves assertiveness in schedules, budgets, and risk anticipation. In the specific scope of communication, generative AI tools have shown potential to support the elaboration of communications, language adaptation by audience, synthesis of extensive documents, and agile information recording among teams. Participants in the exploratory research demonstrated a high level of familiarity with tools such as ChatGPT and Microsoft Copilot, and signaled willingness to adopt them in project communication activities, albeit conditioned by aspects such as data security, organizational restrictions, and the need for adequate training.

Considering the relevance of communication for project success, the low adoption of formalized communication management tools, and the growing interest in the use of generative AI in this context, this research aims to analyze how generative AI can contribute to the elaboration and optimization of the Communication Management Plan and the Stakeholder Matrix, evaluating its practical viability and the degree of openness of professionals in the field to the adoption of this technology.

2. Material and Methods

The present research was developed with a quali-quantitative approach, adopting the strategy of applied research based on simulation. This design sought not only to understand a practical problem in project communication management but also to simulate an intervention through the application of generative artificial intelligence (AI) tools. Applied research was oriented towards the solution of concrete problems and the generation of knowledge with potential for practical use, according to the established objectives.

The investigation was structured into three complementary fronts to address the proposed objective. The first front consisted of a comprehensive literature review. The second involved a practical application with generative AI. Finally, the third front comprised an exploratory survey of perceptions among project management professionals. Each of these fronts contributed distinctly to data collection and analysis.

The first methodological front consisted of a bibliographic review of the literature pertinent to communication management in projects and generative artificial intelligence. Scientific publications on the Communication Management Plan and the Stakeholder Matrix were consulted, based on the guidelines of the Project Management Institute (PMI) (2014). Additionally, references on generative AI and its applications in organizational and professional contexts were included, based on Vanzolini (2024). This review provided the theoretical basis for the construction of the research instruments and for the critical analysis of the collected data.

The second front involved the practical application of the generative AI Claude for the construction of a Stakeholder Matrix and a Communication Management Plan. These instruments were developed from a fictitious project, created specifically for the research. The choice of a fictitious project aimed to ensure the confidentiality of information and allow the replication of the process by other professionals, ensuring the methodological validity of the simulation.

The practical application process was divided into three sequential stages. In the first stage, the fictitious project, named “Renovation and Modernization of the Headquarters Building of a Municipal City Hall”, was defined and contextualized. A contextualization document was prepared that served as input for the AI, containing information such as the project name and objective, scope of works, a 10-month deadline, an estimated budget of R$ 4.8 million, generic location in a city in the interior of the State of São Paulo, organizational structure of the city hall, and main legal and institutional constraints.

In the second stage, the Stakeholder Matrix was built with the support of AI. A structured prompt was elaborated to guide Claude in identifying the relevant stakeholders. For each stakeholder, information was requested such as name or group, role in the project, level of interest and influence (high, medium, or low), main expectations, associated risks, engagement strategy, communication need, channel, and frequency, and communication responsible. The resulting Stakeholder Matrix identified 12 stakeholders, classified according to the PMI (2021) model into four quadrants of interest and influence.

In the third stage, the Communication Management Plan was developed, using the validated Stakeholder Matrix as direct input. A specific prompt was formulated for Claude, requesting a complete plan with seven dimensions: plan objective, communication premises and constraints, communication matrix detailed by stakeholder, project meeting types, issue escalation flow, guidelines for generative AI use (including supported activities and human validation protocol), and communication effectiveness indicators. The AI-generated outputs were analyzed based on the concepts from the literature review to assess the feasibility and limitations of the technology in project communication management.

The third front consisted of conducting an exploratory qualitative survey, through the application of a structured questionnaire. The instrument was developed and made available digitally to professionals who work or have worked in project management. The objective was to capture initial perceptions about the communication challenges faced daily, the level of familiarity with generative AI tools, and the degree of openness to their professional adoption.

The study population was composed of project management professionals. The sample was intentional and included 10 respondents, mostly working in the engineering sector, with different levels of experience. Participation was voluntary, and the data collected were treated anonymously and confidentially, in accordance with the ethical principles established by Resolutions of the National Health Council (CNS) No. 466/2012 and No. 510/2016, which regulate research involving human beings. The exploratory nature of the sample does not allow for statistical generalizations, but it offers relevant initial insights (Gil, 2002).

The data collected through the questionnaire were organized and analyzed descriptively. The analysis focused on identifying perception patterns and the main convergences and divergences among respondents. The interpretation of the data was carried out in light of the theoretical framework raised, integrating the results of the exploratory survey with the findings from the practical application of generative AI, aiming for a comprehensive and coherent analysis aligned with the research objectives.

3. Results and Discussion

The results of this research are presented through three complementary fronts, which interconnect and mutually reinforce each other. The literature review established the theoretical framework that underpinned the construction of the instruments used in the practical application and in the elaboration of the exploratory survey questionnaire. In turn, the data collected in the survey confirmed the gaps and challenges identified in the literature, while validating the relevance of the products developed in the practical application of generative artificial intelligence. This integrated approach allowed for a comprehensive analysis consistent with the objectives proposed by the study.

Bibliographic review

The literature review consolidated the essential theoretical framework for understanding communication management in projects and generative artificial intelligence. The Project Management Institute (PMI, 2021) emphasizes communication as a critical performance domain, responsible for ensuring that the correct information reaches stakeholders at the opportune time and through the most effective channel. This perspective highlights that communication is not a spontaneous process, but an area that demands deliberate planning, structured tools, and clearly defined responsibilities, principles that guided the construction of the practical artifacts of this research.

The consulted literature has extensively documented the negative impacts of communication failures in projects. Cyganczuk et al. (2018) observed that communication problems are associated with team demotivation, deadline delays, and compromised delivery quality, representing a frequent and high-impact barrier. This finding is corroborated by a survey by PMI (2014) with 400 organizations, where 64.2% identified communication as one of the most recurrent problems and 44% pointed to it as the main deficiency in project management, highlighting a persistent gap in practice.

In the context of generative artificial intelligence, Verrel and Julkovski (2024) highlighted its operational benefits in project management, such as improved schedule predictability, task automation, and technological integration. However, they warned of challenges like data security, cultural resistance, and the need for team training. The Brazilian Institute of Corporate Governance (IBGC, 2025) reinforces the urgency of AI training in Brazil and the importance of clear usage policies. Vanzolini (2024) complements this, indicating that generative AI can automate repetitive tasks, adapt language to the audience, and synthesize extensive documents, functions that were tested and validated in the practical application of this study.

Practical application with generative AI

The practical application stage was designed to test, in a controlled environment, the capacity of generative AI to assist in the creation of communication management instruments, based on the theoretical framework. For this purpose, a fictitious project for the Renovation and Modernization of the Headquarters Building of a Municipal Prefecture was used. The choice of this scenario in the public sector, with multiple stakeholders and varying levels of interest and influence, sought to replicate the communication complexity frequently associated with failures, as identified in the literature. The process was divided into three sequential stages to ensure the systematicity of the analysis.

Step 1 – Definition and contextualization of the fictitious project

The first stage consisted of the elaboration of a detailed document for the contextualization of the fictitious project, which served as input for the AI. Crucial information was provided, including the project name, its objective, the scope of works, an estimated deadline of 10 months, and a budget of R$ 4.8 million. Furthermore, the generic location in an inland city of São Paulo, the organizational structure of the involved city hall, and the main legal and institutional constraints were specified. This data allowed the generative AI to process a realistic scenario for the construction of the communication artifacts.

Step 2 – Construction of the Stakeholder Matrix with AI support

With the project context established, a structured prompt was provided to the generative AI tool Claude to elaborate the Stakeholder Matrix. The prompt instructed the AI to act as a project management expert, based on PMI best practices, and to identify all relevant stakeholders. For each stakeholder, the AI should report the name or group, role in the project, levels of interest and influence (high, medium, or low), main expectations, associated risks, engagement strategy, need, communication channel and frequency, and the person responsible for communication, organizing the response in a table format.

The AI-generated Stakeholder Matrix identified 12 stakeholders, classifying them into four quadrants of interest and influence, according to the PMI (2021) model. In the “High interest / High influence” quadrant, which requires close management, the Municipal Mayor, the Secretariat of Works, the Project Manager, and the Municipal Chamber were listed. For the “High interest / Low influence” quadrant, with the strategy of keeping informed, public servants, citizens and users, and the technical works team were identified. In the “Low interest / High influence” group, with the strategy of keeping satisfied, the AI included the Court of Accounts of the State of São Paulo (TCE-SP), the Secretariat of Finance, the Fire Department, and the contracted company. Finally, for “Low interest / Low influence”, with the strategy of monitoring, suppliers and subcontractors were indicated.

AI demonstrated a satisfactory capability in structuring and classifying stakeholders, aligning with best practices in the field, especially for those with more standardized profiles. However, for stakeholders with more complex dynamics, such as the TCE-SP, the Municipal Chamber, and affected communities, the generated results required review and enrichment by the human manager. This finding corroborates the perspective of Verrel and Julkovski (2024), who emphasize the greater effectiveness of AI when combined with the specific knowledge and expertise of the manager responsible for the project, indicating that the tool acts as a support, rather than a complete substitute for human judgment.

Step 3 – Construction of the Communication Management Plan with AI support

With the Stakeholder Matrix validated, it was used as direct input for the construction of the Communication Management Plan. The prompt provided to the AI requested the elaboration of a complete plan, considering the public project and the oversight of the TCE-SP, with communication adapted to different audiences. The plan should contain seven dimensions: objective, premises and constraints, detailed communication matrix (type, content, channel, format, frequency, responsible party), types of meetings, issue escalation flow, guidelines for AI use (supported activities and human validation protocol), and communication effectiveness indicators.

The resulting Communication Management Plan was structured into seven dimensions, and the generated Communication Matrix defined specific standards for each stakeholder. For the Municipal Mayor, formal communication via meeting and PDF, monthly, with executive reports and critical alerts, under the responsibility of the Project Manager. The Secretariat of Works would receive formal communication by meeting and email, weekly, with technical reports, minutes, and non-conformities, also by the Project Manager. The Municipal Chamber would have formal communication via official letter and PDF, bimonthly, with accountability and addenda, under the responsibility of the Secretariat of Works. The TCE-SP, with formal and legal communication, would use the TCE-SP system, on demand, for bidding documentation and contracts, with the Secretariat of Finance as the responsible party.

The Communication Matrix also detailed that the Finance Secretariat would receive formal communication via email and report, monthly, with a physical-financial schedule and measurements, from the Project Manager. The Contracted Company would have formal and operational communication via meetings and email, weekly, with service orders and minutes, also from the Project Manager. The Technical Team, with operational communication, would participate in daily meetings, receiving instructions, safety information, and pending issues, under the technician’s responsibility. Public Servants would be informed via email and intranet, bi-weekly, about construction stages and interruptions, by the Public Works Secretariat. Finally, Citizens and Users would receive information via website and social media, monthly, about service operations, with the Advisory Department being responsible.

AI demonstrated a significant contribution in generating the minutes for each dimension of the plan, in standardizing communication formats, and in adapting language for different stakeholder profiles. However, dimensions such as the problem escalation flow, governance guidelines for the use of AI itself, and effectiveness indicators demanded more substantial human intervention. This is due to the fact that these tasks involve strategic decisions that go beyond the current capabilities of generative tools, a finding that aligns with IBGC (2025) recommendations on the need for governance structures to ensure human validation of critical decisions.

Exploratory survey of perceptions

The exploratory survey was designed to investigate the gaps identified in the literature review and practical application, seeking to understand how the perceptions of professionals in the field aligned or diverged from the mapped problems and potentials. The research involved the participation of 10 professionals who work or have worked in project management. The predominant profile of the respondents indicated that 90% work in the engineering sector and 10% in healthcare. Regarding years of experience, 20% had less than 1 year of experience, 30% between 1 and 3 years, 30% between 3 and 5 years, and 20% between 5 and 10 years. The majority, 80%, did not have project management certification, while 20% did. Regarding the average team size, 40% worked in teams of up to 5 people, 20% in teams of 6 to 15, 20% in teams of 16 to 30, and 20% in teams with more than 30 people.

It is fundamental to reiterate that this survey has an exploratory nature, with an intentional and reduced sample, not allowing generalizations to the universe of professionals in the area. The results should be interpreted as initial perceptions that enrich the understanding of the investigated problem, in line with the nature of exploratory research, as described by Gil (2002). This limitation is crucial for contextualizing the data analysis and guiding future investigations with broader scope.

The evaluation of communication effectiveness in projects, on a scale of 1 to 5, revealed that 50% of respondents considered it “Moderate” (score 3). Only 20% rated it as “Effective” (score 4) and 10% as “Very effective” (score 5). In contrast, 10% rated it as “Ineffective” (score 2) and 10% as “Very ineffective” (score 1). This data indicates that the majority of professionals perceive communication in their projects with an intermediate level of effectiveness, suggesting significant room for improvement and formalization of processes.

The perception of moderate communication effectiveness, with half of the respondents assigning a score of 3, confirms, in the exploratory context of this research, the trend of recurrent dissatisfaction with the quality of communicative processes in projects. This finding directly dialogues with the observations of Cyganczuk et al. (2018), who identified communication problems as one of the most frequent and impactful barriers in project management. The persistence of this perception reinforces the need for instruments and practices that can optimize communication.

The main communication challenges pointed out by respondents were “Excess of information and noise in communication”, mentioned by 50% of participants, and “Lack of standardization in communication channels”, indicated by 40%. Other relevant challenges, cited by 30% of respondents each, included “Lack of clarity in transmitted messages”, “Difficulty in reaching all stakeholders”, and “Delays in sending updates and reports”. Only 10% mentioned “Other” challenges, indicating a concentration in the main categories.

These challenges identified by professionals bear a direct correspondence with the problems that the Communication Management Plan, developed in the practical application stage, seeks to address. The excess of information and noise is treated by defining content delimited by stakeholder, while the lack of standardization is resolved by the Communication Matrix. The difficulty in reaching all stakeholders, in turn, is addressed by the systematic classification of interested parties. This convergence reinforces that the instruments developed with the support of generative AI respond to real and perceived needs by professionals in the field, validating the relevance of the proposed intervention.

Regarding the frequency of communication failures, 40% of respondents stated that they occur “Frequently” and another 40% that they happen “Sometimes”, totaling 80% who face failures with some regularity. Only 10% reported failures “Rarely” and 10% “Never”. As for the use of the Communication Management Plan, only 20% stated they use it “Yes, always”, while 20% use it “Rarely”. Worryingly, 40% “Do not use” and 20% “Did not know” such a document existed, evidencing a low formalization and knowledge about this essential tool.

The fact that 80% of respondents face communication failures with some regularity, combined with the fact that only 20% use a formalized Communication Management Plan, reveals a significant gap between the perception of the problem and the adoption of tools for its treatment. This gap is analogous to that identified by PMI (2014) on a broad scale and by Cyganczuk et al. (2018) in the context of Brazilian project managers. The finding that 20% of respondents were unaware of the document’s existence is particularly relevant, suggesting that the lack of formalization of communication in projects is not just a conscious choice, but often a reflection of ignorance about the available tools.

Regarding the use of generative AI tools in a professional context, 50% of respondents stated they use them “regularly”, and 30% have used them “a few times”, totaling 80% with some experience. Only 10% have tried them but do not use them at work, and 10% are unaware of the tools. The most adopted tools were ChatGPT (60%) and Microsoft Copilot (60%), followed by Gemini (40%), Claude (10%), and Notebook LM (10%). The communication activities most supported by AI were “Drafting emails and reports” (70%), “Adapting language for audience” (50%), and “Summarizing extensive documents” (40%), followed by “Drafting meeting minutes” (30%) and “Creating status reports” (20%).

The data reveal that 80% of respondents already use AI in a professional context, with ChatGPT and Microsoft Copilot being the most adopted tools, which aligns with the practical test conducted in this research. The three most indicated activities for AI use — drafting emails, adapting language, and synthesizing documents — correspond exactly to the functions foreseen in the guidelines for the use of generative AI incorporated into the Communication Management Plan developed. This demonstrates a clear synergy between AI capabilities and the practical needs of professionals, validating the technology’s potential to optimize these tasks.

The evaluation of the results obtained with the use of AI in communication was predominantly positive, with 50% classifying them as “Good” (met the need with minor adjustments) and 30% as “Fair” (I needed to revise and adapt considerably). No respondent rated the result as “Poor”. However, 90% identified at least one relevant risk. Perceived risks included “Inaccurate or incorrect results generated by AI” (30%), “Organizational restrictions — internal policy and data security” (30%), “Loss of human interaction in communication” (20%), and “Over-reliance on technology” (20%). Only 10% see no significant risks.

These risks perceived by professionals are consistent with the challenges of AI implementation identified by Verrel and Julkovski (2024), who highlight aspects such as data security and cultural resistance. They also align with the IBGC’s (2025) recommendations on the need for clear organizational policies for the safe and strategic use of AI. The conditions considered most important for the successful incorporation of AI into the Communication Management Plan were “Team training for the use of tools” (70%), “Clear definition of which tasks will be supported by AI” (50%), “Human validation of AI-generated content” (40%), and “Organizational policy that authorizes and regulates its use” (40%). The “Choice of tools appropriate to the project context” and “Integration of AI tools with existing systems” were cited by 30% of respondents each.

Team training was pointed out as the most important condition by 70% of respondents, a result that converges with IBGC’s (2025) warning about the urgency of AI training in Brazil. The need for a clear definition of the scope of use and human validation, indicated by 50% and 40% respectively, reinforces Verrel and Julkovski’s (2024) perspective that the biggest challenges in implementing AI in organizations are not technological, but predominantly human and cultural. Finally, 100% of respondents stated they were willing to adopt or expand the use of AI in their project communication, with 50% definitively and 50% conditionally based on aspects such as cost, security, and adequate training.

In summary, the results from the three fronts of this research converge on the conclusion that communication failures in projects are recurrent and widely recognized, being amenable to mitigation through the adoption of structured management tools. Generative artificial intelligence has demonstrated a real capacity to support the construction of these tools in an agile and coherent manner with best practices in the field, contributing to the standardization and adaptation of language. However, its limitations are concentrated in activities that require strategic judgment, deep contextual knowledge, and institutional responsibility, demanding human validation. Although the findings are exploratory and based on a small sample, they indicate a promising path for optimizing communication in projects, highlighting the importance of future studies with broader scope to confirm these trends.

4. Conclusion

This research aimed to analyze the contribution of generative artificial intelligence in the development of the Communication Management Plan and the Stakeholder Matrix, as well as to evaluate its practical viability and the acceptance of professionals in the field. It was found that communication failures are recurrent in projects, with low formalization of management plans, and that generative AI demonstrated the capacity to support initial structuring, format standardization, and language adaptation in both instruments. It was observed that the tool is effective for operational tasks, but its limitations manifested in activities requiring strategic judgment, in-depth contextual knowledge, and institutional responsibility. Most professionals in the field already use AI in a professional context and expressed a high willingness for its adoption, conditioned on aspects such as training and clear organizational policies.

The study’s main contribution lies in demonstrating that generative AI represents a promising tool for optimizing communication management in projects, by reducing the time spent on preparing structured instruments and standardizing communications. However, its effective incorporation requires planning, governance, and human training. It is important to note that, due to the exploratory nature of the survey and the small sample size, the findings should be interpreted with caution. Future studies are suggested with larger and more diverse samples, the application of instruments in real projects, and the longitudinal evaluation of results obtained with the use of generative AI throughout the lifecycle of projects of different sizes and sectors, in order to confirm the identified trends.

Bibliographic References

Cyganczuk, S.V.; et al. 2018. Problemas de comunicação em projetos: percepção de gerentes de projeto. GEPROS: Gestão da Produção, Operações e Sistemas 13(3): 1-18. 22 maio 2026.

Gil, A.C. 2002. Como Elaborar Projetos de Pesquisa. 4.ed. Atlas, São Paulo, SP, Brasil.

Instituto Brasileiro de Governança Corporativa [IBGC]. 2025. Inteligência Artificial e Governança Corporativa: urgência da capacitação no Brasil. IBGC, São Paulo, SP, Brasil. Disponível em: <https://www.ibgc.org.br>. 20 maio 2026.

Project Management Institute [PMI]. 2014. Pulse of the Profession: The High Cost of Low Performance — The Essential Role of Communications. PMI, Newtown Square, PA, EUA. Disponível em: <https://www.pmi.org/-/media/pmi/documents/public/pdf/learning/thought-leadership/pulse/the-essential-role-of-communications.pdf>. 22 maio 2026.

Project Management Institute [PMI]. 2021. Um Guia do Conhecimento em Gerenciamento de Projetos. 7.ed. Project Management Institute, Newtown Square, PA, EUA.

Vanzolini, 2024 [Referência completa não encontrada no documento original]

Verrel, A.; Julkovski, D. 2024. O impacto da inteligência artificial na gestão de projetos: aplicações, benefícios e desafios. South American Development Society Journal 10-30. Disponível em:<https://doi.org/10.24325/issn.2446-5763.v10i30p1-23>.22 maio 2026.

Article originating from the Final Course Project of the Specialization in Project Management of the MBA USP/Esalq

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October 22, 2026

Statistical Regression in Microgrids for Operational Performance Estimation: Campusgrid Case

A multiple statistical regression model was proposed to estimate the operational performance of UNICAMP’s CampusGrid microgrid, based on internal electrical quantities. The microgrid integrates photovoltaic generation, batteries, and a gas generator. Energy management system data were collected at five-minute intervals over one month. The Operational Reliability Index, defined as the ratio between supplied and demanded energy, was established as the dependent variable. The model was adjusted for the islanded operation mode, evaluating the impact of demand, state of charge, solar generation, and supplied energy. The results revealed high explanatory power, indicating that operational reliability depends on the interaction between supply and demand. It was observed that the nighttime period concentrated the highest rate of partial supply, attributed to the reduction in solar generation. It was concluded that multiple regression offers an interpretable and useful framework for microgrid monitoring and control strategy support.

Keywords: Battery storage; Photovoltaic generation; Reliability Index; Islanded operation; Energy Management System.

October 22, 2026

Forecast of Aggregate Default in the Brazilian Financial System by Sarimax Model with Macroeconomic Variables

Aggregate non-payment in the Brazilian financial system is a crucial indicator of credit risk, the prediction of which is regulated by CMN Resolutions n.° 4.557/2017 and 4.966/2021 for the prospective measurement of expected losses. Aggregate non-payment was modeled and predicted using the SARIMAX model, projecting its trajectory until December 2026 under optimistic, base, and pessimistic scenarios. 164 monthly observations (July/2012 to February/2026) and macroeconomic variables such as unemployment, Selic, IPCA, IBC-Br, and household debt were used. The specification with contemporaneous variables was selected based on information criteria and coefficient stability, and residual diagnostics confirmed statistical adequacy, with a MAPE of 3.12%. Historical non-payment ranged between 4.33% and 7.64%. The estimation identified unemployment (β = 0.2534; p < 0.001) and Selic (β = 0.2128; p < 0.001) as the main positive determinants, with strong temporal persistence (AR(1) = 0.8965). Selic showed increasing correlation with non-payment (r = 0.62 at lag 12), while unemployment demonstrated a contemporaneous effect (r = 0.33). Projections indicated non-payment between 6.30% and 7.98% in December 2026, with a range of 1.68 percentage points, highlighting direct implications for provisioning in financial institutions.

Keywords: Unemployment; Predictive modeling; Monetary policy; Loss provisioning; Time series.

October 22, 2026

Stakeholder Engagement Factors in International Technology Transfer to a Public Hospital

This study described the critical factors perceived for stakeholder engagement in international technology transfer in a public hospital, with a focus on planning. The objective was to describe these conditioning factors, according to the perception of professionals. A single case study was conducted, applying a questionnaire to 25 professionals and using content analysis, complemented by descriptive tabulations. The main obstacles identified were resistance to change (72%), funding (64%), lack of communication (60%), and bureaucracy (40%). Only 28% of respondents recognized the existence of adequate tools for stakeholder management, while 48% denied it and 24% did not know. Exploratory cross-tabulations indicated variations in the assessment of influence according to time of practice, but did not establish causal relationships. Lack of engagement was associated with delays, low adherence, waste of resources, communication failures, compromised knowledge absorption, and risks to patient safety. The conclusions were limited to the perceptions of the researched group and supported preliminary recommendations for intersectoral communication and coordination.

Keywords: Case study; Project Management; Health innovation; Stakeholders; Public sector.

Economy

October 19, 2026

End of the 6×1 scale: what do the numbers allow us to conclude?

Following the promulgation of the end of the 6×1 shift system, the debate on the shorter workday moves to implementation and requires distinguishing social benefits from economic costs. The end of the 6×1 shift system transitioned from legislative discussion to a constitutional change in Brazil. On October 16, 2026, the National Congress promulgated Constitutional Amendment No. 141/2026, originating from Proposal […]

Artificial Intelligence

October 16, 2026

Why study if AI exists?

When answers become easy, learning comes to mean more than just arriving at them. Why do I need to learn this if I can ask an artificial intelligence? This type of question has accompanied education for decades. Why learn an operation if a calculator exists? Why memorize information if it can be found […]

Tax Management

October 15, 2026

Pink tax and the gender of price

How different marketing treatments for men and women are incorporated by consumption taxation Imagine a shelf on which two razors of the same brand and intended for the same purpose are displayed side by side: one has dark packaging and promises strength, precision, and efficiency; the other comes in shades of pink or […]

Health

October 13, 2026

The missing link in health transformation

Why is innovation not enough to drive changes in organizations and health systems Digital transformation has become a strategic priority for health systems worldwide. Electronic health records, artificial intelligence, telemedicine, remote monitoring, and data analysis are now part of the strategic agenda of governments and health organizations. Paradoxically, […]

Marketing

October 09, 2026

Bitcoin or pets: what Artificial Intelligence would not see

A real-life consumer intelligence case shows what gets left out of the brief A few years ago, an American insurance company hired a specialized consumer intelligence firm to answer three questions: The insurer was also considering launching paid insurance in bitcoin. At the time, the consultancy’s workflow was as follows: the analyst created a query […]

School Management

October 06, 2026

The school is not a casino: when trading cards become currency in the playground

Why, for certain students, does school manage to offer so few experiences of achievement? The World Cup is over. Brazil left the competition, the school holidays came, the final was played and the football calendar moved on. It would be reasonable to imagine that, with the end of the tournament and the return to classes, […] would also begin

Energy Transition

September 30, 2026

Renewable energies: the Brazilian advantage

Brazil needs to invest in the capacity to transform natural resources into innovation, productivity, and development. Talking about energy is talking about development. Behind industry, transportation, services, cities, and increasingly artificial intelligence, there is an energy infrastructure that sustains the economy. Understanding a country’s energy matrix is understanding […]

Data Analysis

September 30, 2026

When the data changes, has reality changed?

An analysis of almost 20 million teaching positions-year between 2020 and 2025 shows how changes in population composition and record production can alter the interpretation of historical series Between 2020 and 2025, the number of formal teaching employment positions identified in RAIS (Annual Relation of Social Information), from the Ministry of Labor, […]

Artificial Intelligence

September 28, 2026

Artificial intelligence and the trends

Why do so many people join in on the fun with ChatGPT? I was never the trend person. I still am not. Some pass through my timeline, I see them, I find them interesting but not to the point of trying them out. This was the case, inclusive, with some recent waves of images made by artificial intelligence, like the 80s trend, the one that […]

Tax Management

September 01, 2026

Tax reform and estate planning in the countryside

Efficiency in managing taxes facilitates governance and allows for the organization of family succession. Rural wealth organization has become a strategic measure in light of the tax reform in Brazil, which came into effect this year. The planning of activities and rural wealth management, through tools such as the transition from an Individual to […]

Renata de Gaspari Valdejão Almeida

Artificial Intelligence

August 05, 2026

Inside the company and off the radar: the risks of Shadow AI

According to Microsoft, 75% of professionals already use artificial intelligence at work without company approval. The use of generative artificial intelligence is already part of the corporate routine. Tools like ChatGPT, Copilot, and other platforms help professionals produce texts, analyze data, create presentations, and accelerate tasks in practically all sectors. But this advance […]

Renata de Gaspari Valdejão Almeida

Strategy

July 02, 2026

The future as a competence

Academic interest reinforces the projection of scenarios as an essential tool for decision-making. While some companies are still trying to get the next step right, others are already working with multiple possible futures — and preparing for all of them. But after all, what does it mean to “think about the future”? Is it a trend, a strategy, or a new competence that […]

Renata de Gaspari Valdejão Almeida

Innovation

Technology

May 21, 2026

Agro SP Corridor: innovation, institutional articulation and future

Pecege commands the executive operation of the 400 km ecosystem activities that became known as the Brazilian agro Silicon Valley In 2025, in addition to taking over the management of the Piracicaba Technology Park, the Pecege Institute was also designated to command the executive operation of the State Agribusiness Innovation Corridor activities, the so-called […]

Education

April 27, 2026

How to turn a TCC into a business

New management of the Piracicaba Technology Park offers consulting to MBA graduates The new project director of the Piracicaba Technology Park (PTP), Alexandre Barreto, often says that one of the greatest rewards he has ever had in life was seeing his MBA USP/Esalq students structure companies from their final projects […]

Technology

March 20, 2026

The human repertoire in the age of AI

Critical thinking and creativity are irreplaceable in the work of a marketing professional Artificial Intelligence (AI) is capable of incredible feats, but it does not yet possess the judgment, empathy, intuition, and strategic creativity necessary to do the job of a good marketing professional. In this area, it is important to know how to use the tool to automate […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

February 23, 2026

ESG as a growth strategy in a cooperative in RS

Santa Clara balances social and environmental responsibility with innovation Founded in 1911 by Italian immigrants in Carlos Barbosa, in the Serra Gaúcha region, Cooperativa Santa Clara is an example that it is possible to balance economic growth with social and environmental responsibility. From a small cheese production company, the organization has evolved into a […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

January 22, 2026

Brazil free of Foot-and-Mouth Disease: what changes for Brazilian beef?

With a herd of over 200 million head of cattle, the country is currently the leader in exports. Brazil recently received, for the first time, the certification of country free of foot -and-mouth disease without vaccination, conferred by the World Organisation for Animal Health (WOAH). The seal strengthens the country’s position as a reliable supplier of meat for the […]

Renata de Gaspari Valdejão Almeida

Innovation

December 09, 2025

Innovation: the new cycle of the Piracicaba Technology Park

Instituto Pecege assumes management, betting on the creation of new businesses Starting in 2026, Instituto Pecege will assume the management of the Piracicaba Technology Park (PTP). Among its responsibilities will be the administration, operation, maintenance, and expansion of the park, in addition to fostering activities in innovation, entrepreneurship, and science and technology. The choice was made […]

Renata de Gaspari Valdejão Almeida

July 06, 2026

Large-Scale Architecture: DSR-SCRUM Change Management

Mônica Alessandra Guerios; Maria do Carmo Assis Todorov Abstract generated by ResumeAI, an artificial intelligence solution developed by Instituto Pecege focused on synthesis and writing. Architecture and urbanism are configured as essential bases in an increasingly complex and challenging urban space, where the intrinsic connection between social, environmental, and technological issues […]