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Publicación A Efficient Model for Startups Creation with Low Risk and Uncertainty, Study Cases in IADES(Springer Nature, 2025-03-25) Pérez-Pupo, Iliana; Piñero-Pérez, Pedro Yobanis; Piñero-Ramírez, Pedro E.; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Piñero-Ramírez, Carlos ManuelSmall and medium-sized enterprises (SMEs) and startups are an essential part of the economy in many countries, having a significant economic and social impact. In this context, recent advances in Artificial Intelligence (AI) have fostered the creation of numerous companies supported by these technologies. However, the creation of such enterprises involves high risks, with 50% of initiatives failing. Multiple factors, coupled with a high degree of uncertainty in decision-making, contribute to this phenomenon. The methods section presents a model for building AI-supported startups. The proposed method facilitates the processes of implementation and governance during its application. This model can be generalized through the IADESPro platform. In the results analysis section, the authors validate the proposal using socio-economic indicators and word computing techniques. Furthermore, the results of applying the model in the IADES Commercial Society, a company dedicated to the development of new AI technologies for Sustainable Development, are presented. The IADES company adopted the proposed model and focused on applying AI in the fields of Sports, Sustainable Development, and Project Management. The application results are demonstrated.Publicación Decision Making in Artificial Intelligence Training Programs(Springer Nature, 2025-03-25) Yzquierdo-Herrera, Raykenler; Piñero-Pérez, Pedro Yobanis; Pérez-Pupo, Iliana; Alvarado-Acuña, Luis Segundo; García-Vacacela, Roberto; Hernández-Pupo, Luis GabrielThis work addresses the challenge of capacity building in the areas of artificial intelligence and data science. It starts by recognizing the need for new academic programs that consider these subjects as central themes. To develop researchers skilled in topics such as computational intelligence, decision-making in uncertain environments, generative artificial intelligence, and other trends in the development of new AI technologies in society, an ethical approach is required. In the methods section, the proposal addresses the fundamental challenges related to these topics and provides a brief analysis of the state of the art. Additionally, a training strategy is proposed, ranging from short-cycle programs to postgraduate education. The proposal includes a short-cycle program for a Data Science Technician, an Artificial Intelligence Engineering degree, and a master’s degree in Artificial Intelligence. In this way, the training is provided at various levels, accompanied by a strategy for continuous education. In the results analysis section, the proposal was evaluated by a group of specialists in curriculum design, yielding positive results. Finally, the conclusions focus on the fair and ethical development of artificial intelligence.Publicación Framework for Strategic Planning and Assisted by Artificial Intelligence(Springer Nature, 2025-03-25) Alvarado-Acuña, Luis Segundo; Piñero-Pérez, Pedro Yobanis; Yzquierdo-Herrera, Raykenler; Piñero-Ramírez, Carlos Manuel; López-Correa, Francisco Javier; García-Vacacela, RobertoStrategic forecasting continues to be one of the fundamental elements in decision making. This branch of management sciences, like other branches of knowledge, is being influenced by artificial intelligence and other emerging technologies. In this work, in the first section of the methods section, a brief study is made of the state of the art of trends in strategic planning and the points of contact with artificial intelligence. The opportunities for improvement of existing strategic forecasting techniques with respect to the treatment of uncertainty are analyzed. In the second section, a proposal is made for a framewrok for strategic planning assisted by artificial intelligence techniques. This model allows aiding decision making while maintaining an adequate management of information uncertainty. Then, in the results analysis session, the proposals made are validated. Statistical techniques and expert and data triangulation methods are used. As conclusions, the validity of the proposal and its power for decision making under uncertainty is demonstrated. Future lines of work are also presented.Publicación Model for the Creation and Decision-Making in Project Management Offices (PMO)(Springer Nature, 2025-03-25) Fuentes-Ruiz, Daniel Alejandro; Alvarado-Acuña, Luis Segundo; Heredia-Rojas, Boris Fabrizio; Huidobro-Arabia, Juan Elías; Piñero-Pérez, Pedro-Yobanis; Yzquierdo-Herrera, RaykenlerDuring the evolution of project management, various authors have proposed theories regarding the roles and structures of Project Management Offices (PMOs). In literature, a wide variety of PMOs can be identified. Each PMO has essentially been tailored to the organization that supports it. However, the high rate of project and PMO failures suggests that it is possible to generalize the best practices. The first section of the methods chapter introduces various concepts related to project management and PMOs. The second section presents a model for the creation and decision-making processes within PMOs. The core of the proposal focuses on decision-making methods for PMOs and how these methods evolve with the introduction of artificial intelligence. Additionally, different PMO contexts and best practices for the scenarios analyzed are discussed. The study also examines various roles within PMOs and their relationship to project management maturity levels. In the results analysis, the proposal is validated by subject matter experts using computational techniques based on linguistic approximations and the Delphi method.Publicación Platform for Project Management IADESPro, Supported by Artificial Intelligence(Springer Nature, 2025-03-25) Álvarez-Sago, Yunieck; Piñero-Pérez, Pedro Yobanis; Pérez-Pupo, Iliana; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Hernández-Pupo, Luis GabrielThis work addresses the challenges of managing science and innovation projects, with a particular focus on the issues faced by the international science and innovation funding and project management office of CITMA. As part of the study, a state-of-the-art review is conducted to examine trends in project management. A critical analysis based on the literature is then presented. In the methods section, a proposed platform for project management, called IADESPro, is introduced. The proposed platform is based on agile management methods and performance domains, incorporating best practices from PMBOK and ISO standards. The platform is supported by artificial intelligence techniques to aid decision-making. The proposed platform focuses on value generation, covering the various performance domains of project management. In the results section, the implementation of the platform is evaluated in the context of managing research and innovation projects. A comparison is made between the proposed platform and others reported in the literature, with a critical analysis of their advantages and disadvantages. The feasibility of the proposal is demonstrated, along with its potential for decision-making in environments characterized by uncertainty.