Knowledge management is defined by the Inter-American Law Bank as a conglomerate of actions and processes that allow strengthening the exchange of information and expertise in organizations and/or groups of professionals with the objective of enhancing the performance of the organization, group of professionals or results of any ongoing project. (Briceño, Strand, & Marshall, 2020)

According to the Technical Guidelines for Knowledge Management and Innovation (Función Pública, 2020) "knowledge management is understood as the process by which actions, mechanisms and instruments that generate, identify, capture, value, transfer, appropriate, analyze, disseminate and preserve knowledge are put into practice (...)", so we can understand that knowledge management is any action that helps in the exchange and dissemination of knowledge among organizations and/or specific groups of society.

Knowledge management according to Blázquez (2011) cited by Luna Jiménez et al. (2017), has been studied with the aim of maximizing the contribution that organizations make to society, because thanks to globalization and the changes that this has brought about in the economy, universities need to manage these resources because they are generators of knowledge and train people.

The purpose of knowledge management is to help organizations to be more agile, efficient and innovative than the competition, therefore, it also deals with the relationship and interaction between the organization and the surrounding environment, at the level of responsiveness and in general in all the actions it develops. Greiner et al. (2007) cited by Villasana Arreguín et al (2021).

Knowledge management, according to Davenport T. H. (1996) cited by Larrea Abásolo (2008), consists of 10 general principles that are described from a pragmatic perspective, as shown in Figure 1:

Figure 1 Source: Own elaboration based on Larrea Abásolo (2008).

O'Dell & Grayson, (1998) cited by Larrea Abásolo, (2008) proposed the following comparative distribution between a culture that promotes knowledge transmission and one that does not promote knowledge:

Figure 2 Source: Own elaboration based on Larrea Abásolo (200)[sic].

Authors such as Rodríguez Castellanos et al. (2001), state that knowledge management can be understood as "the planning, organization, coordination and control of the activities that lead to the capture, creation and dissemination of knowledge in the company or other type of organization in an efficient manner". These same authors conclude that in the midst of the search for a unified or general theory of knowledge management, there is an implicit agreement that the process is circular and spiral, because it consists of some sub-processes, as shown in Figure 3.

Figure 3 Source Bahtt (2000). Taken from: Rodriguez Castellanos et al. (2001)

To understand the relevance of managing knowledge in the progress of any organizational strategy, it is necessary to understand the approach to resources and capabilities. This theoretical approach to resources and capabilities is a valuable instrument that facilitates the determination of strengths and weaknesses internally in an organization, which is why the resources and capabilities that an organization has is what allows the exploration of capabilities and the neutralization of threats, but this is only possible for a very restricted number of organizations, because it is costly and not very accessible in the market. Barney (1997)

The above is complemented by Guerras M & Navas L (1998) who stated that "intangible resources and capabilities are usually based on information and knowledge, so there are no limits to their capacity for use. This allows us to appreciate that at present the value of organizations is related to intangible aspects, more than to tangible ones, and that the former refer to the intellectual capacity that is becoming more important day by day.

This is why knowledge management, as Revilla Gutiérrez (1996) put it "means managing processes of creation, development, dissemination and exploitation of knowledge to gain organizational capacity".

For Vitale Alfonso et al. (2020), it is important because it enhances the organizational structure, making it innovative and efficient; the skills and useful information is transmitted to workers effectively, so that the chance of generating new knowledge is much higher, as well as improving processes, products, and different ways of negotiating for new opportunities.

Entrepreneurship in its most generalized and basic definition can be understood as the development of a project that aims at economic, social, personal or any other kind of gain, which in turn has characteristics such as innovation and uncertainty. Kundel (1991) cited by Formichella (2004) defines this activity as the management of a radical and discontinuous change, a strategic renewal, in which it does not matter whether such renewal is internal or external, nor does it matter whether or not it gives rise to new business or business ideas.

Duarte Cueva (2007) establishes that the entrepreneur is any person who individually or as a group creates business ideas, understanding that this is feasible when it is innovative and responds to a need in a creative and hitherto non-existent way. For Andy Freire (2004), the entrepreneur is the person who sees an opportunity and based on it develops an organization, acquires it or is part of a group that acquires it. These definitions allow us to understand that the entrepreneur is the person capable of detecting a business opportunity or project because of a need that has not been solved efficiently. Therefore, the entrepreneur is the idea or project that will respond to this need and will take advantage of this opportunity to profit and/or achieve its objectives.

There are several types of entrepreneurs, but Alcaraz (2011) cited by Cozarit León & Palma Esquer (2016) defines 5 main personalities:

Each of these types of entrepreneurs described in Figure 4 need skills and abilities to be able to carry out their business ideas or projects. That is why Rockerfeller (2006) cited by Cozarit León & Palma Esquer (2016) establishes that entrepreneurial ability is the potential that an individual possesses and that this, in turn, is a set of skills and knowledge that allows a person to develop the activities that will allow them to successfully develop their entrepreneurship.

Figure 4: Source: own elaboration based on Cozarit León & Palma Esquer (2016).

Likewise, Sánchez (2014) quoted by Cozarit León & Palma Esquer (2016), defines entrepreneurial skills as "capacity or ability to carry out some tasks efficiently and effectively".

Figure 5: Source: own elaboration based on Cozarit León & Palma Esquer (2016).

There are 10 main characteristics that allow entrepreneurs to achieve their goals and make their ideas successful, benefiting them and all those who are part of their entrepreneurship:

Figure 6 Source: Own elaboration based on Pérez Paredes and others (2020).

Entrepreneurship itself is an engine of the economy, regardless of the context in which it is developed, it becomes a challenge for those who want to become entrepreneurs, but it is they, the entrepreneurs, who generate jobs, move the economy and promote paradigm shifts, because they are responsible for dreaming of a world and an economy different from the one already established (Loor Mendoza, 2022).

There are many studies that establish that the entrepreneur is born and not made (Zhang, 2009 cited in Arias-Arciniega et al., 2020), there are others that direct their efforts to the understanding of learning to generate entrepreneurship by university students (Soria, 2016 cited in Arias-Arciniega et al., 2020) that is based on tastes, contexts, interests and culture (Bandera, 2018 cited in Arias-Arciniega et al., 2020). The above establishes that there are many researchers who have focused their resources on the study of entrepreneurship learning in the university environment, with the objective that this population is able to generate entrepreneurship and with it work and significant contributions to the economy.

Therefore, for authors such as Bienkowska & Klofsten (2012), university entrepreneurship was born with the objective of including universities in the economic development of the regions in a more extensive way. This has led universities to establish a role and status in the development and promotion of the entrepreneurial culture, which is why, although it is more common for them to focus on business creation than on the competencies, skills and abilities of entrepreneurs. (Arias-Arciniega, Villegas López, López Tovar, & Echavarría Cuervo, 2020)

For Juliá (2013) entrepreneurship based on innovation and knowledge, is and will be a high-quality entrepreneurship, which will favor local, national and global economies to be truly competitive, something that will bring with it the generation of more jobs, which is why this type of competitive and quality entrepreneurship is the one that should be promoted from universities.

Artificial intelligence (AI) has been radically transforming the way we manage knowledge, especially in institutional and organizational environments. This transformation, although it brings many innovative opportunities, also poses quite complex challenges, especially if we talk about the ethics and responsibility involved in its implementation. Zambrano (2022) says that although AI has been very beneficial in areas such as health, food and other key sectors, it can also generate very negative effects, such as in armed conflicts or when personal information is misused. That is why it becomes urgent to reflect on how we use these technologies and think about how they can be regulated in a fair way.

Figures such as Pope Francis or Vladimir Putin have shown their concern about the possible negative effects of AI, and it is no wonder, because we are already seeing debates about how robotics should work and what role machine ethics play in this context. Therefore, from the academic point of view, it is essential that universities begin to include more spaces in their curricula where ethics and technology are taught, because the coming generations must be prepared to make responsible decisions in an increasingly automated and complex world.

The impact of AI is also beginning to be felt strongly in the field of education, since we are talking about a transition towards what is known as education 3.0, which blends technological advances, neuroscience and psychology to improve the teaching-learning processes. It is a stage that redefines the role of educational institutions, and although its benefits are clear, such as the development of critical thinking and peer-to-peer collaboration, very serious questions also arise: how to regulate its use, how to detect possible biases in the algorithms, and whether there should be a global code of ethics to guide its implementation.

In that sense, as Zambrano (2022) says, AI cannot be seen only as a cold tool, but as a phenomenon that forces us to think about issues such as autonomy, accountability and respect for human rights. Integrating this tool without an ethical basis would be a mistake, because technology alone does not guarantee good use; what does guarantee it is the human judgment behind it.

Beyond education, the risks of AI also affect other global scenarios such as international security and politics. We are seeing more and more news of cyber-attacks, information theft and even autonomous weapons that could increase tensions between countries. According to Zambrano (2022) the use of AI in driverless vehicles, military drones and other dangerous applications can lead to very serious consequences. This makes it clear that more robust global regulation and stronger ethical education is needed to help us use these technologies responsibly and humanely. Because yes, AI is moving fast, but ethics and collective conscience must move just as fast, lest we end up creating something we can't control.

AI has become a key factor within the educational system, as it has allowed personalizing learning and improving certain processes within the classroom. González, Baren and Zapata (2023) state that these technologies help to better identify the needs of each student, adapting content to their abilities, which allows not only a more effective education, but also a more inclusive one. At the same time, these tools serve to automate repetitive tasks such as evaluation or analysis of results, which gives teachers more time to focus on pedagogical issues.

But it must also be said that AI is not only changing how we teach, but also what we teach. It is now important to train students not only in technical aspects, but also in the critical and ethical use of these tools. According to González et al. (2023) training in technological skills must go beyond the instrumental and address the ethical, social and economic implications that come with the use of these tools, because it is not only about knowing how to use them, but also about knowing when and for what purpose.

However, all this comes with challenges, which is why González, Baren and Zapata (2023) warn that there is still a marked digital divide between different regions, and that excessive dependence on technology can be a risk if there is not a balanced approach. Added to this is the need to protect students' personal data, and to prepare teachers not only to handle these tools but also to integrate them properly into their classes. That is why it is said that AI should not replace the teacher but complement his or her work and make it more human, not less.

Figueroa and Barreto (2024) point out that these tools have made it possible to further personalize learning and facilitate access to knowledge, enabling universities to better adapt to the needs of the 21st century. Interaction between students and teachers has improved through intelligent systems that organize and optimize knowledge, and this not only raises the quality of education, but also makes more efficient use of available resources.

In addition, AI makes it possible to analyze large amounts of information, which helps to make more informed academic decisions that impact curriculum design educational policies, and allows for better measurement of student performance. This in turn translates into improvements that benefit both students and institutions. Figueroa and Barreto (2024) insist that these technologies can also change the way assessment is done, providing faster and more personalized feedback, which can help close learning gaps.

But not everything is positive, there are also major challenges that must be faced responsibly: privacy, unequal access, possible displacement of the teaching role, among others. And while it is true that AI has enormous potential to improve university education, it all depends on how it is used. Therefore, Figueroa and Barreto (2024) conclude that, despite the difficulties, if an ethical approach is maintained and all stakeholders are listened to, these tools can positively transform higher education, making it more humane, more inclusive and more prepared for the future.