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1 March 2026

Algorithmic Challenges and Regulatory Frameworks of Artificial Intelligence in Mexico: A Prospective Analysis from the Perspective of Digital Governance Theory

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1
Unidad Profesional Interdisciplinaria de Ingeniería y Ciencias Sociales y Administrativas, Instituto Politécnico Nacional, Av. Té 950, Granjas México, Iztacalco, Ciudad de México 08400, Mexico
2
Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Juan de Dios Bátiz s/n, GAM, Ciudad de México 07700, Mexico
3
Subsecretaría de Educación Media Superior, Secretaría de Educación Pública, Av. Universidad 1200, Piso 4, Sector 4-6, Xoco, Benito Juárez, Ciudad de México 03330, Mexico
4
Campus CDMX, Universidad OMI, Av. Anillo Periférico 42, Constitución de 1917, Iztapalapa, Ciudad de México 09260, Mexico
Computers2026, 15(3), 150;https://doi.org/10.3390/computers15030150
This article belongs to the Section AI-Driven Innovations
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Abstract

The rapid integration of artificial intelligence (AI) has heightened the need for evidence-based regulatory frameworks to effectively address its legal, ethical, and societal consequences. This research carefully analyzes the prevailing landscape of AI-related legislation in Mexico. The study conducts a comprehensive review of legislative initiatives related to AI regulation submitted to Mexican legislative bodies, encompassing those approved or pending in commissions. This process leads to the identification and categorization of outstanding initiatives across seven policy areas: Congress, Education, Health, Intellectual Property, Justice, AI Promotion, and AI Regulation. As a principal contribution, this work offers the first exhaustive mapping and thematic classification of legislative activity related to AI in Mexico. Furthermore, the analysis identifies systemic regulatory deficiencies, such as the lack of AI-specific legislation, the limited scope of existing data protection laws in relation to AI systems, and an absence of technical provisions concerning ethical design, algorithmic transparency, cybersecurity, and accountability frameworks. By showcasing these deficiencies, the study contributes a diagnostic framework for evaluating AI governance readiness in emerging economies. The findings emphasize the importance of establishing a comprehensive, technically sound, and internationally harmonized regulatory framework to reduce AI-related risks while promoting responsible innovation in Mexico.

1. Introduction

Artificial intelligence (AI) has become an integral part of modern life. Recent advances in generative transformers, along with other technologies, are reshaping society, driving rapid development across various domains. However, these advances do not come without limitations and concerns regarding their safety, environmental impact, and potential disruptive influence on jobs, the economy, and other social aspects [1].
In addition, several concerns have been raised about autonomous weapons, including the potential for chemical and biological attacks, AI-based cyberattacks, and the facilitation of organized crime by AI, as well as the ultimate accountability of technologies that incorporate AI [1] and its ethical use [2]. That is why the rapid advancement of AI technologies has sparked a global dialogue on the need for comprehensive legal frameworks to regulate their use, and Mexico is no exception. As AI systems continue to permeate diverse sectors, from healthcare to finance, the Mexican legal landscape faces a pressing need to adapt and evolve to address the complexities and ethical dilemmas posed by these technologies.
Mexico was among the first nations to initiate discussions on AI regulation in 2018, emphasizing the need for each country to define its own AI regulatory framework, reflecting a proactive stance in shaping ethical guidelines tailored to its national priorities [3]. The concerns regarding digital governance in Mexico have been studied for several years. A pioneering study by Schneider concludes that, although Mexico has established an AI and digital transformation strategy, its concrete agenda remains in its early stages. The country lacks a large market to exert significant pressure on major digital platforms, and large corporations can easily bypass existing Mexican data protection laws (Federal Law on the Protection of Personal Data Held by Private Parties [4]). In addition, enforcing the current regulations remains an area for improvement [5]. Ruvalcaba-Gomez and Cifuentes-Faura studied the perception of digital governance and artificial intelligence in the state of Jalisco, Mexico [6]. Their study showed that public officials consider themselves fairly proficient in information technologies but less proficient in AI-related issues. It was reported that 53.8% of respondents have never heard of AI in the public sector, and 98.9% consider it necessary to develop regulations and public policies on AI.
Other researchers studied the impact and barriers of AI in the public sector, as well as the perception of local politicians [7,8]. They analyzed public officials’ perceptions of the impact, functions, and barriers of artificial intelligence (AI) within the context of a local government in the State of Mexico. A survey of 32 key public managers identified the competencies, perceptions, and challenges of AI implementation. These studies reveal concerns, functional impairments, and key obstacles to AI implementation. While AI has the potential to significantly transform and improve the efficiency and quality of public services, it also faces significant barriers that must be addressed to ensure its success. Appropriate regulation and ongoing training for public officials are crucial to fully harness the benefits of AI and mitigate its potential adverse effects.
In addition, Criado et al. conducted a survey administered to chief information officers in ministries of Mexico and Spain [9]. The survey identified three key inhibitors to the adoption of AI in the Mexican public sector: budget (90.9%), the digital divide (63.6%), and technological infrastructure (54.5%). An intriguing finding is that security and data privacy were not perceived as barriers to AI implementation in the public sector, as none of the Mexican respondents selected these options. Similar concerns regarding the adoption of AI in the public sector of different countries from an ethical perspective were summarized in 2021 as part of the CLAD International Course “Governance of Artificial Intelligence in Public Administration from an Ethical Perspective” [10].
An interesting study explored users’ perceptions of AI-based chatbots during the COVID-19 pandemic [11]. They conducted an open survey regarding two chatbots (Susana Distancia and Dr. Armando Vaccuno) deployed as part of a “digital government” strategy of Mexican health systems. The survey reported high levels of apprehension regarding the transparency, data protection, and accountability of the chatbots. Both users and non-users share concerns about the lack of information regarding the treatment and processing of the collected data, the lack of credibility in governmental responsibility for the bots’ functioning, and a high level of concern about the use, distribution, and protection of their personal data.
Additionally, Mendoza-Enríquez commented on the challenges related to data protection. She considered that, although Mexico has a solid legal framework for personal data protection, it faces challenges in technological environments, particularly with the use of AI. The extraterritoriality of the law, the absence of physical borders, and the reliance on corporations to safeguard rights diminish its effectiveness. Furthermore, new forms of the right to data protection need to be recognized, such as the right to challenge automated decisions, the right not to be subjected to AI processing, and the right to non-identification in these processes [12]. A small survey by Pérez et al. in Yucatan on AI safety revealed concerns about the spread of misinformation, manipulation of public opinion, and the possibility of AI being used in an authoritarian manner [13].
Despite those previous investigations, there is no comprehensive analysis of the current legislation governing artificial intelligence in Mexico. In this context, questions arise regarding the current status of different regulatory proposals, the adequacy of current regulations, and the effectiveness of enforcement mechanisms. Furthermore, significant challenges remain in implementing AI regulations, including striking a balance among innovation, ethical considerations, and the protection of individual rights.
This review paper will examine the current legal framework governing AI in Mexico by reviewing the existing initiatives regarding AI regulation and discussing the potential future directions for the regulatory landscape. The aim of this review is to analyze the current state of legislative initiatives in Mexico related to the development, use, and regulation of artificial intelligence.
We want to focus on two research questions:
Q1: 
What legislative initiatives currently exist in Mexico at the federal level that directly or indirectly address the use of artificial intelligence?
Q2: 
What critical aspects of AI (such as algorithmic bias, transparency, accountability, or privacy) are insufficiently regulated or completely absent in current legislation?
By reviewing the current state of the AI-related legislative corpus in Mexico and addressing the research questions above, our study will ultimately contribute to a more informed and nuanced understanding of the country’s AI governance.
The rest of the paper is organized as follows: Section 2 assesses the legal framework governing AI in Mexico till 15 May 2025. Section 3 discusses the initiatives reviewed and the limitations of our study. Section 4 summarizes key challenges and future directions in AI regulation in the studied country and presents actionable recommendations. Finally, Section 5 concludes the paper.

3. Discussion

In Section 2, we answered our first research question: Q1: What legislative initiatives currently exist in Mexico that directly or indirectly address the use of artificial intelligence? Therefore, this section focuses on our second question: Q2: What critical aspects of AI (such as algorithmic bias, transparency, accountability, or privacy) are insufficiently regulated or completely absent in the current legislation? First, we state the limitations of our study, and in Section 3.2, we summarize the main gaps found per area.

3.1. Limitations of the Study

The main limitations of our study are:
6.
Documentary and normative scope: The analysis is limited to formal legislative initiatives, excluding regulations, administrative guidelines, case law, and informal regulatory practices that also influence AI governance in Mexico.
7.
Static nature of the analysis: Since the study is based on pending initiatives at a specific point in time (31 May 2025), the results may be affected by the rapid evolution of the legislative and technological landscape, which limits the timeliness of the conclusions.
8.
Textual search: The Legislative Information System search engine only allows for textual search; that is, only the words “artificial intelligence” (inteligencia artificial in Spanish) were used in the search.
9.
Lack of empirical validation: This study does not incorporate the perspective of key stakeholders (legislators, regulators, developers, or AI users), which restricts the empirical assessment of the practical impact and potential effectiveness of the initiatives analyzed.
10.
We only focused on the current legislative landscape regarding AI in Mexico. We did not compare it with those in other countries.

3.2. Main Gaps of the Surveyed Initiatives

Below, we address the main gaps identified in the proposed initiatives by area of interest.

3.2.1. Congress-Related Initiatives

With respect to initiatives to empower Congress to enact AI-related laws, only one addresses the prevention of AI-based discrimination at the constitutional level. In addition, there is no consensus among legislators regarding the modification of an (apparently simple) text that includes AI among the areas over which Congress has the power to enact laws.

3.2.2. Education-Related Initiatives

In the Education-related initiatives, there is no regulatory framework to ensure the necessary technological infrastructure [28], including data centers, high-speed networks, and hardware that meet standards to guarantee coverage and keep pace with AI advancements, as well as addressing data usage and algorithmic bias.
There is no clear explanation of how training programs [29] will be implemented, how discrimination and algorithmic bias will be prevented, or how job losses resulting from the implementation of AI to increase business productivity will be mitigated.
Finally, the wording of the proposal [30] is unclear, particularly regarding the aspect of “analysis in Artificial Intelligence.” This is because in Spanish grammar, the phrase “analysis in” typically refers to a specific field or context of application, which makes it difficult to determine how analysis within artificial intelligence will be incorporated into curricula across disciplines.

3.2.3. Health-Related Initiatives

With respect to the Health-related initiatives established by [32,33], it is not clear how “promoting” the protection of personal data will guarantee the security of such data, nor how AI will be incorporated into health services, whether it is to manage care, support diagnosis or treatment, record consultations (environmental scribes), or for what other purposes these technologies will be used. In one case, a set of potential applications is listed, but it is clarified that they are “not limited” to these.
It leaves data protection to individuals (the developers and providers of AI systems). No sensitive characteristics (such as age, sex, race, socioeconomic status, among others) are excluded from being used by developed AI algorithms. It leaves it to the patient to obtain “informed” consent without establishing who will provide accurate information about how the systems work (especially given the industrial secrecy usually associated with systems development).
The Federal Commission for the Protection against Health Risks assigned responsibility for assessing health risks associated with the use of artificial intelligence systems, without clarifying which risks are being assessed or how they will be evaluated. However, it will be the Ministry of Health that “will determine in which cases artificial intelligence systems pose a risk to people’s health and will proceed to request the suspension of the system’s operations and, where appropriate, its cancellation” without clarifying what mechanisms will be used for this purpose. This aspect is grave, given the negative impact that Large Language Models (LLMs) have on people with mental illness, increased phobias, paranoia, schizoid disorders, and a tendency towards violence and suicide, as well as the issues of hallucinations inherent to LLMs [58,59].
It is unclear how “equity and inclusiveness in its use” will be guaranteed, what type of training doctors will receive, or whether any requirements for AI systems are mandated. It dilutes the responsibility for events that may affect patients among “health professionals, health service providers, and developers of artificial intelligence systems intended for use in the health field, who will be responsible, as appropriate.”
Regarding the initiative [34], there is no regulation to ensure bias is absent, no assessment of system quality, and nothing that allows medical personnel or patients to determine the potential impact of these tools on their care, diagnosis, or treatment.
In the case of COFEPRIS, it is unclear which criteria will be used to determine an “improvement of services,” and no characteristics are excluded from the potential use of AI systems, which can introduce bias and disparities and increase inequity and algorithmic injustice.

3.2.4. Intellectual Property Initiatives

The voice-protection initiative [36] is a starting point for regulating the use of personal data (in this case, a person’s voice), but it fails to address crucial aspects such as algorithmic bias, transparency, technical accountability, and data protection. Furthermore, it presents implementation challenges in a global market and lacks alignment with international standards that would enable a flexible, comprehensive framework.
It focuses on protecting the rights of voice actors against AI-generated voice cloning, emphasizing labor and copyright issues, but neglecting technical aspects. It fails to define quality, transparency, or auditing standards applicable to the use of voice synthesis and cloning software. Similarly, it omits any form of regulation regarding the security of biometric data (such as voiceprints) used to train these models, thus exposing risks of data breaches, misuse, or unauthorized appropriation in international contexts.
In addition, it does not include mechanisms for auditing, monitoring, or mitigating potential biases in AI systems that could affect employment opportunities; for example, by favoring certain voices or profiles over others. Moreover, the initiative places the burden on employers and producers but does not clearly define the responsibility of AI developers, software distributors, or streaming platforms that use these technologies. While it establishes financial penalties for unauthorized uses in employment and commercial contexts, it is unclear how to address illicit non-commercial uses (e.g., parodies, viral content) that also affect artists’ identities and reputations. Finally, the requirement for authorization from the Ministry of Culture for certain AI uses could become a bureaucratic obstacle that stifles artistic experimentation or innovation in independent projects.

3.2.5. Justice-Related Initiatives

The main gaps found in the Justice-related initiatives are summarized below:
When considering the use of AI for generating or modifying sexually explicit content, some proposals fail to consider whether such content depicts a real person or if it is generated without reference to a particular individual.
Furthermore, some initiatives only consider malicious acts that cause harm to the intimacy, privacy, and/or dignity of women, or the creation and dissemination of defamation campaigns, the theft and alteration of personal data, or the impersonation of a woman, with the purpose of slandering, intimidating, or terrorizing women, thus rendering male victims of digital violence invisible and excluding them from access to justice.
The initiative that proposes equating any deepfake to sexual assault [46] effectively criminalizes the use of AI technologies for generating visual content that includes any sexual component, such as series and films, among others. The text does not consider whether a real victim exists. Still, it is ambiguous in its wording, referring to “synthetic sexual images of people outside their original context, generated through computer synthesis, artificial intelligence, or other technological methods.” This wording does not clarify what the “original context” of “synthetic images” is; such images are assumed to have been “generated through computer synthesis.”
The initiative that penalizes fake audio recordings [48] with the purpose of deceiving, defaming, or harming defines a fake audio recording as “Any sound recording generated or manipulated by artificial intelligence with the intention of making it appear to come from a specific person, without their consent.” In this way, the door is left open for audio recordings to be manipulated using any technology to deceive, with the individual’s consent, without violating the law. In addition, only fake audio recordings of “public figures” are penalized, and not those of any person.
The initiative to use AI to combat crime [49], despite stating that “security protocols will be established to protect the processing and handling of information and products generated by artificial intelligence, preventing the misuse of the technology and possible violations of privacy,” does not clarify who will guarantee due process, non-discrimination, and the presumption of innocence, among other relevant elements, since the proposal is “illustrative but not exhaustive” regarding the use of AI in biometrics, finance, behavioral prediction, and real-time monitoring of communications, among others. At no point is it stated that a court order, an open case, or anything similar is required to be subject to these AI applications, which, de facto, would enable real-time mass surveillance without legal checks and balances.
The introduction to the market and deployment [50] of generative AI platforms that result in deliberate, deceptive, and non-consensual manipulation to alter images, scenarios, or video and audio recordings, making them appear real, is penalized. This shifts responsibility for potential misuse of these tools to providers, not to users. Furthermore, many platforms that support image, audio, and video manipulation operate online. There is no guarantee of how their providers will be prosecuted.
The introduction to market, deployment, or operation of generative artificial intelligence technological tools that use facial recognition data obtained through the indiscriminate extraction of facial images from the internet is also penalized. This effectively penalizes any current generative AI platform (e.g., Gemini, Claude, ChatGPT, and others), since all of them have been trained with images from various sources, including the internet.

3.2.6. Promoting AI-Related Initiatives

Regarding the promotion of AI [51,52,53], it remains unclear how the use of AI is to be “promoted,” how “strict adherence to human rights” will be ensured, or under what conditions the use of AI will be considered acceptable or unacceptable. The initiatives also fail to address key technical aspects, including machine learning, algorithmic bias, transparency, privacy, and experimental validation, thereby limiting their potential to inform effective public policy.

3.2.7. Regulate AI-Related Initiatives

Regarding the initiative to modify the Federal Telecommunications and Broadcasting Law [55], we identified the following limitations. First, the international reach is difficult to control. This applies to providers and users outside Mexico whose systems affect people in Mexico, complicating oversight and enforcement. Second, it presents complex technical and transparency requirements: The obligation to generate cryptographic digital signatures and decryptable files of AI-generated content can be costly and technically challenging for many developers to implement. Developers and operators are the only ones liable for AI-related damages. Users are not considered liable for the misuse of the technology; only the developers and operators are. Third, there is ambiguity in ethical and human rights concepts: requirements such as “full respect for human rights” or “ethical principles” are vague and could lead to uncertainty regarding their practical interpretation.
The main limitations of the AI law of 2024 [56] are that it leaves the proposal of technical and methodological standards to the National Center, so in practice, it is unclear how compliance will be guaranteed, which could render regulations ineffective. It mentions principles (transparency, traceability, ethics, human oversight), but clear technical and methodological standards for ensuring their compliance are not defined, which may render them impractical.
Although risk categories are established (unacceptable, high, limited), verifiable technical criteria for classifying AI systems within each category or evaluation procedures are not included. In addition, there is no requirement to detect, mitigate, or report biases in models, which is a critical aspect in the scientific literature and international AI regulations. Moreover, the requirement to inform users and label AI-generated content is stated, but model explainability and the right to know how an automated decision was reached are not addressed. The source of the information to be cited [56] is not specified (Training information? Validation information? User information? Other?), and it is not clarified what constitutes “illegal content” that developers should avoid generating with the models. The obligation to prevent illegal content falls on the “developer,” without distinguishing between designers, implementers, distributors, and end users, creating gaps in accountability. Although consent is mentioned in the use of AI systems in the public sector, no details are provided regarding security measures, data retention, transfer, or anonymization for data used by AI systems.
Finally, there is no mention of what will happen as a result of non-compliance by individuals or legal entities that are not public servants of the various levels of government.
The AI law of 2025 [57] contains duplicate articles in the text (e.g., 67 and 69, 66 and 68). It does not clarify how or how often the “own funds” of the National Artificial Intelligence Council will be allocated (beyond the fact that the Federal Government will allocate them), nor how it will be ensured that the National Algorithmic Audit Platform can “maintain its technological capabilities, methodologies, and tools up to date, to preserve its effectiveness, reliability, and relevance to the state of the art in artificial intelligence and algorithmic auditing” (Article 21). Although Article 66 establishes that “Every artificial intelligence system accessible to or directed at minors must have a Child Algorithmic Impact Assessment”, it does not clarify how this law will be enforced, given that Mexican citizens (including minors) can use AI systems via HTTP protocol as long as they have the necessary internet connectivity. How do governments intend to regulate the use of these systems?
In addition, it does not specify how responsibility (Article 133) will be established, nor who will bear it—the developers, the operators, those who facilitate access to the systems, or other involved parties. Likewise, it does not clarify who will be held accountable under the law in case of non-compliance (the developers, companies, government entities, individuals who deploy the system, or others).
Although it includes a “broad and preventive” prohibition of some artificial intelligence systems, the writing of the text de facto prohibits, for example, professional training systems (e.g., military simulators developed for weapons use) by public and private entities responsible for security matters, as well as systems for detecting substances (because they could be harmful) used in scientific institutions for knowledge development. Furthermore, “subliminal manipulation” is not defined, leaving the door open to banning systems that include recommendations, advertising, and other elements that have a “filter bubble effect” [60,61,62] and could be considered behavior-altering. This would effectively classify all social media platforms as prohibited artificial intelligence systems.
Similarly, following the provisions of items II and VII of Article 63 of the proposal, all social networks would be effectively banned in this country, since they encourage digital addiction [63] and actively use the data of their users (many of whom are minors) for their operation (e.g., advertising) and the training of their models. For example, the minimum age for using Facebook in Mexico is 13.
Finally, no proposed initiatives align with emerging regulatory frameworks such as the EU AI Act or the OECD and UNESCO guidelines, which could lead to incompatibilities in cooperation or digital trade contexts.

4. Conclusions

In this paper, we aimed to answer two research questions: (Q1): What legislative initiatives currently exist in Mexico that directly or indirectly address the use of artificial intelligence? (Q2): What critical aspects of AI (such as algorithmic bias, transparency, accountability, or privacy) are insufficiently regulated or completely absent in current legislation?
We reviewed the current initiatives in the Mexican legislative bodies aimed at regulating artificial intelligence. We identified 40 pending initiatives across seven areas: Congress, Education, Health, Intellectual Property, Justice, Promote AI, and Regulate AI. Regarding the second, we can conclude that, in Mexico, the use of artificial intelligence (AI) faces several legal limitations, summarized as follows:
  • All critical aspects are insufficiently regulated in the reviewed initiatives. There are specific provisions for bias-free training, no enforcement of transparency, insufficient accountability, and privacy is only covered by current data protection laws.
  • Privacy and Data Protection: Existing privacy and data protection laws, such as the Federal Law on the Protection of Personal Data Held by Private Parties (in Spanish Ley Federal de Protección de Datos Personales en Posesión de los Particulares), apply indirectly to AI. However, they do not address all of this technology’s specificities.
  • Ethics and Transparency: Implementing AI poses significant ethical challenges, including ensuring fairness, equity, and transparency in its use. There are currently no laws that address these aspects from a technical perspective.
  • Oversight and Accountability: The algorithms and source code used in AI applications are not clearly supervised or regulated, which can lead to accountability and transparency issues. No current law requires code supervision or accountability for AI systems.
  • Cybersecurity: The lack of a robust legislative framework on cybersecurity also affects the use of AI, as many AI applications depend on the security of the data and systems they operate.
Currently, Mexico lacks any approved legislation governing the use of AI. This allows providers and developers to use a wide range of data from multiple sources for model training and decision-making, leaving users potentially vulnerable to the unethical use of their personal data. This creates uncertainty and risks for both legal professionals and citizens.
These points reflect the need to develop a comprehensive regulatory framework that addresses AI’s specific challenges in Mexico. The regulatory landscape governing artificial intelligence (AI) in Mexico presents a complex interplay of existing legal frameworks and evolving proposals that aim to address the multifaceted challenges posed by AI technologies.
The need for comprehensive regulations, particularly given advances in cross-border technologies such as drone surveillance, underscores the urgency of a legal framework that recognizes national priorities and aligns with international obligations. This alignment is crucial, as it fosters a harmonized regulatory environment that can effectively manage the ethical and legal implications of AI integration while maintaining a human-centered perspective.

5. Challenges and Future Directions for AI Regulation in Mexico

An element of interest in Mexico is that there is currently no specialized framework that regulates the use of AI and protects citizens from discrimination, algorithmic bias [64], false representation, digital identity theft, or other practices that undermine their human rights, nor does it guarantee ethical AI governance. Therefore, a comprehensive legal strategy that addresses current challenges and positions Mexico to harness AI’s potential to drive innovation and social progress remains necessary.
Implementing AI regulations in Mexico presents numerous challenges, primarily due to the intricate interplay between legal, regulatory, and technical domains. The development of governance regimes for AI must intricately weave human rights, democracy, and the rule of law into a cohesive framework, requiring a comprehensive approach that recognizes these interconnections [65]. The technical challenges are further compounded by the need to establish robust regulatory frameworks that address privacy and security concerns, which are paramount given AI’s potential to disrupt existing norms across sectors such as medicine, finance, and law [66].
Furthermore, the introduction of new legislation must be balanced with efforts to reduce regulatory barriers to foster innovation while ensuring ethical compliance, which remains a significant challenge for countries such as Mexico, where emerging economies are struggling to keep pace with global advancements in AI technology [67]. Addressing these challenges demands concerted efforts to align legal frameworks with technological realities, ensuring that AI not only advances but does so in a manner consistent with the broader sociopolitical and ethical landscape.
Given the identified gaps in existing regulatory frameworks, Mexico’s approach to managing ethical concerns related to AI is multifaceted and strategic. Recognizing the global discourse on AI ethics, Mexico, along with other emerging countries like Jordan, recognizes the pressing need to address ethical considerations as a critical challenge in the AI landscape [67]. Mexico’s strategy includes not only aligning with international ethical standards but also adapting solutions to its specific socioeconomic context, thereby distinguishing it from wealthier countries that face similar ethical dilemmas [68,69].
Notably, Mexico was among the first nations to initiate discussions on AI regulation in 2018, emphasizing the need for each country to define its own AI regulatory framework, reflecting a proactive stance in shaping ethical guidelines tailored to its national priorities [3]. By integrating these considerations into its AI strategy, Mexico aims not only to protect against potential ethical pitfalls but also to leverage AI to foster local talent and innovation, thereby ensuring ethical AI development that is both locally relevant and globally informed [70]. This comprehensive approach underscores the need for ongoing dialogue and the adaptation of ethical frameworks to keep pace with technological advancements, highlighting the importance of collaborative efforts among nations to establish robust and context-aware AI policies.
When considering future legislative measures to improve AI regulation, it is crucial to adopt a comprehensive approach that encompasses both national and international perspectives. Nation-states recognize the need to establish national committees to ensure greater oversight of AI weaponry, which is aligned with broader national defense strategies [71]. However, as AI technologies transcend national borders, the need for international cooperation becomes evident.
Participation in international forums is essential to address domestic policy differences and align them with global regulatory standards. Such cooperation is particularly important when managing the strategic risks associated with lethal autonomous weapons systems (LAWSs), as unilateral actions by individual states are insufficient to address the complexities of these technologies [71]. Furthermore, policymakers are urged to collaborate with key allies to advance humanitarian objectives, emphasizing the ethical dimensions of AI regulation. This multilateral participation not only ensures a harmonized regulatory landscape but also fosters the creation of international standards that safeguard fundamental rights while encouraging responsible technological advancement.
It is important to note that the difficulty of regulating AI is tied to its characterization as artificial intelligence, with existing and new conflicting notions of the meaning of “artificial” and “intelligence” [72]. Therefore, future legislative measures must be adaptable, ensuring they nurture technological progress while remaining firmly anchored in ethical and social well-being.

5.1. Actionable Recommendations

In developing our recommendations, we considered the ten core principles that outline a human rights-centered approach to the Ethics of AI as defined by the United Nations Educational, Scientific, and Cultural Organization [73].
  • Proportionality and Do No Harm. “The use of AI systems must not go beyond what is necessary to achieve a legitimate aim. Risk assessment should be used to prevent harm which may result from such uses”.
  • Safety and Security. “Unwanted harms (safety risks) as well as vulnerabilities to attack (security risks) should be avoided and addressed by AI actors”.
  • Right to Privacy and Data Protection. “Privacy must be protected and promoted throughout the AI lifecycle. Adequate data protection frameworks should also be established”.
  • Multi-stakeholder and Adaptive Governance & Collaboration. “International law & national sovereignty must be respected in the use of data. Additionally, participation of diverse stakeholders is necessary for inclusive approaches to AI governance”.
  • Responsibility and Accountability. “AI systems should be auditable and traceable. There should be oversight, impact assessment, audit, and due diligence mechanisms in place to avoid conflicts with human rights norms and threats to environmental wellbeing”.
  • Transparency and Explainability. “The ethical deployment of AI systems depends on their transparency & explainability (T&E). The level of T&E should be appropriate to the context, as there may be tensions between T&E and other principles such as privacy, safety, and security”.
  • Human Oversight and Determination. “Member States should ensure that AI systems do not displace ultimate human responsibility and accountability”.
  • Sustainability. “AI technologies should be assessed against their impacts on ‘sustainability’, understood as a set of constantly evolving goals including those set out in the UN’s Sustainable Development Goals”.
  • Awareness & Literacy. “Public understanding of AI and data should be promoted through open & accessible education, civic engagement, digital skills & AI ethics training, media & information literacy”.
  • Fairness and Non-Discrimination. “AI actors should promote social justice, fairness, and non-discrimination while taking an inclusive approach to ensure AI’s benefits are accessible to all”.
In addition, according to the proposals of [74], we consider the following recommendations:
11.
The Judiciary must collaborate with AI, ethics, and human rights experts to develop ethical and legal guidelines and standards for the use and application of AI-based technologies in the judicial system.
12.
The capabilities of the National Electoral Institute (INE) should be strengthened through the creation of a regulatory framework that defines the limits and conditions under which AI-based tools can be used in political campaigns, electoral propaganda, and the dissemination of election-related information.
13.
The capabilities and regulatory framework of the National Institute for Transparency, Access to Information, and Personal Data Protection (INAI), as the competent body for personal data protection, should also be strengthened and modified to include the supervision of and compliance with regulations related to the use of AI-based technologies and personal data protection, and establish clear and specific regulations for data management in the cloud and in data centers.
14.
It is recommended to strengthen the capabilities of the Federal Economic Competition Commission (COFECE) as a regulatory body that promotes competition and equitable access to data so that new technologies, such as those based on artificial intelligence, are accessible to all.
It is also recommended to update the federal law on the protection of personal data held by private parties and the general law on the protection of personal data held by obligated subjects.

5.2. Possible Social Actors That May Influence Technological Decisions in the Country and Technology Regulation

Several social actors in Mexico influence the development of AI. In 2018, a national coalition of stakeholders from industry, academia, and civil society, called IA2030.mx, was launched to coordinate efforts, build a unified voice to address AI, and promote continued action and support for the topic. This coalition developed the first National AI Agenda, based on the collective intelligence of more than 400 people. However, the website (IA2030.mx) is no longer active.
According to the AI Readiness Index (https://oxfordinsights.com/ai-readiness/), accessed on 29 December 2025, Mexico does not currently play a leading role in Latin America and the Caribbean, ranking eighth. In fact, from 2020 to 2025, the country’s performance declined across key indicators (Table 3) and moved from fifth to eighth in the region.
Table 3. Mexico’s performance regarding AI, according to the AI Readiness Index.
To address this situation, we identified several social actors in Mexico who can contribute to AI regulation and the safe development of AI.
  • The Center of Industrial Innovation and Artificial Intelligence (Centro de Innovación Industrial e Inteligencia Artificial, CII.IA).
  • fAIrLAC+.
  • The Mexican Academy of Computation (Academia Mexicana de Computación, AMEXCOMP).
  • The Mexican Academy of Cidersecurity and Digital Law (Academia Mexicana de Ciberseguridad y Derecho Digital, AMCID).
  • The Mexican Association of the Information Technology Industry (Asociación Mexicana de la Industria de Tecnologías de Información, AMITI).
  • The Mexican Society of Artificial Intelligence (Sociedad Mexicana de Inteligencia Artificial, SMIA).
  • The National Alliance for Artificial Intelligence (Alianza Nacional de Inteligencia Artificial, ANIA).
  • The White Box Project.
  • United Nations Development Program (PNUD Mexico).
Furthermore, we emphasize the importance of collaborating with key allies to advance humanitarian objectives, thereby ensuring that ethical considerations remain central to AI regulation. While Mexico’s approach to AI regulation is strategic and multifaceted, recognizing AI’s unique opportunities and challenges is essential to creating a robust legal framework that safeguards fundamental rights.
Ongoing dialogue in international forums highlights the need for cooperation to address policy differences and establish global regulatory standards that can guide nations in their AI governance. Despite these proactive measures, we recognize the limitations of traditional legal structures in addressing the rapid evolution of AI and the ethical dilemmas it presents. Therefore, future research should focus on developing innovative regulatory proposals that not only address current challenges but also anticipate the dynamic nature of AI technologies.
By fostering local talent and innovation, Mexico can leverage AI as an engine of social progress while ensuring that its development remains ethically sound and globally informed. In conclusion, the interplay between national and international regulatory measures underscores the need for an adaptive, inclusive legal strategy that positions Mexico favorably in the global AI landscape, ultimately contributing to the responsible advancement of AI technologies.

Author Contributions

Conceptualization: Y.V.-R. and O.C.-N.; Methodology: Y.V.-R., M.A.-P. and E.A.; Validation: Y.V.-R., O.C.-N. and M.A.-P.; Investigation: E.A., M.A.-P., A.C.-J. and J.M.-H.; Writing—Original Draft Preparation: E.A., A.C.-J., J.M.-H., M.A.-P., Y.V.-R. and O.C.-N.; Writing—Review and Editing: Y.V.-R., O.C.-N., M.A.-P. and E.A.; Supervision: O.C.-N.; Project Administration: O.C.-N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

All data used in this review are publicly available on the website http://sil.gobernacion.gob.mx/Busquedas/Basica/ (accessed on 16 February 2026) hosted by the Secretary of the Interior (Secretaría de Gobernación, in Spanish) of the Mexican government.

Acknowledgments

The authors would like to thank the Instituto Politécnico Nacional (Secretaría Académica, Comisión de Operación y Fomento de Actividades Académicas, Secretaría de Investigación y Posgrado, CIDETEC, ESIME-Zacanteco, and UPIICSA), OMI University, the Secretaría de Educación Pública, the Secretaría de Ciencia, Humanidades, Tecnología e Innovación, and the Sistema Nacional de Investigadoras e Investigadores of Mexico, for their support in developing this work. During the preparation of this manuscript, the authors used the Grammarly tool for the purposes of English correction. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

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