Mexico - AI Strategy Development

Overview

The white paper "Towards an AI Strategy in Mexico: Harnessing the AI Revolution" (June 2018) was commissioned by the British Embassy in Mexico and produced by Oxford Insights and C Minds. It provides a diagnostic of Mexico's AI readiness, evidence-based projections of the labour-market impacts of automation, and 21 recommendations organised across governance, data infrastructure, research & development, skills, and ethics & regulation. The document argues Mexico should institutionalise leadership, create a national AI research centre, strengthen data governance and open-data practices, and prioritise inclusive education and skills development. The full text is available from C Minds: Towards an AI Strategy in Mexico (PDF).

Definitions

The report uses a practical, policy-oriented definition of AI: computational systems that perform tasks traditionally requiring human intelligence, including machine learning, natural language processing, computer vision and other subfields. It distinguishes levels of application (research, applied development, and deployed systems) and clarifies terms such as "AI system", "automation impact", "open data", "data trusts" and "sandbox" in the Mexican policy context. The authors emphasise a human-centred framing: AI systems are tools to improve public services and productivity, not substitutes for governance or rights protections.

Governance and Institutional Framework

The report recommends Mexico create a permanent institutional lead to coordinate AI policy across ministries, regulator bodies and subnational governments. It proposes either a national centre for AI (modelled on institutes like the UK Alan Turing Institute) or a dedicated AI office within the Office of the Presidency that would: set strategy, coordinate R&D agendas, steward public data assets, oversee procurement guidance for public AI systems, and convene multi-stakeholder fora. The paper also recommends a Subcommission on AI within the Comisión Intersecretarial para el Desarrollo del Gobierno Electrónico (CIDGE) and closer involvement of constitutional autonomous regulators (e.g., INAI, IFT, COFECE) to ensure policy coherence across data protection, competition, telecoms and transparency domains. See the government response and subsequent guidance developed by the Coordinación de Estrategia Digital Nacional at Coordinación de Estrategia Digital Nacional and the C Minds report at C Minds / Oxford Insights (2018).

Key Focus Areas

The report focuses on five strategic pillars: 1) Governance, government and public services — recommending institutional leadership, public-sector procurement guidance and impact assessment for deployed systems; 2) Data and digital infrastructure — prioritising open-data standards, interoperable formats, secure data-sharing mechanisms and the exploration of data trusts; 3) Research & development — boosting applied R&D, incentivising private-sector labs to operate in Mexico and supporting startups; 4) Capacity, skills & education — building AI curricula, reskilling programmes for at-risk sectors, and strengthening postgraduate research; and 5) Ethics and regulation — publishing ethical guidelines and regulatory principles to protect rights, reduce bias, and enable safe innovation. The paper highlights sectoral opportunities (health, education, transport, tax and public administration) and identifies manufacturing and construction as sectors with concentrated automation risk.

Implementation Framework

Implementation recommendations include: establishing a national AI roadmap with short-, medium- and long-term milestones; a permanent coordinating body (or National Centre for AI); funding lines for R&D and public-private co-investment; pilot projects and sandboxes to test regulatory approaches; procurement reforms to encourage responsible supplier behaviour; and a multi-stakeholder "AI coalition" to keep civil society and industry engaged. The authors stress continuity across political administrations and recommend anchoring long-term strategy in existing instruments such as the National Digital Strategy and intersecretarial commissions. For practical tools and case examples the paper references existing Mexican pilots and local initiatives and provides templates for impact assessment and governance processes in the public sector (full report).

Monitoring and Evaluation

Monitoring should combine quantitative indicators (investment in AI R&D, number of AI-related start-ups, open data availability, broadband coverage, public procurement metrics) and qualitative reviews (stakeholder consultations, ethical audit outcomes). The report suggests periodic public reporting, independent evaluation, and use of pilot sandboxes to learn regulatory lessons. It also recommends integrating AI readiness indicators with international indices (e.g., Oxford Insights Government AI Readiness) for benchmarking.

Penalties, Liability, and Appeals

The white paper itself is non-binding and does not prescribe novel administrative penalties. Instead it recommends that regulation of harms and liability be aligned with existing legal frameworks (data protection law, consumer protection, administrative law and sectoral statutes). For AI deployed in the public sector it proposes impact assessments, appeals mechanisms for affected citizens, and transparency obligations on procurement to enable accountability. Any enforcement would typically rely on agencies such as INAI (data protection/transparency) and PROFECO (consumer protection); technical guidance or mandatory standards could later be added by coordinating bodies.

Relationship to Other Instruments

The strategy is explicitly designed to complement Mexico’s National Digital Strategy and other digital-government initiatives. It references, and is intended to inform, the Coordinación de Estrategia Digital Nacional’s own guidance for the federal administration, as well as interagency coordination through CIDGE and related agency-level policies. The white paper is positioned as an input for legislative or regulatory reforms, but it does not supersede sectoral law; rather, it recommends alignment with data-protection rules, intellectual-property regimes and procurement law to enable AI adoption while protecting rights.

International Alignment

International alignment is an explicit objective. The report compares Mexico with early AI strategies worldwide and recommends adherence to international best practices, engagement with OECD.AI, the G20/OECD principles, and multilateral fora. The authors encourage Mexico to join international coalitions, to adopt interoperable standards, and to participate in international research collaborations. The British Embassy’s involvement and the report’s cross-border comparisons aim to situate Mexico within a global governance dialogue (UK Government / British Embassy updates).

Implementation Timeline

Stage	Actions	Indicative timing
Immediate	Publish recommendations; create coordinating working group; launch national AI coalition	0–6 months
Short-term	Establish permanent AI office/centre; pilot sandboxes; publish procurement guidance and impact-assessment templates	6–18 months
Medium-term	Fund R&D programmes; national skills/reskilling programmes; data governance reforms	18–36 months
Long-term	Institutionalise national AI roadmap; evaluate impacts; adopt any needed sectoral regulation	3–5 years

Compliance Checklist

Requirement	Who	Action
Designate AI lead	Federal government	Create permanent office or national centre
Publish AI procurement guidance	Public procurement units	Apply impact assessments and transparency clauses
Data readiness	Data custodians	Publish machine-readable, interoperable datasets
Ethics & rights	All actors	Adopt human-rights based principles and conduct bias testing

Sources and References

Source	Type
Towards an AI Strategy in Mexico: Harnessing the AI Revolution (C Minds / Oxford Insights, June 2018)	Primary Source
Panorama de la Inteligencia Artificial en México (British Embassy / GOV.UK, March 2024)	Primary Source (Government update)
Coordinación de Estrategia Digital Nacional (gob.mx)	Primary Source (Government)