AI Training

CONOCER (Consejo Nacional de Normalización y Certificación de Competencias Laborales) is Mexico's federal authority for labor competency standards and certification. A CONOCER-certified AI program meets defined competency standards, uses a structured assessment methodology, and produces certifications recognized by Mexico's education and labor systems — not just a certificate of attendance.

Standard online AI courses teach concepts and tools in isolation. NDA designs programs around what participants need to do after training — in their specific role, with the tools their organization already uses. Programs include practical application exercises, real-use-case design, and assessment against defined competency outcomes. Certification is tied to demonstrated performance, not completion.

Program content is scoped to the tools and workflows relevant to each organization — not a generic survey of every AI platform. Common coverage includes large language models (Claude, GPT-4, Gemini), AI-assisted content and communication tools, automation platforms (Make, Zapier with AI nodes), and AI-enhanced CRM and analytics. The goal is applied fluency in the tools the team will actually use.

AI awareness means people understand that AI tools exist and have a general idea of what they do. AI fluency means people can apply AI tools to their actual work, evaluate output quality, identify where AI judgment is unreliable, and integrate AI into their workflows to produce better outcomes faster. Most organizations achieve awareness quickly; fluency requires structured practice with feedback.

Start from use cases, not from technology. Non-technical learners engage with AI training when it's framed around problems they already recognize — drafting faster, researching better, analyzing data they couldn't process before. Technical architecture, model mechanics, and infrastructure are irrelevant for most non-technical staff. First-principles thinking and practical application are what move the needle.

Pre- and post-program competency assessments, output quality evaluation (before and after training on real work tasks), 60-day follow-up on actual tool adoption and workflow integration, and manager assessment of behavioral change. Self-reported confidence scores are a baseline measure but not sufficient — actual output quality and tool adoption are what matter.

Participants who complete NDA's CONOCER-aligned programs receive competency certificates recognized under Mexico's national competency framework. For corporate programs not tied to CONOCER standards, participants receive Innovation program certifications — documentation of the competencies assessed and the level of performance demonstrated.

NDA delivers both in-person and remote-synchronous formats, as well as hybrid programs where conceptual content is delivered asynchronously and application workshops are live. The format is scoped to each engagement — remote delivery requires more structured facilitation to maintain engagement and produce the same hands-on practice outcomes as in-person.

Innovation typically scopes corporate programs for teams of 10 or more. Smaller groups can participate in open enrollment cohorts scheduled periodically. The minimum is driven by program economics, not learning design — smaller teams get better outcomes from cohort programs where the group is working through similar real-use cases together.

Core competency frameworks (how to evaluate AI output, how to design effective prompts, how to integrate AI into workflows) change slowly — these can be refreshed annually. Tool-specific training needs refreshing every 6 months at minimum, and immediately after major platform changes. NDA's program structure separates foundational content from tool-specific modules to make this maintenance tractable.