Short answer: AI readiness is not something you buy with licences or solve with training alone. It is a measurable quality of people: curiosity, learning agility, and abstract reasoning. You can assess it before hiring, not after an AI pilot fails.
Latin America does not have an AI adoption problem; it has the opposite. EY’s Work Reimagined 2025 reports that 93% of workers in the region already use AI tools, compared with 83% globally. Yet only 28% of organisations are able to turn that adoption into high-value outcomes.
The gap is not merely technical. EY estimates companies can lose up to 40% of AI’s potential productivity through gaps in talent strategy. Aon’s 2026 Human Capital Trends study paints a similar picture: many organisations are implementing, piloting, or preparing AI solutions, but still need to turn activity into sustainable results.
Asking whether someone uses a particular tool, requesting prompt examples, or valuing a short course certificate measures a skill with a short shelf life. What lasts is the disposition to learn the next tool: curiosity, comfort with ambiguity, learning orientation, and critical reasoning.
The World Economic Forum estimates that 39% of current skills will change or become outdated by 2030. That is why assessing adaptability provides a more useful signal than checking knowledge of an interface that may change in months.
Training transfers knowledge, but it does not replace the willingness to learn and change. People can attend a course and return to the old process if curiosity, agility, and learning orientation are absent. The critical decision happens earlier: when selecting, promoting, and prioritising who to support through reskilling.
Aon developed an 11-competency Digital Readiness model built on the ADEPT-15 workplace personality questionnaire and the gridChallenge cognitive assessment. Agility, Learnability, and Curiosity sit at its core, helping organisations understand how people may respond to a new technology.
| What you hear | What to assess | Instrument |
|---|---|---|
| “We trained everyone and nobody uses it” | Curiosity and openness to change | ADEPT-15 |
| “The team goes back to the old process” | Agility and ambiguity tolerance | ADEPT-15 |
| “They learn one tool, but not the next” | Learnability and learning speed | ADEPT-15 + gridChallenge |
| “They accept every AI output without question” | Abstract and numerical reasoning | gridChallenge and switchChallenge |
These instruments do not ask whether someone knows how to use ChatGPT. They assess dispositions to learn and apply emerging technology critically: a more durable basis for hiring and development decisions.
In selection: add a learning-agility measure to roles exposed to automation so you can plan the support and development each person may need.
In reskilling: use learning-disposition data to prioritise where a training investment can create the greatest change, alongside your learning and development strategy.
In succession and leadership: update the criteria used to identify potential. Talent development assessments make those decisions evidence-led.
Generative AI exposes a meaningful share of Latin American jobs to changing tasks and skills. The potential value is substantial, but the difference between a pilot and sustainable transformation depends on whether people can learn, challenge, and apply the technology responsibly.
If you are designing roles, processes, or selection for that transition, responsible AI recruitment and talent assessments offer a measurable starting point. That can be assessed before, not after.
For an action-oriented overview, explore the AI Readiness guide for organisations or take the free 12-question readiness check in Spanish.
Yes. Rather than measuring knowledge of one tool, assess dispositions that support adoption of new technology: curiosity, agility under change, learning orientation, and abstract reasoning.
Organisational readiness considers data, governance, infrastructure, and use cases. Individual readiness assesses whether the people who will operate those systems have the disposition and capacity to do so.
Training transfers knowledge, not disposition. Without curiosity and learning agility, people can return to their usual process even after training.
Aon’s ADEPT-15 includes Learnability, Curiosity, and Agility dimensions in its workplace personality model. It can be combined with gridChallenge for a fuller digital-readiness profile.
It works for organisations of different sizes. The assessment is tailored to the role, talent decision, and implementation context.
Want to understand how to assess your team’s digital readiness? Start a conversation with us.
Take the free readiness check in Spanish