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Portrait of Alejandro Rudloff Muñoz.

Alejandro Rudloff Muñoz

Engineer, MBA and doctoral student in Management at Universidad de Talca.

Humans with AI, or humans for AI?

At this moment of technological singularity, developing people and organizations that make AI their strategic co-thinker to address complex problems means taking their capacity to frame, understand, model, decide and implement solutions beyond anything ever possible in our history.

It all starts with a skill that can be learned: asking meaningful questions. Without it, we delegate. With it, we think better.

The new role of learning

Yesterday we learned, today we transform

Companies are exposed to shifts in markets and technology, to economic shocks and to the pressures of the productive and working world. Education, at every level, needs a direct channel to that reality in order to respond in time, both in forming new generations and in the continuing education of those working today. The speed of change forces reinvention in ever shorter cycles: what once took years is now renewed continuously. That is why learning is no longer enough: it takes transformation, reconfiguring one's own way of thinking at the pace the world imposes.

  • Education

    Education, at every level, is where the skill of asking meaningful questions is cultivated. Leading-edge educational innovation, aligned with the most advanced knowledge on how people learn, forms people able to contribute to the challenges of their time.

  • Organizations

    Every human group is an organization: a company, an educational institution, a social organization or a team. All of them live by learning, and that is how they endure, adapt and evolve. Today every organization is exposed to the effects of generative AI, and reflective dialogue with those facing this paradigm shift is vital to build a new social foundation.

  • Research

    Conducted within the Doctorate in Management at Universidad de Talca, this research studies the conditions that advanced use of AI at work requires. To do so, it brings together what is observed in education and the experience of organizations exposed to the changes of the technological singularity.

Five phases to solve a complex problem

Each phase starts with a question. Asking it well is what turns AI into a co-thinker rather than an executor.

Opening up the problem

  1. Frame

    What is the real problem, the one that matters and not just the urgent one?

  2. Understand

    What causes it and whom does it affect?

  3. Model solutions

    What paths are there, beyond the obvious one?

Solving it

  1. Decide

    Which one do I choose, and what am I risking?

  2. Implement

    How do I carry it out, and how will I know it works?

See the conceptual framework →