According to the World Economic Forum’s "Future of Jobs 2023" report, nearly half the skills needed to operate in the labor market will change in the next five years. Translated into reality: the professional who is key to an organization today may need a profound transformation tomorrow to continue generating value.
McKinsey estimates that up to 375 million people will need to professionally reskill before 2030 due to AI, automation, and digital disruption. But in which direction should this transformation occur? The answer is not merely learning to code. It's about learning to collaborate with machines, lead with data, and think critically.
1. Power Skills: The True Differentiator in the Age of Machines
Large companies no longer seek technical abilities alone. What makes the difference are hybrid profiles, capable of integrating the digital with the human. "Power skills," as LinkedIn dubbed them in its 2024 Learning Trends report, now define employability.
Critical thinking, emotional intelligence, collaborative leadership, intercultural communication, and adaptability. They all point toward the same thing: the ability to connect human intelligence with technological potential. Because someone still needs to interpret AI models, identify biases, lead diverse teams, and communicate findings strategically. And that task cannot yet be delegated to an algorithm.
2. Constant Reskilling: Building Talent as a Competitive Advantage
Technical knowledge quickly becomes obsolete. According to multiple studies, many digital skills become irrelevant in less than two years if not updated. That is why the best talent programs are not conceived as one-off courses but as ecosystems of continuous learning.
What works combines technical training (AI, data, security, automation) with the development of human skills applied to digital contexts. And the key is not just the content, but also the format: microlearning, simulations, internal mentors, and collaborative learning.
At Q-Vision Technologies with IzyAcademy, we develop adaptive capabilities, contextualized and with a direct impact on business results. A training platform designed to scale technological and human skills at the pace of the teams, not just the market.
3. Knowing How to Connect with AI, Not Just Program It
A study by MIT Sloan Management Review makes it clear: the most valuable professionals of the future are not those who know how to program, but those who know how to interact with technology, give it direction, and translate its value into business language.
The human-AI interaction thus becomes a new core competency. Knowing how to ask questions that optimize the response of generative models (such as prompt engineering). Creating frameworks for supervision and technological ethics. Becoming the "bridge" between data science and decision-making.
This new layer of talent must be designed today, before the market demands it massively. And that is where talent teams reinvent themselves as generators of new capabilities for an increasingly present future.
4. Generational Diversity and Inclusive Learning
The demand for digital talent intersects with an interesting phenomenon: the coexistence of several generations within the same company. Digital natives, technology migrants, and reskilling profiles must learn and teach together.
In this sense, the most advanced talent strategies bet on inclusive learning models: reverse mentoring, cross-training, adaptive platforms, and intergenerational coaching. The important thing is not that everyone learns the same things, but that everyone evolves at their own pace and contributes to an organizational culture with a shared vision.
