People first: why talent remains the differentiator in the age of AI

Contextual data: 90% of organizations will face IT talent shortages by 2026 · 70% of human skills will remain critical · +70% of companies prioritize continuous learning.

Artificial Intelligence is transforming the way organizations develop software, manage processes, and make decisions. Today, it is possible to automate tasks, accelerate development, analyze large volumes of information, and collaborate on solving complex problems using AI tools that did not exist two years ago.

However, in the midst of this technological evolution, a question arises that I ask myself every day from my role as Chief People Officer: if technology is within everyone's reach, what will differentiate successful organizations?

My answer is clear, and it is not technological: people. Because technology can accelerate processes, but it is people who bring judgment, creativity, context, and real transformation capacity.

The true transformation is not technological. It is human.

Every major technological advancement has generated uncertainty and expectations. The emergence of the Internet, cloud computing, mobile devices, and now Artificial Intelligence have redefined entire industries. But there is a pattern that repeats itself:

The pattern that repeats itself in every technological revolution

• The organizations that best capitalize on technological changes are not those that adopt a technology first.

• They are those that develop the human capacities necessary to leverage it.

• Digital transformation always ends up being a transformation of people.

• The slogan of the Digital Enterprise Show 2026 summarized it precisely: “Machines Learn, People Lead.”

This is not humanistic optimism in the face of technology. It is evidence. According to McKinsey, although theoretically up to 57% of current working hours could be automated, more than 70% of human skills will remain critical. The difference lies in how they are applied, not in whether they exist.

From accumulated knowledge to continuous learning

For many years, the differentiator for professionals was mainly associated with accumulated knowledge. Today we live in a different reality. Information is more accessible than ever, and AI tools allow for obtaining answers and accelerating learning processes at an unprecedented speed.

This is changing the way we understand professional development. The question is no longer just how much a person knows. The question is:

How fast can they learn, adapt, and evolve in the face of new challenges? In an environment where technology is constantly changing, the capacity for continuous learning becomes the most lasting competitive advantage.

— Paula Devincenzi, Chief People Officer · Suris Code

Market data confirms this trend. According to IDC projections, more than 90% of organizations worldwide will face an IT talent shortage by the end of 2026. Not a shortage of technology — a shortage of people capable of using it well. HR trends for 2026 point out that the half-life of technical skills has dropped to just a few months, making the capacity for continuous learning more valuable than any specific skill.

Key data:

• 90% of organizations will face IT talent shortages in 2026 — IDC

• 57% of working hours could be automated — McKinsey

• 70% of human skills will remain critical — McKinsey

The skills that AI does not replace

As operational tasks become automated, human capabilities acquire even greater relevance. The true differentiator in 2026 is not mastering a specific tool, but the ability to integrate AI, strategy, and human skills into a single professional profile.

These are the capabilities that will make a difference in the coming years — and that no AI tool can replace:

• Critical thinking. Analyzing information, questioning results, and making informed decisions — including the outputs of AI itself.

• Problem solving. Identifying challenges, evaluating alternatives, and building effective solutions in complex and changing contexts.

• Communication. Translating complex ideas into clear messages and creating alignment between teams and clients.

• Collaboration. Working together to achieve shared goals in increasingly dynamic and hybrid environments.

• Adaptability. Responding quickly to new contexts, technologies, and business needs without losing focus on the outcome.

• Creativity. Imagining new possibilities and building innovative solutions that AI can execute but cannot conceive.

These capabilities are fundamental because they require something that AI lacks: lived experience, judgment built in context, and a deep understanding of the business and people. AI can generate large volumes of information, but the real value emerges when a professional knows how to interpret that data and turn it into strategic decisions.

The future will not be human or AI. It will be human plus AI.

Frequently the debate is framed as a competition between people and technology. That is the wrong question. The reality is that AI does not eliminate the need for talent — it transforms the way talent generates value.

The new work equation

Speed of AI + Human experience = Sustainable advantage

The most successful organizations will be those that combine the speed of automation and the analytical capacity of AI with the experience of people, business knowledge, and human creativity. Technology amplifies capabilities. People continue to lead the change.

According to McKinsey research, work in 2026 is structured as a partnership between people and software agents. 62% of organizations are already piloting AI agents, and the trend points to a fundamental transition in the worker's role: we are moving from being task executers to orchestrators of digital capabilities. The fastest-growing skill will not be programming per se, but AI fluency: the ability to direct, validate, and collaborate with intelligent systems.

What this means for organizations

The adoption of Artificial Intelligence should not begin with the selection of tools. It should begin with a capability development strategy. There is a substantial difference between a company that buys AI licenses and one that builds the culture to use it well.

This implies:

• Promoting a culture of continuous learning where updating is not an occasional demand but a daily practice.

• Driving permanent training, adapted to the actual pace of tool changes — not annual courses, but modules integrated into the workflow.

• Fostering responsible experimentation, creating spaces where the team can test, fail, and learn without errors carrying a disproportionate cost.

• Accompanying teams in incorporating new ways of working, recognizing that resistance to change is not a lack of will but a lack of support.

• Measuring the human impact of technology, not just tool adoption. People Analytics connected to business results.

Technology evolves rapidly. Organizations that develop people capable of evolving along with it are the ones that generate sustainable advantages over time. The rest just buy tools.

Our vision at Suris Code

Technological innovation and talent development: two sides of the same strategy

At Suris Code, we are an AI First company — we adopt AI tools in development, design, marketing, and talent. But that adoption does not replace people. It empowers them.

That is why we promote a culture based on continuous learning, professional evolution, and the incorporation of new technologies as team capabilities — not as substitutes for the team. AI will continue to evolve. Tools will change. Platforms will transform. But there is something that will continue to be the driver of all innovation: people who know how to learn, adapt, and transform challenges into opportunities.

In our talent acquisition process, we use AI for the initial analysis of candidates — technical and cultural fit. But the final decision is always human. Always.

Frequently asked questions about talent and artificial intelligence

Will artificial intelligence replace software developers?

It does not replace them — it transforms the role. Developers who adopt AI spend less time writing repetitive code and more time on system design, technical decision-making, and quality control. The most valuable skill is not programming per se, but the ability to direct, audit, and collaborate with AI tools. Those who do not adopt this capability will be displaced — not by AI, but by other developers who do.

What are the most in-demand skills in the era of AI?

The most in-demand skills in 2026 are those that AI cannot replicate: critical thinking, complex problem solving, strategic communication, adaptability, and creativity. Added to these is a new one: AI fluency — the ability to understand how AI systems work, what their limitations are, and how to integrate them into daily work productively and responsibly.

How can a company prepare for the IT talent shortage in 2026?

The most effective response is not just hiring more — it is developing the talent it already has. This implies continuous training programs integrated into the workflow, a culture of experimentation with new tools, structured mentorship, and professional development metrics connected to business goals. Companies that treat training as an expense instead of an investment are the ones that will suffer the shortage the most.

What is continuous learning and why is it key in 2026?

Continuous learning is the ability to incorporate new knowledge and skills on an ongoing basis, adapting to the pace of change in the environment. In 2026, it is key because the half-life of technical skills has dropped to months. One-time training — an annual course, a certification — is not enough. The most competitive organizations integrate learning directly into the daily workflow, making updating a practice rather than an event.

How does Suris Code balance AI adoption with the development of its team?

We adopt it as a capability, not as a substitute. Every AI tool we incorporate is accompanied by a training process for the team on how to use it well. Human review is non-negotiable for all critical outputs — production code, customer prototypes, hiring decisions. And we measure the impact of adoption on concrete results: delivery speed, quality, client satisfaction, and professional development of the team.