I have been closely monitoring the transformation caused by artificial intelligence in the business world. At the center of this revolution, the role of the CIO has been evolving rapidly. It's no longer enough to enable technology. It is necessary to lead the change. And this is where the difference between an operational CIO and a truly transformative CIO lies.
The CIO who acts only as a technical enabler of AI loses the most important part of the equation: the impact on the business. Sure, information security, data architecture, and compliance are fundamental topics, but not enough. The true transformation occurs when AI is designed to change the way the company operates, and this requires a deep understanding of the business model.
Today, a large part of the value of generative AI lies in the orchestration of multi-agent solutions, capable of automating processes, making real-time decisions, and changing the way entire sectors work. For that, the CIO needs to go beyond IT. You need to master strategic design, user experience, and service journey. Only then is it possible to align technology with purpose and impact.
Such alignment is still a barrier for many. According to the studyGartner CIO Agenda 202572% of CIOs worldwide state that artificial intelligence is among the strategic priorities of the technology sector. However, only 24% can prove that they are generating tangible value with the initiatives. This highlights a gap between intention and execution, reinforcing the need for a more active and strategic role for the CIO in the AI journey.
Three key skills to leave the laboratory
If you are a CIO still stuck in the experimentation phase, my clear suggestion is: develop three key competencies to turn the game around and deliver real value.
- Strategic and service design: Understanding how workflows and experiences connect is essential to building AI solutions that make sense within the business.
- Agile experimentation: Nothing replaces the ability to test quickly, fail fast, and learn even faster. Models like Scrum, Lean, and Design Sprint are great allies.
- Adaptabilidade: A IA muda todo dia. New models emerge, APIs transform, regulations appear. The CIO and his team need to be prepared to rebuild whenever necessary. This is part of the game.
Inclusive, a recent study of theMIT Sloan Management Review in partnership with BCGIt points out that only 11% of the analyzed companies managed to achieve a positive financial return with AI. What do they have in common? A strong integration between technology and business strategy, along with clear governance and a focus on value from the outset.
How have I applied this in practice
At the company where I serve as CIO, we made the decision to democratize access to AI from the beginning. We built an internal platform, a true AI hub, that connects different models (including the leading LLMs on the market) in a single interface accessible to all 900 employees.
The measure prevents two common mistakes: uncontrolled use of public tools (which can compromise sensitive data) and limiting the use of AI to isolated niches. Here, everyone has access, from customer service to leadership.
Additionally, we have a public innovation roadmap, updated twice a week, that clearly shows ongoing projects, their phases, deliverables, and next steps. This generates transparency, engagement, and accountability.
Another aspect is the monthly workshops on AI, covering topics such as autonomous agents, prompt engineering, comparison between LLMs, among others. More than 400 people actively participate. And most importantly: we have a C-Level advisory board that prioritizes AI initiatives based on business return.
This type of structure and initiative is increasingly present in Brazil. A IDC Latin America AI Spending Guide 2025It is estimated that Brazilian companies will invest more than US$ 1.9 billion in artificial intelligence solutions this year. The main focuses are process automation, customer service, data analysis, and decision support. In other words, the local market already understands AI as a strategic pillar, no longer as an isolated experiment.
AI is no longer a laboratory — it's a value platform
If I could give advice to other CIOs, it would be: stop treating AI as a laboratory experiment. Choose small use cases with high potential impact and quick implementation, and put them into production. Even if imperfect, these field tests will provide valuable feedback to improve the solution.
The true leap occurs when the development team and end users work together. The ongoing collaboration between technology and business generates more relevant, effective, and lasting solutions.
In the end, good AI is AI that works in the real world. And the CIO who understands this, who builds together with users, ceases to be just a technology manager to become the protagonist of business transformation.
