KAEFER RIP Industrial Services

Joao Junior

Responsible Innovation Champion

João Junior is Brazil Technology Manager at KAEFER Group, with 20 years of experience in Information Technology. He holds postgraduate qualifications in Technology Management, Artificial Intelligence, Data Strategy and Organizational Efficiency. Currently a member of the Brazilian Association of Artificial Intelligence.

Artificial Intelligence is no longer just a technology trend. It has become part of everyday business. In only a few years, we have seen rapid advances in models, platforms and applications that support activities once requiring substantial human effort. Along with this progress, however, come equally important challenges involving data control, information security, regulatory compliance and, above all, governance.

The speed at which new solutions reach the market makes it difficult for many organizations to keep track of what employees and partners are using. Generative AI tools, digital assistants, intelligent automation and autonomous agents are entering companies, often faster than control mechanisms can evolve. Innovation and risk now move side by side, requiring a structured approach to ensure responsible use.

Moving AI into the Strategic Core

Few technologies have transformed the way people work as quickly as Artificial Intelligence. More than a new tool, it represents a significant cultural shift in the corporate environment.

AI expands human capacity, reduces repetitive tasks, accelerates analysis and allows professionals to devote more time to higher-value activities. Processes that once took hours or even days can now be completed in minutes, significantly increasing productivity.

At the same time, technology has never been as closely connected to the business as it is today. Historically, IT was often viewed as an operational support function. Today, technology decisions directly affect revenue, competitiveness, operational efficiency and customer experience. Artificial Intelligence has made that connection even clearer by placing technology at the center of strategic discussions.

The question is no longer “should we use AI?” It is “how can we use it securely, with appropriate controls and in alignment with the company’s objectives?”

Between AI Restriction and Uncontrolled Adoption

Across industry events, executive forums and conversations with fellow technology leaders, I see that the greatest challenge is no longer deciding whether we should do something with Artificial Intelligence. The real challenge is how to adopt and govern it.

 ​Governance does not mean preventing innovation. It means establishing boundaries, accountability and controls that allow innovation to move forward safely. 

Many frameworks, methodologies and governance models are entering the market. Although they are important starting points, no single structure will serve every organization equally well. Decisions must reflect each company’s profile, digital maturity and, most importantly, risk appetite.

I frequently see two equally inadequate extremes. On one side, companies impose broad restrictions because of the associated risks. On the other, organizations release tools without direction or control. Blanket restrictions limit innovation and can encourage unauthorized use. Unrestricted access increases the risk of data exposure, noncompliance, intellectual property issues and reputational harm, making governance nearly impossible.

Finding the right balance is the best path forward. Governance does not mean preventing innovation. It means establishing boundaries, accountability and controls that allow innovation to move forward safely.

Moving AI from Models into Business Workflows

In this environment, continuous learning and integrated teams offer the most consistent way forward. The pace of change requires technology, security, legal, data and business teams to evolve together, using a common language and clear responsibilities.

One essential practice is to create an idea funnel that captures opportunities from across the organization. Not every initiative will offer the same return. Companies should prioritize the layers with the highest ROI, whether measured by the number of users reached, the importance of the processes improved, risk reduction or operational and financial gains.

The consultative phase of AI, driven mainly by models that answer questions, summarize, analyze and support decisions, is becoming more mature. The focus is now moving upward to systems and their intersections: integrations with enterprise applications, process automation, agents and business workflow orchestration.

Value will not come only from interacting with language models. It will come from connecting intelligence to the processes that sustain operations. This is where the deeper opportunities for transformation and competitive differentiation will emerge.

Accelerating Governance Alongside AI

Given the current level of investment in infrastructure, research and development, I believe it will be extremely difficult to slow down, as some Big Tech leaders have suggested. In theory, the idea may sound rational. In practice, competitive pressure, investor expectations and the amount of capital involved make a coordinated slowdown very difficult to implement.

Progress will continue at a rapid pace. Therefore, the central discussion should not be limited to how we reduce the speed of innovation. It should focus on how we accelerate the security, control and governance mechanisms that must accompany it.

As capabilities improve, we must advance even faster in data protection, identity, compliance, traceability and responsible use. The goal is to ensure that, at the final checkpoint, harm is minimized and benefits are maximized.

Success will not be defined only by AI adoption, but by the ability to balance innovation and responsibility. Governance will determine which organizations can turn this potential into sustainable, long-term value.