The transformations that the Information Technology area has experienced in recent years go beyond digitization. They involve intelligence, automation and real-time decision making. Integration between data, algorithms and operational processes not only modernizes structures: it changes the logic of the operation.

IT management is no longer reactive to become predictive, context-sensitive and, increasingly, AI-driven. In this article, we explain how organizations are applying AI to drive efficiency, bolster security, and transform the experience of internal and external users.

From Response to Anticipation: The New Role of AI in IT

Traditional models of service desk and technical support worked, for a long time, under a corrective logic. The user identified a problem, opened a call and waited for service. Today, this approach no longer meets the expectations of agility, productivity and fluidity that the market demands.

With the use of AI, IT management evolves into an invisible layer of support, which anticipates bottlenecks, corrects faults in an automated way and acts transparently. Technologies such as machine learning and predictive analytics have created a new operational infrastructure, more resilient and prepared for peaks in demand, vulnerabilities and systemic failures.

Real use cases: intelligence as an ally in everyday life

Companies such as Dasa and Positivo S+ already demonstrate, in practice, how this integration takes place on multiple fronts. On the one hand, AI models act in the analysis of large volumes of clinical data, optimizing research and diagnostic processes. On the other hand, technologies such as the Estella platform monitor users' devices, identify failures before they become incidents and automate the opening and resolution of tickets.

Instead of relying exclusively on rigid SLA contracts, these companies are already adopting models based on user experience, the XLAs, where the focus is to deliver fluidity and continuity imperceptibly. This means that problems are solved even before the user realizes their existence.

People at the center: AI as a tool, not a substitute

Integrating AI into IT management is not about reducing people, but about expanding the reach of human capabilities. With automated operational tasks, professionals can dedicate themselves to analysis, innovation and strategy.

The role of the IT professional is transformed, gaining more prominence in the curation and evolution of intelligent systems. The monitoring of outputs, the calibration of models and the validation of automated decisions become central activities.

Connecting IT to internal audit: data, governance and predictability

The strategic use of AI in IT is also reflected in areas such as auditing and compliance. As we discuss in the article“Internal audit and automation”, process automation and intelligent data analytics are redefining how risks are assessed and decisions are informed.

In the context of governance, this integration strengthens the traceability of actions, improves the quality of audit evidence and allows anomalies to be identified in real time. With this, the audit anticipates risks, reduces failures and expands its ability to add strategic value to the organization.

The challenge of maturity in AI and data culture

Despite the promising scenario, many leaders still face barriers to advance in digital maturity. Or the main obstacle? The difficulty in demonstrating the real value of AI to the business.

Without a solid data culture, adoption of artificial intelligence tends to be fragmented and limited. In addition, the scarcity of trained professionals and the absence of robust governance make it difficult to gain scale.

The construction of this maturity involves:

• Clarity in defining use cases with measurable impact;
  

• Engaging leaders to guide culture and strategy;
  

• Structuring a solid database, with quality and security;
  

• Investment in training, especially at the intersection between IT, business and data science.
  

Ethics, privacy and regulation: AI under responsibility

Every transformation carries risks. In the case of artificial intelligence, most of them are in the use of sensitive data without control. Corporate use of AI requires clear policies, robust data governance structures, and a careful look at ethical implications.

The absence of regulation in Brazil still represents a challenge, but this cannot be justified for neglecting security and transparency. Organizations that want to position themselves sustainably in the market will need to adopt good practices from now on, including to anticipate requirements that will be mandatory soon.

The future is proactive, invisible and supervised

The trend is for AI solutions to solve problems without triggering users, acting in an integrated way to all areas of IT - from infrastructure to security, from service desk to digital experience. Support becomes invisible, IT gains operational intelligence, and the organization reaps gains in scale, resilience and trust.

But no intelligent system operates alone. Human supervision remains essential, both in the validation of the results and in the evolution of the models. The balance between automation and discernment will be the differential of the teams that will lead the future of technology in companies.

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