Who Will Really Control the Intelligence of the Future?

Artificial intelligence is already changing the way data is created and used, and the role of the infrastructure that supports it is also changing. Data centers remain fundamental as they provide computing power and system reliability, but they do not, by themselves, determine how that intelligence will be used. A crucial shift is occurring with the development of AI environments that introduce standardization, orchestration, and management, transforming infrastructure into a system capable of continuous application of artificial intelligence.

In this new context, the advantage will not belong to those who merely own the infrastructure, but to those who can connect data, models, and processes into a functional and controlled system: from data storage to model training to their application and measurement of results.

Control is thus increasingly shifting from the resource level to the management level, i.e., to the ability of organizations to apply artificial intelligence reliably, securely, and in accordance with their own business and regulatory framework. This includes technology companies, but also states and regional initiatives that develop their own capacities and regulatory frameworks.

Key Question: Control

With the development of such systems, the question of control comes to the forefront.

– The biggest challenge is not in technology, but in data: where it is located, who manages it, and under whose jurisdiction it falls. Without that, there is no real control over the systems that make decisions – emphasizes CEO of DataBox Filip Olujić.

The question of ownership of the infrastructure on which these systems operate is becoming increasingly important, as only the combination of local data and local infrastructure enables security and compliance.

Infrastructure as the Foundation of AI

In this layer, DataBox plays its role. As a provider of integrated infrastructure – data center, cloud and network connectivity – it enables users to have a stable and controlled environment for developing digital solutions. The focus is on availability, security, and keeping data within the same jurisdiction. Such infrastructure becomes the foundation for the development of AI systems. Advanced solutions based on artificial intelligence are developed on it.

An example is Datum, a solution that DataBox is developing with partners, which allows organizations to manage AI agents within their own closed environment. The key difference compared to global AI systems is that it relies exclusively on user data, which is why complete control over data and results is maintained.

AI Factories Without the Hype

AI factories are not a new type of data center, but a way in which existing infrastructure is used. It is a model that enables continuous development and application of AI systems with clear processes, resource control, and cost predictability. The key change is that artificial intelligence is no longer viewed as a series of isolated experiments, but as part of the operating system. This implies standardized data flows, resource management, and the ability for different teams to work on the same infrastructure without the need for ad hoc solutions.

In practice, this means a shift from individual AI projects to systematic and measurable application. Organizations can thus plan capacities, monitor effects, and integrate artificial intelligence into everyday business processes – while maintaining control over data and systems.

Therefore, control of the intelligence of the future will not belong to a single actor, but to those who can connect and manage the key layers of the system: the infrastructure, data, and models on which artificial intelligence is based.