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[TECHNOLOGY] · Czechia, Germany, Slovakia · 4 sources

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Cybersecurity and IT infrastructure evolve amid AI integration

The integration of artificial intelligence into cybersecurity and IT infrastructure is driving significant changes in how organizations protect data and manage operations. In cybersecurity, the value of AI is being measured by its ability to improve decision-making and reduce noise for analysts, rather than simply increasing the volume of alerts. Companies like secunet, Bechtle, and Rheinmetall emphasize that the rise of AI-driven attacks requires new talent with strong analytical skills and a commitment to continuous learning.

To support AI workloads, enterprise IT infrastructure is evolving. Beyond high-performance GPUs, there is an increasing need for specialized storage architectures, fast data access, and cyber-resilience. Companies such as Cohesity are focusing on data security and recovery to ensure that information remains usable and protected following an attack.

Furthermore, experts warn that cybersecurity must extend beyond digital defenses like firewalls and antivirus software. Physical risks to IT infrastructure—including overheating, fire, moisture, and unauthorized physical access—can disrupt operations just as effectively as a cyberattack. Comprehensive protection requires addressing both the digital and physical environments of data centers and server rooms.

Entities

Bechtle · Cohesity · Czech Association of Artificial Intelligence · GoodCall · José Kadlec · RITTAL s. r. o. · Rheinmetall · Tomáš Nagy · secunet

Claims

What the coverage asserts, and how many sources carry each claim.

  • [○ 1 SOURCE] AI's value in cybersecurity depends on whether it enables professionals to work more effectively and make better decisions, rather than just its presence. www.systemonline.cz
  • [○ 1 SOURCE] IT infrastructure can be disabled by physical risks such as fire, water, overheating, or unauthorized physical access, not just hacking. www.podnikajte.sk
  • [○ 1 SOURCE] Recruitment AI tools must be adaptable because different clients, such as telecommunications operators, have different rules regarding cloud services and data.