Sure! Here’s the translation into American English:
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The transformation that artificial intelligence (AI) is bringing to digital infrastructure is reshaping the rules of the game in cybersecurity, a field that has become a crucial battleground for technological confrontation. As we approach 2025, the cyber landscape presents itself as a scenario of intensification in the struggle between defenders and attackers, with AI playing roles as both aggressor and protector.
Recent data indicates that 87% of organizations worldwide suffered AI-influenced cyberattacks in the last year. This phenomenon has fueled explosive growth in the AI-based cybersecurity market, which is projected to reach $82.56 billion by 2029, growing at an annual rate of 28%. This boom not only represents a window of opportunity but also an urgent response to threats that adapt at a speed that conventional solutions can barely keep up with.
Attackers have found in AI a formidable ally that allows them to rewrite attack tactics. Old security recommendations, such as detecting typos in emails, have become obsolete. Generative AI can create hyper-personalized phishing messages that are devastatingly effective. For example, emails generated by this technology have click-through rates of 54%, compared to just 12% for messages crafted by humans.
The risks associated with this new era are more than evident. In 2024, a finance employee in Hong Kong fell victim to a scam resulting in the transfer of $25 million after a video conference with participants who were actually AI-generated imitations. Additionally, phishing techniques are being democratized, making it easier for common cybercriminals to carry out convincing campaigns with minimal effort.
In the realm of malware, the situation is equally alarming. Attackers are now using software that constantly modifies its structure to evade traditional defenses. This type of malware can adapt in real-time to the security systems of its victims, making detection significantly more difficult. At the same time, AI is being used to automate various stages of the hacking process, allowing malicious actors to explore networks and discover vulnerabilities without human intervention.
However, defensive tools are also evolving. Security teams have begun using AI as a powerful resource, shifting from a reactive approach to a proactive one that enables the prediction and neutralization of threats in real time. Advanced systems can create behavior profiles within networks and look for anomalies that indicate hidden compromises.
Furthermore, the implementation of “Zero Trust” security models—based on the principle of “never trust, always verify”—is becoming the norm. This allows for real-time decisions on data access based on user behavior.
Despite these advancements, serious concerns remain regarding the security of AI systems themselves. There are risks of adversarial attacks that can compromise machine learning models, leading to catastrophic errors. The threat of autonomous agents, which operate without a real understanding of what constitutes malicious activity, is also on the rise.
To counter these vulnerabilities, the practice of AI-specific “red teaming” is suggested, a technique that simulates attacks to test and strengthen systems. The growing AI revolution in cybersecurity highlights the need for a balance between defense and offense. Organizations that succeed in mastering this duality will be those that thrive in an environment where costs for AI-related incidents average $4.8 million per breach. The algorithmic arms race has begun, and success will depend on the strategy and human understanding that support its implementation.
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via: MiMub in Spanish
