Artificial Intelligence (AI) is increasingly being exploited by cybercriminals to make digital attacks more sophisticated and difficult to detect. A recent study by Forrester Research, published in January 2025, revealed that AI techniques are being applied to automate fraud, allowing scams such as phishing and deepfakes to become highly personalized and convincing. The report points out that AI-based cyber attacks have grown by 60% in the last year, and that fraud driven by deepfakes already poses a significant threat to companies in a variety of sectors.
In this article, we'll explore how cybercriminals are using AI to create hyper-personalized attacks, from highly adaptive phishing to realistic deepfakes used for financial fraud and corporate espionage. We'll also look at real cases, the main challenges companies face in detecting these scams and the trends for the coming years.
The evolution of digital threats with AI
With the advance of AI, cyber attacks are becoming more sophisticated and targeted. Some of the main changes that this scenario has brought about include:
- Advanced phishing: Personalized emails and messages generated by AI, making fraud more difficult to detect.
- Deepfakes and visual fraud: Cloning voices and faces to deceive employees and simulate false identities.
- Attack automation: Bots that adjust approaches in real time to exploit vulnerabilities.
- Enhanced social engineering: AI analyzing behavior patterns to create highly convincing approaches.
According to a report by CyberArk, 82% of financial scams in 2024 involved deepfakes or AI-driven phishing. In addition, AI-based cyber attacks have grown by 60% in the last year, according to the Darktrace Cybersecurity Report.
This scenario requires companies and users to be alert to new threats, understanding how these attacks work and what the real risks are.
How cybercriminals are using AI to create hyper-personalized attacks
The use of Artificial Intelligence in cybercrime has allowed attacks to be more sophisticated and difficult to detect. Previously, digital fraud such as phishing and social engineering followed more predictable patterns, but now AI allows attacks to be adaptable, personalized and much more effective.
Instead of sending massive generic emails, criminals use AI to collect specific information about their victims, exploiting social networks, leaked data and digital behavior patterns to create highly convincing scams.
Advanced and automated phishing
- E-mails and personalized messages: Algorithms analyze the victim's writing and communication patterns, generating messages that appear legitimate.
- Voice phishing: AI is used to clone real voices, making fraudulent calls more convincing. Europol reports indicate that vishing-based scams grew by 353% in 2024.
- Fraudulent chatbots: AI systems simulate fake attendants to trick customers and steal credentials.
Deepfakes for financial fraud and espionage
- Voice and image manipulation: Scammers create hyper-realistic deepfakes to approve transactions and access restricted systems.
- Fraud in virtual meetings: Cybercriminals use AI to impersonate directors in videoconferences, requesting confidential information.
- Global impact: According to a study by Sensity AI, 78% of the deepfakes detected in 2024 were used for financial fraud.
Attack automation and advanced social engineering
- Autonomous bots: AI scans networks for leaked credentials and security breaches.
- Strategic social engineering: Algorithms analyze behavioral patterns to identify ideal times for an attack, such as meetings or periods of high workflow.
- CEO and boardroom scams: Companies have already reported million-dollar scams in which deepfakes were used to simulate urgent money transfer requests.
These new tactics demonstrate how AI is changing the landscape of cyber attacks, making fraud increasingly personalized and difficult to identify.
Why are companies still not prepared for this type of attack?
Although AI-driven cyber attacks are becoming more sophisticated, many companies still lack effective strategies to protect themselves from these threats. The problem lies not only in the lack of defense tools, but also in the difficulty in recognizing the seriousness of these new criminal tactics.
One of the main challenges is that hyper-personalized attacks are designed to look legitimate, making them extremely difficult to detect. While traditional security methods focus on known threat patterns, scams created by AI are dynamic and adjust their approach in real time, making it difficult for companies to respond.
Lack of awareness and preparation on the part of companies
Lack of adequate training is still one of the factors contributing to this vulnerability. Many organizations still treat phishing and social engineering as common threats, without realizing that these attacks have evolved significantly with the use of AI. According to a report by the Cyber Readiness Institute (2024), 70% of companies do not have training aimed at recognizing AI-generated fraud, which means that many employees are not prepared to identify hyper-personalized scams.
This problem is especially acute in the financial and legal sectors, where quick decisions and high-value transactions are frequent. Companies that deal with sensitive information are prime targets for criminals who use AI to create convincing scams by exploiting employees' lack of technical knowledge.
Deepfakes and advanced manipulations are difficult to detect
Another critical point is the difficulty in identifying deepfakes and other advanced manipulations. Most traditional security tools are not designed to detect audio and video deepfakes, making these attacks even more dangerous. Biometric verification systems have already been fooled by realistic deepfakes, allowing fraudulent access to bank accounts and corporate networks.
In addition, companies that rely on virtual meetings for decision-making can be easy targets for attacks in which cybercriminals use AI to fake identities in video calls. In 2024, one case attracted attention when criminals used a video deepfake to trick employees of a technology company into releasing access to internal data (Source: Sensity AI, 2024).
Threats evolve faster than defenses
The rapid evolution of threats also prevents many companies from being able to react in time. Generative AI models are becoming more accessible, allowing even criminals without advanced technical knowledge to create sophisticated scams with little difficulty.
In addition, many companies still adopt a reactive rather than preventative approach, reinforcing security only after suffering a successful attack. This mentality puts organizations in a vulnerable position, as AI-based attacks tend to be highly effective on the first try.
According to a report by IBM X-Force (2024), 80% of AI-based attacks go undetected by traditional security tools, proving that some of the current solutions are still ineffective against these threats, it is important to reinforce that, for example, cybersecurity companies such as Asper already have solutions that help prevent hyper-personalized AI attacks.
Without adapting quickly to new attack tactics, companies will continue to be vulnerable to increasingly convincing, sophisticated and automated scams. To face this scenario, it is essential that organizations recognize the seriousness of the problem and look for ways to strengthen their security processes before these threats cause irreversible damage.
The future of cybercrime with AI: How to avoid falling victim to these attacks?
The evolution of Artificial Intelligence is not just limited to improving cyber attacks - it can also be used to strengthen digital security. However, many companies are still not prepared to face this new reality.
With criminals exploiting AI to create increasingly convincing scams, the trend is for scams to continue to evolve, requiring companies to rethink their protection strategies. Traditional solutions are no longer enough to mitigate these threats, making it essential to adopt more dynamic and intelligent approaches.
The importance of awareness and the human factor
Although technology is a crucial factor in defending against cyber attacks, human error is still one of the main loopholes exploited by criminals. Advanced phishing and social engineering models continue to trick employees and executives, showing that training and internal awareness are key to reducing risks.
Many companies still don't implement ongoing digital security training programs, leaving their teams vulnerable to hyper-personalized attacks. Creating phishing simulations, regular training and stricter identity validation policies can help mitigate these risks, making employees the first line of defense against AI-based threats.
New technological approaches against AI-driven attacks
In addition to awareness, technological solutions need to evolve to keep up with the sophistication of cyber attacks. Some trends that should gain momentum in the coming years include:
- Advanced behavioral analysis → Monitoring user behavior patterns to identify suspicious activity before an attack takes place.
- Real-time deepfake detection → Specialized voice and video analysis tools to prevent AI-based fraud.
- Enhanced multi-factor authentication (MFA) → Security measures that go beyond traditional passwords and verification codes, making it more difficult to gain unauthorized access.
Although no solution is foolproof, the combination of technology and good security practices can significantly reduce the impact of these new threats.
Preventive strategy: act before an attack happens
Many companies still adopt a reactive stance, strengthening their security only after suffering an incident. However, in the face of the growing sophistication of AI-based attacks, prevention has become a critical factor in avoiding financial losses and reputational damage.
Implementing proactive strategies, such as continuous monitoring, frequent intrusion tests and constant updates to security protocols, can help companies identify vulnerabilities before criminals exploit them. This defense model, combined with threat intelligence, makes it possible to anticipate attacks and minimize their impact.
The road to a safer future
Artificial Intelligence has brought significant advances to cybersecurity, but it has also increased the challenges faced by companies. To protect themselves against hyper-personalized attacks, organizations need to adopt a balanced approach between technology, processes and human training.
With the continuous evolution of threats, the question that remains is: is your company prepared for this new digital security scenario?
The new reality of cybersecurity in the age of AI
Advances in Artificial Intelligence are irreversibly transforming cybersecurity. While AI has brought innovations that optimize digital protection, it has also been exploited by criminals to create attacks that are increasingly sophisticated and difficult to detect. AI's ability to personalize fraud, automate attacks and manipulate digital information is challenging companies to re-evaluate their security posture.
More than ever, just having basic protection tools is no longer enough. The new reality demands a more intelligent and integrated approach, involving continuous monitoring, proactive strategies and an organizational culture focused on digital security. After all, threats are no longer generic , they are adaptable, persistent and targeted.
Protecting against hyper-personalized attacks requires a combination of advanced technology, threat analysis and internal awareness. Companies that adopt robust strategies and stay one step ahead of these new threats not only avoid financial losses, but also strengthen their digital resilience.
Faced with this ever-changing scenario, the question remains: is your company prepared to deal with this new level of threat? If digital security is already a priority for your business, it's worth exploring how experts and specialized solutions can contribute to more strategic and efficient protection.
Here on the Asper blog, you'll find weekly content that also explores a little about how Asper has been working and bringing these technologies and solutions to help companies in various segments mitigate these types of threats.
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