In 2026, artificial intelligence could cease to be a tool and instead become an engine that performs critical tasks without human intervention, according to predictions by experts cited in specialized reports. This year would mark a transition toward autonomous systems that operate with greater speed and scale, generating challenges for security and digital trust.

The key fact is that, with the anticipated arrival of Web 4.0, the interaction between humans, AI, and connected devices could become more intuitive and predictive, enabling hyper-personalized interactions and a closer fusion between physical and virtual environments. This technological framework promises more efficient processes across various areas, from logistics management to health and urban network administration, but it also broadens the attack surfaces for cybercriminals.

Predictions also indicate a rise in malicious activity driven by AI, including the possibility of attacks operating autonomously. Experts warn of an “industry” of automated cybercrime and emphasize the need to establish safeguards and traceability for decisions made by AI agents, with a particular focus on data integrity and identity verification in corporate environments.

In the realm of digital identity, risks from deepfakes and impersonation of executives emerge as vectors for fraud and privileged access. These alerts come from cybersecurity firms forecasting that the convergence of advanced AI, operational autopilot, and next-generation networks will require AI-based defense strategies and real-time execution controls to thwart machine-speed attacks.

The European, Latin American, and global context has reinforced these observations: firms like Palo Alto Networks have highlighted the need for intelligent defenses to counter malicious autonomous agents, while others warn of an increase in attacks targeting sensitive sectors such as finance, health, energy, and public administration. Furthermore, the public conversation emphasizes the importance of advancing toward post-quantum cryptography as a proactive measure against emerging information security challenges.

With these trends in mind, the article proposes an analytical perspective: why is this moment crucial for security and trust? Who might be most affected by the autonomy of AI and Web 4.0? What structural measures could mitigate risks without hindering innovation? The answer lies in establishing AI governance frameworks, execution controls, and coordination between public and private sectors to proactively manage risks.

In conclusion, 2026 could consolidate an economy driven by autonomous AI and a more integrated Web 4.0, but this scenario demands investments in technological defenses, trust standards, and data surveillance to prevent efficiency from being undermined by systemic vulnerabilities. The path toward responsible adoption involves understanding emerging threats, preparing for them, and channeling innovation toward sustainable social and economic benefits.