It may already be too late to control AI, warns new report

The Washington Post published an article today, originally penned by Gleb Tsipursky for The Hill, which raises a stark warning about the accelerating pace of artificial intelligence development and the lagging ability to control its potential negative consequences. The piece draws heavily on findings from the "International AI Safety Report 2026," which details how the continuous gains in AI capabilities are inadvertently creating a wider array of pathways for harm. Simultaneously, the report observes a concerning delay in understanding and responding to the real-world misuse of these advanced systems. The article underscores that the traditional methods for managing AI-related risks are proving inadequate in the face of such rapid technological evolution. It points out that organizations treating AI risk merely as a policy matter are likely to incur significant costs later, manifesting as increased fraud losses, more frequent security incidents, damage to brand reputation, and unexpected regulatory challenges. In contrast, the report suggests that organizations adopting AI risk as a core operational discipline will be better positioned to build resilience, effectively navigating the complex landscape of emerging threats. Key concerns highlighted include the proliferation of AI-generated content, which is leading to a sustained climb in incidents tracked by the AI Incidents Monitor. This trend translates into heightened brand exposure to issues like impersonation, fraud, harassment, and the malicious use of synthetic media against both employees and customers. The article specifically notes that deepfakes, once considered a novelty, have now become an infrastructural component of various harmful activities. Furthermore, the report addresses the growing cyber risks associated with AI autonomy. It presents stronger evidence of AI being actively used in real cyber operations and points to rapid performance gains in cyber benchmarks. This dual signal indicates that while AI can enhance defenders' speed, it also significantly boosts attackers' scale. A security program that solely focuses on AI as a defensive aid risks overlooking the competitive reality that adversaries are also automating reconnaissance, social engineering, and exploit development. Even as model providers improve baseline defenses, attackers continually probe for vulnerabilities. The author concludes by emphasizing that the compounding second-order effects of AI's capability progress are already evident. Deepfakes erode trust, autonomous agents pose security risks, open-weight models challenge containment, and uneven adoption strains competitiveness. The article serves as a critical call to action for leaders to shift their approach to AI safety from reactive policy-making to proactive operational resilience, acknowledging that the window for effective control may be rapidly closing.