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ISACA's 2026 State of Cyber report found that organizations are deploying AI security capabilities faster than they are preparing to handle AI-related incidents. Seventy-one percent have not conducted an AI incident-response exercise, and only 3% have mature formal runbooks for AI-specific incidents. The report highlights risks including sensitive-data exposure, AI-enabled phishing and fraud, scaled social engineering, and employee or insider misuse of generative AI.
European security teams are also facing a growing operational burden: 38% of surveyed IT and cyber professionals said their organizations had already sustained more attacks this year than during all of 2025, while 54% expect a material attack within the next 12 months. Social engineering remains the most common threat, with AI helping attackers automate and refine targeting; defenders are using AI for detection, response, endpoint protection, and task automation, but persistent understaffing, underfunding, skills gaps, and burnout are limiting resilience.
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An April 2026 ISSA survey found that nearly seven in ten cybersecurity workers believed their jobs had become more difficult over the preceding two years. Nearly half were considering leaving their jobs, with stress and poor work-life balance cited as major factors.
ISACA published its 2026 State of Cyber report, finding that AI adoption in security outpaced preparedness for AI-related incidents: 71% of organizations had not conducted AI incident-response exercises and only 3% had mature AI-specific incident runbooks. The report also documented rising attack volumes, AI-supported social engineering, and widespread understaffing, underfunding, skills gaps, and workforce stress among surveyed European cybersecurity professionals.
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Organizations are rapidly increasing their adoption of artificial intelligence (AI) technologies, but security measures are failing to keep pace, resulting in a widening exposure gap. Surveys from Red Canary and Tenable highlight that while security budgets and tool sophistication have grown, incident response times are slowing, and the attack surface is expanding—particularly as AI becomes embedded in business operations. Key targets remain email, identity, and endpoints, with a significant portion of organizations experiencing incidents in these areas. Despite efforts to consolidate security tools, most teams report longer detection-to-resolution times, and the business impact includes substantial financial losses, data breaches, and service disruptions. The rush to integrate AI has outstripped the ability to secure it, with most organizations adopting AI faster than they can implement effective protections. While many are aligning with frameworks like the EU AI Act and NIST AI RMF, few are translating these into practical controls such as data encryption, system testing, or robust identity management for AI systems. As AI pipelines and connections proliferate across productivity apps, browsers, and cloud services, new attack vectors emerge, leaving critical systems and data increasingly vulnerable. Proactive defense and continuous visibility are recommended to close the gap between AI innovation and enterprise security readiness.
Jul 12, 2026
European IT and cybersecurity professionals are increasingly concerned about the rise of AI-driven cyber threats, with 51% expecting such threats and deepfakes to be a major worry in 2026. Many organizations admit they are not adequately prepared to manage the risks associated with generative AI, and few feel confident in their ability to secure these technologies. The majority of professionals identify AI-driven social engineering as the most significant cyber threat, with 59% highlighting it as a top concern. Insider threats, both intentional and accidental, are also seen as a growing risk in the context of AI adoption. Despite the transformative potential of AI, most organizations lack comprehensive hiring plans for digital trust roles such as audit, risk, and cybersecurity, which are essential for building resilience. Business continuity and resilience are prioritized, but there is a clear gap in staff training for both responsible AI use and response to AI-related threats. The rapid pace of AI development has outstripped the ability of many companies to update or establish effective AI governance policies. Only 36% of boards have adopted an AI governance framework, and even fewer have integrated AI oversight into their corporate strategies or board committee charters. Experts emphasize the urgent need for organizations to create or update AI governance and usage guidelines, especially if existing policies are more than a year old. The lack of robust data governance and a single source of truth is cited as a major barrier to successful AI implementation, with data security and governance being prerequisites for leveraging AI effectively. Despite significant investments in AI, only 5% of surveyed companies have achieved visible value across their organizations, and 60% have not realized substantial returns or cost savings. The thin line between using AI for defensive and offensive purposes is highlighted, as tools designed for security can be repurposed for attacks with minimal changes. Threat actors are leveraging AI to develop exploits faster than defenders can patch vulnerabilities, and AI-assisted attacks are becoming more prevalent. The need for up-to-date guidelines, staff training, and a strong governance framework is underscored as essential for mitigating the risks posed by AI-driven cyber threats. Organizations are urged to address these gaps proactively to ensure both the security and the business value of their AI initiatives.
Jul 12, 2026
Enterprises’ rapid deployment of **AI and agentic AI** is increasingly creating measurable security and business risk, including direct exposure of sensitive personal data and downstream impacts on risk transfer. A widely cited example involved McDonald’s *McHire* applicant-screening platform (built by *Paradox.ai*), where researchers reported a trivial backend credential weakness (`123456` as both username and password) and no MFA, potentially exposing data tied to roughly **64 million** applicants; the incident is being used by insurers and risk teams as evidence that AI adoption is moving faster than security and governance, contributing to tighter cyber-insurance language, higher premiums, and **AI-related exclusions**. Separate reporting also highlighted that “plug-and-play” AI is unrealistic at enterprise scale, with organizations increasingly needing custom integration and operational ownership rather than relying on off-the-shelf tools. Threat reporting during the same period reinforced that AI is expanding both attacker capability and the attack surface: researchers described **Pakistan-linked APT36** using AI coding tools to generate high volumes of low-quality malware variants (including in less common languages) and to leverage legitimate cloud services for command-and-control, complicating detection. Additional research flagged **AI-themed browser extensions** (Chrome/Edge) that impersonate legitimate tools and can harvest LLM chat histories and browsing activity, underscoring the risk of “shadow AI” and unvetted add-ons. In parallel, routine threat-intelligence summaries continued to track major incidents (e.g., ransomware and data breaches) alongside AI-enabled tactics, indicating that AI risk is becoming intertwined with broader enterprise security exposure rather than remaining a standalone technology concern.
Jun 29, 2026