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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.
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Help Net Security published coverage on organizations trying to adopt AI while avoiding the associated cybersecurity consequences, highlighting concern over AI-driven cyber threats.
SecuritySenses published a video discussing the risk that AI could be easily repurposed for malicious cyber activity, framing concerns around offensive use of generative AI in infosec.
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Enterprises are rapidly integrating artificial intelligence (AI) into their core operations, leading to a significant increase in both the scale and complexity of cybersecurity risks. Autonomous AI agents, once limited to providing suggestions, now act independently within enterprise systems, accessing sensitive data, executing transactions, and triggering downstream workflows without human oversight. These agents, often deployed by individual teams or embedded in third-party software, can inadvertently ingest confidential information, such as customer credit card data, even if the data is only briefly accessible. Unlike human users, AI agents lack contextual understanding and ethical judgment, acting continuously and at scale, which introduces a new category of 'Shadow AI' risk. Multimodal AI systems, which process multiple input streams to generate more human-like outputs, further expand the attack surface. Adversaries can exploit these systems by manipulating data inputs, such as subtly altering images or text, to deceive the AI and bypass security controls. Research has demonstrated that these attacks are not merely theoretical; adversarial manipulations can evade detection and cause significant harm, especially in critical sectors like defense, healthcare, and finance. Organizations are increasingly aware of the dangers posed by AI-augmented threats, including deepfakes and AI-driven social engineering, but many lag in implementing effective technical defenses. Surveys indicate that while a majority of firms have experienced deepfake or AI-voice fraud attempts, more than half have suffered financial losses as a result. Despite this, investment in detection and mitigation technologies remains inadequate, and many companies overestimate their preparedness. The surge in AI adoption is reflected in corporate disclosures, with over 70% of S&P 500 firms now reporting AI as a material risk, up from just 12% two years prior. Reputational and cybersecurity risks are the most frequently cited concerns, followed by legal and regulatory challenges as governments move to establish AI-specific compliance requirements. However, only a minority of corporate boards have formally integrated AI oversight into their governance structures, highlighting a gap between risk awareness and actionable governance. The lack of comprehensive frameworks for managing AI risk leaves organizations vulnerable to both technical and compliance failures. As AI becomes more deeply embedded in business processes, the need for robust governance, continuous education, and responsible-use frameworks becomes increasingly urgent. Security and governance leaders must adapt to this new frontier by developing strategies that address the unique risks posed by autonomous and multimodal AI systems. Failure to do so could result in significant financial, operational, and reputational damage as adversaries continue to exploit the evolving AI landscape.
Jun 29, 2026
Cybersecurity leaders are facing a rapidly evolving threat landscape shaped by the integration of artificial intelligence (AI) into both attack and defense strategies. According to a report from VikingCloud, 71% of surveyed security leaders have observed an increase in the frequency of cyberattacks over the past year, with 61% noting that the impact of these incidents has also grown. Nation-state actors are increasingly targeting a broader range of industries, including retail, healthcare, and hospitality, often leveraging AI to scale their operations and exploit third-party software vulnerabilities. The use of generative and agentic AI by attackers has enabled more sophisticated phishing, social engineering, and ransomware campaigns, with deepfakes and voice-based fraud becoming more prevalent. Security leaders report that AI is now commonly used to automate the creation of polished, linguistically sophisticated phishing emails, making them harder to detect and more convincing to recipients. Attackers are also targeting AI assistants embedded in workplace tools, using malicious prompts hidden in emails to manipulate these systems into leaking sensitive information or executing unauthorized actions. Research from Columbia University and the University of Chicago, as well as Barracuda Research, has documented how attackers exploit weaknesses in AI-driven security tools and tamper with systems that use retrieval-augmented generation (RAG), leading to unreliable outputs and poor decision-making. Despite these challenges, organizations are increasingly adopting AI to bolster their defenses, automating threat detection, identity management, and patching to free up security teams for more strategic tasks. However, a significant skills gap persists, as highlighted by the AI Workforce Consortium, which found that AI technical skills are now required across 50 job roles in ICT, yet the market lacks enough professionals with these capabilities. The demand for expertise in areas such as LLM architecture, prompt engineering, and generative AI is outpacing supply, putting additional pressure on security teams. Security leaders are also concerned about reduced government oversight, with many citing cuts to agencies like CISA and NSA as factors that have increased organizational vulnerability. The interplay between AI-driven attacks and defenses is creating new security, compliance, and governance challenges that organizations must address to safely deploy advanced AI systems. As both attackers and defenders race to leverage AI, the need for skilled professionals and robust governance frameworks has never been greater. The evolving threat landscape underscores the importance of continuous learning and adaptation for cybersecurity teams. Organizations must remain vigilant against AI-powered threats while investing in workforce development to close the skills gap. The integration of AI into cybersecurity is not only transforming technical requirements but also reshaping risk management and strategic decision-making at the highest levels.
Jun 29, 2026
Artificial intelligence is fundamentally reshaping the cybersecurity landscape, introducing both new opportunities and significant risks for organizations and professionals. The adoption of AI tools is accelerating the learning curve for cybersecurity practitioners, enabling faster skill acquisition, automated reconnaissance, and streamlined exploit generation, as highlighted by experts who advocate for integrating AI into bug hunting and security research workflows. However, this technological leap is also disrupting traditional career paths, with studies showing a marked decline in entry-level cybersecurity and IT jobs as AI automates routine tasks such as help desk support, manual testing, and security monitoring. Industry leaders emphasize the need for IT teams to adapt by acquiring new skillsets and focusing on strategic problem-solving, as the majority of job skills are expected to change dramatically by 2030 due to AI's influence. Concurrently, the rise of autonomous AI agents introduces a new class of security risks, as these systems possess the ability to make independent decisions, access sensitive data, and execute code across networks, often in ways that are opaque and difficult to audit. The lack of robust identity management and oversight for these agentic systems leaves organizations vulnerable to novel attack vectors, including black box attacks where the root cause of malicious or erroneous actions is nearly impossible to trace. Deepfake technology, powered by generative AI, is rapidly becoming a favored tool for social engineering attacks, with a significant increase in organizations reporting incidents involving AI-generated impersonations of executives and employees. This trend is eroding traditional trust mechanisms, such as voice and video verification, and forcing security teams to rethink their authentication strategies. Ethical concerns are also at the forefront, as CISOs and boards are urged to monitor for red flags such as loss of human agency, lack of technical robustness, and data privacy risks associated with AI deployments. Regulatory frameworks and responsible AI governance are becoming essential to ensure that AI systems are deployed safely and ethically, particularly in sectors like financial services where the stakes are high. The convergence of these factors is creating a dynamic environment where cybersecurity professionals must continuously adapt to the evolving threat landscape, leveraging AI for defense while remaining vigilant against its misuse. As organizations rush to deploy AI-driven solutions, the need for comprehensive security strategies, ongoing workforce development, and ethical oversight has never been more critical. The future of cybersecurity will be defined by the ability to harness AI's power responsibly while mitigating its inherent risks, ensuring both operational resilience and trust in digital systems.
Jun 29, 2026