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PwC’s 2027 Global Digital Trust Insights survey of roughly 4,000 business and technology leaders across 71 countries found that 52% identify adversarial AI attacks as their largest cybersecurity preparedness gap. Organizations cited fragmented accountability, immature data controls, and shortages of AI-governance expertise as major obstacles to securely deploying AI, particularly autonomous or agentic systems that can create new enterprise entry points.
Responsibility for AI risk remains divided: 29% assigned it to CIOs or CTOs, 26% to dedicated AI leaders, and 17% to CISOs or cybersecurity teams, while 11% reported unclear or shared ownership. Although 90% reported governance foundations such as board oversight and executive accountability, only 47% make cybersecurity a standing board agenda item. Organizations are increasing spending on AI governance, platform hardening, supply-chain security, and AI-enabled detection; RSA recommends managing each AI agent as an identity under zero-trust, MFA, centralized registration, regular assessment, explicit human ownership for high-risk actions, and decommissioning controls.
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PwC published its 2027 Global Digital Trust Insights report, based on a survey of 3,934 business and technology leaders in 71 countries. The report found that 52% of respondents viewed adversarial AI attacks as their largest cybersecurity preparedness gap and identified fragmented accountability for AI risk management.
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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.
Jul 12, 2026
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.
Sep 22, 2026
A global shift is underway as artificial intelligence becomes the top investment priority for cybersecurity among organizations, according to a recent PwC survey of nearly 4,000 business and technology executives. Sixty percent of respondents indicated that AI technologies are their primary focus for cybersecurity spending in the coming year, with key use cases including threat hunting, AI agents, event detection, and behavioral analysis. This surge in AI adoption is driven in part by ongoing skills shortages, with over half of organizations prioritizing AI and machine learning tools to close capability gaps. Additionally, 38% of companies are turning to managed service providers to access the necessary AI expertise. However, the rapid integration of AI into enterprise environments is not without significant risks. New research from LayerX reveals that AI has already become the leading uncontrolled channel for corporate data exfiltration, surpassing traditional risks like shadow SaaS and unmanaged file sharing. The report highlights that 45% of enterprise employees use generative AI tools, such as ChatGPT, Claude, and Copilot, with AI accounting for 11% of all enterprise application activity. Alarmingly, 67% of AI usage occurs through unmanaged personal accounts, leaving security teams with little visibility or control over sensitive data flows. The research found that 40% of files uploaded to generative AI platforms contain personally identifiable information (PII) or payment card information (PCI), and a significant portion of these uploads are conducted via personal accounts. Traditional data loss prevention (DLP) tools are often ineffective in this context, as they are not designed to monitor or control the new channels introduced by AI tools. Experts warn that the lack of governance and oversight around AI usage in enterprises creates substantial risks, including the potential for AI agents to access sensitive data beyond their intended scope if not properly managed. The PwC survey also notes that organizations are balancing investments between proactive technologies, such as monitoring and testing, and reactive measures like incident response and recovery. As AI becomes more deeply embedded in cybersecurity operations, the need for robust governance, least-privilege access for AI agents, and updated security controls is increasingly urgent. The evolving geopolitical landscape further complicates the risk environment, making it critical for organizations to understand both the opportunities and threats posed by AI in cybersecurity. The convergence of rapid AI adoption and insufficient controls underscores the importance of immediate action to secure enterprise data and workflows against emerging AI-driven threats.
Jun 29, 2026