Artificial intelligence is becoming part of everyday enterprise operations faster than almost any technology before it. As adoption accelerates, AI security risks are becoming a growing concern for organizations trying to balance productivity, data protection, and effective governance. Employees are using AI assistants to summarize documents, analyze data, write code, generate reports, and automate routine work, often without waiting for formal approval or governance.

The latest industry research paints a clear picture: AI isn’t creating an entirely new cybersecurity landscape. It’s accelerating existing risks while exposing new gaps in governance, data protection, and visibility.

Here are the statistics every security leader should know.

AI Adoption Is Outpacing Enterprise Governance

Enterprise AI adoption has moved well beyond experimentation.

According to Verizon’s 2026 Data Breach Investigations Report, 45% of employees are now regular users of AI applications on corporate devices, a dramatic increase from just 15% one year earlier. At the same time, 67% of AI users access these services using personal, non-corporate accounts, making governance significantly more difficult.

These numbers highlight one of the biggest challenges facing security teams today. AI adoption is no longer driven exclusively by IT initiatives. Employees are introducing AI into daily workflows on their own, creating a growing gap between technology adoption and organizational oversight.

• 45% of employees regularly use AI applications on work devices.
• AI adoption among enterprise users has tripled in one year.
• 67% access AI services through personal rather than managed enterprise accounts.
• Shadow AI is now among the fastest-growing forms of unsanctioned technology usage inside organizations.

Sensitive Enterprise Data Is Already Flowing Into AI Platforms

One of the most significant security concerns is no longer whether employees use AI, but what information they share with it.

Enterprise DLP telemetry shows users routinely uploading sensitive business information into external AI services. The most common content includes source code, structured business data, research documents, technical documentation, and images. Verizon also found that AI-related DLP events increased fourfold year over year, making Shadow AI the third most common type of non-malicious insider activity observed in enterprise environments.

Unlike traditional insider threats, most of these actions are not malicious. Employees are simply trying to improve productivity. However, every prompt, uploaded document, or copied report has the potential to expose intellectual property, confidential business information, or regulated data outside approved environments.

• AI-related DLP incidents increased 4× year over year.
• Shadow AI ranks as the third most common non-malicious insider activity.
• Source code is the most frequently uploaded sensitive content.
• Research documents, technical documentation, structured data, and images are also commonly shared with AI services.

AI Security Risks Are Extending the Cyber Threat Landscape

The same technology improving employee productivity is also making attackers more efficient.

The Verizon DBIR notes that cybercriminals increasingly use generative AI to accelerate phishing campaigns, vulnerability research, malware development, and social engineering. Rather than inventing entirely new attack methods, AI allows attackers to execute familiar techniques with greater speed, scale, and efficiency.

This trend reinforces an important reality: AI is lowering the barrier to sophisticated cyberattacks while increasing the volume of threats organizations must defend against.

• AI is increasingly used to improve phishing campaigns.
• Threat actors leverage AI for malware development.
• AI accelerates vulnerability discovery and research.
• Social engineering attacks continue to become more convincing through AI-generated content.

Enterprise Visibility Is Becoming Harder to Maintain

AI introduces new blind spots that traditional security tools struggle to monitor.

Verizon found that more than 15% of users within the average organization have unauthorized AI browser extensions installed. Many of these extensions continuously collect browsing context to generate responses, potentially exposing confidential enterprise information without users fully understanding the implications.

Combined with personal AI accounts, browser-based AI assistants, and rapidly expanding AI ecosystems, organizations are losing visibility into where sensitive information is processed, stored, and shared.

• Over 15% of enterprise users have unauthorized AI browser extensions installed.
• AI assistants increasingly collect contextual browsing information.
• Traditional monitoring tools often lack visibility into browser-based AI interactions.

The Broader Threat Landscape Continues to Evolve

AI adoption is only one part of today’s cybersecurity challenge.

The 2026 Verizon Data Breach Investigations Report analyzed more than 31,000 security incidents and over 22,000 confirmed breaches across 145 countries, providing one of the industry’s most comprehensive views of the current threat landscape.

The report highlights several persistent trends:

• Vulnerability exploitation remains the leading initial access vector.
• Ransomware continues to impact organizations of every size.
• Third-party risk continues to grow.
• AI-assisted phishing is increasing the effectiveness of social engineering attacks.

What These Trends Mean for Security Leaders

The latest industry research points to a consistent trend: AI is becoming embedded in everyday enterprise operations faster than governance and security practices are evolving.

Employees are using AI to accelerate productivity, attackers are using AI to improve the efficiency of existing cyberattacks, and organizations are working to establish the policies and controls needed to manage this rapidly expanding technology landscape.

For security leaders, the challenge is not simply adopting AI securely. It is understanding how AI is changing the way sensitive information is created, processed, accessed, and shared across the enterprise.

The organizations that adapt most effectively will be those that continuously reassess their security strategies as AI reshapes both business workflows and the broader threat landscape.