By Mackenzie Gryder
Welcome to Gate 15’s blog series “Riding the Tiger: Artificial Intelligence (AI) Threats and Opportunities”, highlighting essential AI security considerations for organizational leaders and security professionals. Every week, we’ll be sharing insights, best practices, and actionable strategies to help your organization responsibly leverage AI while safeguarding data, operations, and reputation. Each post in the series will examine a different aspect of AI adoption, threat mitigation, and resilience, while providing actionable insights to help organizations navigate evolving AI risks and harness the technology effectively.
Theoretical vs. Actionable AI Risk
As organizations deepen their reliance on AI across operations, customer engagement, and security functions, the ability to distinguish realistic risks from exaggerated narrative has become essential. Headlines often focus on dramatic hypotheticals, rogue AI agents, runaway autonomy, or machines making catastrophic decisions. These scenarios capture public imagination, but they overshadow the far more immediate and operationally relevant threats organizations face today.
In 2026, the real AI threat landscape is shaped by vulnerabilities already present in enterprise environments. The discussion below examines three areas: how cybercriminals are operationalizing AI to scale fraud and intrusion, how state actors are using AI to support influence and misinformation campaigns, and how organizations introduce new internal vulnerabilities when AI tools are integrated into everyday workflows.
Understanding the difference between theoretical risks and active, observable threats allows leaders to prioritize resources, safeguard sensitive information, and maintain trust with customers and stakeholders. Organizations that thrive will be those that embrace AI innovation while building resilience against misuse.
AI-Enabled Criminal Activity
Criminal groups are leveraging AI to lower technical barriers, increase operational efficiency, and improve deception quality.
The 2024 ThreatLabz Ransomware Report from Zscaler highlights how ransomware groups are increasingly pairing traditional intrusion techniques with AI-enhanced phishing. Generative AI allows attackers to craft highly personalized emails that replicate internal tone, branding, and context at scale. This lowers the skill barrier for sophisticated social engineering while increasing speed and success rates. Rather than replacing ransomware tactics, AI accelerates and refines them.
Similarly, reporting from CNN detailed a case in which a finance employee in Hong Kong transferred $25 million after participating in a video call with a convincing deepfake version of their chief financial officer. The attackers used synthetic video and audio to simulate the executive’s presence during a live call, bypassing traditional red flags such as awkward phrasing or email-only communication. This incident underscores that deepfake-enabled fraud is no longer hypothetical; it is operational and financially impactful.
Across the criminal ecosystem, AI is now commonly used to:
- Generate phishing lures tailored to specific industries or individuals
- Clone executive voices for vishing (voice phishing) campaigns
- Automate malware code generation and refinement
- Rapidly localize scams across multiple languages
- Enhance reconnaissance using AI-powered data aggregation
State Actors, AI, and Information Operations
Beyond financially motivated crime, state actors are increasingly integrating AI into cyber and influence operations. The nexus between AI and misinformation is particularly significant.
AI-generated synthetic media, including deepfake video, cloned audio, and fabricated imagery, has lowered the cost and technical skill required to produce convincing propaganda. Generative AI can produce large volumes of persuasive content aligned with specific narratives, tailored to cultural or regional audiences, and deployed across social media at scale.
These capabilities enable:
- Rapid production of disinformation during geopolitical crises
- Fabricated statements from political or corporate leaders
- Manipulated video evidence designed to erode public trust
- Automated social media amplification through AI-generated personas
Unlike traditional propaganda, AI-enhanced influence campaigns can be dynamic and adaptive, adjusting narratives in real time based on audience reaction and engagement data.
Organizational Risk: AI Inside the Enterprise
While AI is often discussed as defensive capability, introducing AI tools into enterprise environments creates its own risk surface. In many cases, the threat is not external actors using AI, but the vulnerabilities organizations introduce by adopting it without governance controls.
Key risk areas include:
- Data Exposure and Leakage: Employees may input sensitive proprietary, financial, or personal data into public AI tools without understanding how that data is stored, retained, or used for model training. This creates potential confidentiality and compliance risks.
- Inside Threat Amplification: AI tools can enable malicious or negligent insiders to scale harm more efficiently through automating document exfiltration, generating convincing pretexts, or drafting fraudulent communications with minimal effort.
- Model Manipulation and Prompt Injection: AI systems integrated into workflows may be vulnerable to adversarial inputs, prompt injection attacks, or manipulated training data, potentially leading to compromised outputs or decision-making errors.
- Overreliance and Automation Bias: Organizations may place undue trust in AI-generated outputs, leading to flawed risks assessments, inaccurate reporting, or insufficient human oversight.
- Expanded Attack Surface: Integrating AI platforms into enterprise systems introduces new APIs, data flows, third-party dependencies, and authentication pathways, all of which increase complexity and potential vulnerability.
- Supply Chain Risks: Vendors and third-party service providers adopting AI technologies may introduce inherited vulnerabilities including insecure model integrations, exposed APIs, poisoned training data, or weak access controls, meaning an organization can be compromised indirectly through a trusted partner using AI with inadequate security safeguards.
Conclusion
As we continue into 2026, the most pressing AI risks are not distant, speculative scenarios, but instead are the operational threats already unfolding across enterprise environment. Organizations don’t need to prepare for science-fiction outcomes; they need to strengthen defenses against data manipulation, model exploitation, deepfake-enabled fraud, and AI-accelerated social engineering. By focusing on the threats that matter today, leaders can make smarter investments, protect critical assets, and maintain the trust of customers and stakeholders. AI will continue to transform how organizations operate, but that transformation must be paired with intentional governance, security-minded deployment, and a commitment to resilience.
Building upon this threat overview, please look forward to our next blog post in this series, as Gate 15 begins to dive into specific AI threat-related topics and insights into how to address these threats before they affect your organization!
Gate 15 works across Critical Infrastructure sectors to help organizations protect their people, places, data, and dollars. The threat environment is constantly shifting, and we are here to boost your resilience with plans, exercises, threat analysis, and operational support against both emerging and enduring threats. Contact our team at Gate15@gate15.global to see how we can assist you in delivering on your mission. Join Gate 15’s Resilience and Intelligence Portal (the GRIP)! Sign up today to stay informed of what’s new in all-hazards homeland security and join us in securing America’s people, places, data, and dollars.
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