Artificial intelligence has become the defining technology of our era. Most leaders aren’t questioning whether to adopt AI or not — they are pondering the scope and pace of implementation.
But with AI comes new risks. The same technologies driving innovation are being weaponized by cybercriminals, fraudsters, and nation-state actors. This creates a dual challenge for security leaders: secure the use of AI internally and protect against an onslaught of AI-powered attacks.
The Growing Threat Landscape
While organizations carefully navigate their AI journey, malicious actors have already embraced the technology's destructive potential. Recent incidents reveal the sobering scope of AI-enabled threats.
In one operation, cybercriminals deployed AI coding assistants to orchestrate a massive data extortion campaign. Rather than relying on human operators, they automated reconnaissance, credential harvesting, and data exfiltration decisions. Even their ransom demands were AI-generated, crafted with psychological precision designed to maximize compliance rates. Known as “vibe hacking”, this approach allows cybercriminals to scale operations like never before.
Nation-state actors have proven equally innovative. North Korean operatives successfully used AI to fabricate convincing résumés, excel in technical interviews, and perform legitimate job functions after being hired by Western companies. This elaborate deception allowed them to funnel resources to sanctioned regimes while maintaining deep cover within target organizations.
Perhaps most alarming is the evolution of deepfake technology into a precision fraud instrument. In a landmark case from January 2024, fraudsters convinced an Arup engineering firm employee to transfer $25.5 million during a video call featuring AI-generated replicas of the company's senior leadership team. This wasn't an isolated incident. Deepfake fraud across North America has exploded by over 1,700% since 2022, with first-quarter 2025 losses exceeding $200 million dollars.[MN1] [BH2]
These cases represent more than individual security failures; they signal a fundamental shift in the threat landscape. AI is democratizing sophisticated attacks, enabling low-skilled actors to execute operations that previously required expert teams and substantial resources.
Securing AI Inside the Enterprise
Addressing AI risk requires a multi-layered approach, beginning with policy and awareness. Security leaders must establish clear guidelines for the use of AI tools, so employees understand what is acceptable and what isn’t. Employees must be trained on their responsibilities under the new policy, as well as on how to spot AI-enabled threats such as deepfake calls or AI-generated phishing.
Leaders should monitor regulations and consider using governance frameworks and standards as a backbone for AI security. The NIST AI Risk Management Framework and OWASP GenAI Security Project are two that offer guidance for identifying and mitigating AI-specific risks. While regulations are evolving, the EU AI Act is one that is establishing transparency and risk-based controls for AI applications that could become global benchmarks.
Privacy-enhancing technologies (PETs), incorporating data minimization techniques like de-identification and aggregation to protect individual privacy, should be used. These technologies work alongside established cybersecurity frameworks to address specific AI threats including data poisoning and unauthorized model extraction.
Real-time monitoring systems should be used for continuous oversight of AI operations to detect deviations from expected behavior. These should be integrated with existing cybersecurity frameworks to protect against both traditional software vulnerabilities and AI-specific attack vectors.
To protect against the loss of sensitive information, a secure data platform that encrypts data at rest and in flight is non-negotiable for AI systems. To prevent unauthorized access, identity-based control systems should be used to maintain confidentiality, integrity, and availability of AI systems and their training data while ensuring legitimate users can perform necessary functions. With effective governance, visibility and control, encryption and structured monitoring and management, mission critical data can be secured and organizations can keep their most critical assets safe.
Organizations developing internal AI applications must embed security considerations from initial conception through deployment. This means implementing comprehensive data protection measures, following secure development practices, and establishing regular vulnerability testing protocols. It also requires rigorous vendor assessment processes to ensure third-party AI tools meet security standards before integration into critical business systems.
Finally, human oversight mechanisms should be used to establish clear boundaries between automated decision-making and human intervention. These are particularly critical in high-stake scenarios where AI systems may operate beyond their training parameters.
Charting Your Path
Today's organizations exist across a broad AI maturity spectrum. Some remain "AI-curious," experimenting with proof-of-concept projects to understand the technology's potential. Others have graduated to developing comprehensive AI use cases and governance frameworks. Only a few industry leaders are operating sophisticated AI systems at enterprise scale.
Regardless of where you are on this continuum, AI security is critical. Without proper guardrails, AI can lead to serious risk exposure, and one mistake could lead to big problems.
ePlus has developed a comprehensive service portfolio designed to support organizations throughout their AI journey. For organizations just starting out, we offer AI envisioning workshops and readiness assessments that establish clear plans and roadmaps from the outset. Our copilot readiness assessment ensures Microsoft AI tools are deployed with appropriate security controls and governance frameworks.
Organizations that want to simplify AI infrastructure deployments can leverage our AI Experience Center, a hands-on environment where users can explore and evaluate a variety of AI infrastructure solutions and walk through automation, management, and monitoring of AI workflows.
By aligning people, processes, and technology within a coherent security framework, these services provide organizations with a proven pathway from "AI-curious" to “AI-mature” without compromising their security posture.
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For more information on how to secure your AI systems, contact us to start a conversation with one of our AI experts.