Many of us remember the awe of first encountering AI through Siri, Alexa, or Google Assistant. We were captivated by its potential. However, that same technology now poses a significant risk: AI has become the most effective tool for threat actors orchestrating sophisticated attacks against our infrastructure and data.
The most severe cyber threats AI is making more profitable are ransomware attacks, which can paralyze an organization's ability to operate, on top of the financial burden. No organization with a device connected to the Internet is immune from being targeted. For instance, the Springfield, MA school district canceled the first week of classes this month after threat actors infiltrated its IT network, blocking access to vital software and severely hampering school operations. At the University of Texas at San Antonio, the start of classes was delayed and locked 42,000 students and faculty out of the university’s networks.
However, AI is also being deployed in software used to defend, monitor, and report threats to IT teams, Security Operations Centers (SOCs), and even the productivity tools we use daily—but this comes with significant costs. This is creating a structural gap between large enterprises with robust budgets and cyber response teams, and small to medium businesses (SMBs) who lack the financial or human resources to dedicate to cybersecurity. According to the 2026 Verizon Data Breach Investigations Report, there is a disproportionate impact from ransomware: 88% of all SMB breaches involve ransomware, compared to just 39% for enterprises.
Ransomware is rarely launched in isolation. To maximize impact, threat actors often employ a "softening" phase, targeting an organization’s cyber posture before deploying the final ransomware payload. Adopting classic military strategies, attackers frequently conduct a form of cyber-bombardment utilizing two prominent AI-driven tactics:
- AI-Generated Content Spam ("AI Slop"): As described by Adam Nemeroff of Quinnipiac University, this refers to low-to-mid-quality content generated by AI tools with little regard for accuracy (The Conversation, 2025). Cybercriminals weaponize this "slop" across multiple vectors, including mass phishing campaigns and slopsquatting (the creation of deceptive domains using AI-generated text to mimic legitimate sites).
- Autonomous Rogue AI Agents: To understand this risk, one must first define an AI agent: a system that autonomously executes tasks by designing workflows with available tools (IBM, 2026). Stuart Russell, Professor of Computer Science at UC Berkeley, warns that agents become "rogue" when they execute actions outside their programmed directives, often due to goal misalignment. In a cyber attack, such agents could autonomously scan for vulnerabilities, escalate privileges, or deploy payloads without human intervention.
Ransomware, AI slop, and rogue AI agents have converged to create an unprecedented era of cyber threats. Early ransomware was transactional: encrypt data, demand payment, return data. But AI-backed attacks have shifted the model to extortion. Data-extortion-only attacks skyrocketed from 2% to 22% between 2024 and 2025 (The HIPAA Journal, Feb 2026), turning SMBs into low-hanging fruit due to gaps in their security posture.
Over the next seven weeks, StrongKey is releasing a series on these converging threats and exactly how you can protect your organization's data.
