IoT security has always presented unique challenges. Hardcoded default credentials and irregular or impossible patching are common problems. A high percentage of IoT traffic travels over networks as unencrypted plain text, leaving it vulnerable to eavesdropping or interception.
AI is transforming IoT security by analyzing massive streams of data to spot threats human operators would miss. However, there remains a huge gap between purchases and execution. Organizations are buying AI-enabled IoT security tools, but they’re deploying them for limited use cases.
With IoT security threats surging, organizations need an effective strategy for leveraging AI without creating operational risks. The right partner can help them bridge the execution gap to bolster IoT security.
Addressing the High Cost of IoT Threats
Because traditional security software requires a lot of processing power, it fails to protect most IoT devices. AI-powered tools take a different approach. Machine learning algorithms quickly learn what “normal” behavior looks like. AI then monitors the data traveling to and from the device so it can spot anomalies. If a smart security camera starts scanning the corporate database, an AI system will detect and flag it automatically.
When an anomaly is detected, AI triggers automated playbooks, cutting response times down from hours to milliseconds. The AI can dynamically rewrite network firewall rules to quarantine an infected device, kill the device’s active internet sessions, and alert administrators without manual intervention.
Best-in-class AI systems provide predictive threat intelligence. By analyzing massive, global datasets of cyberattack patterns, AI tools can identify similarities between unknown threats and IoT behavior. This allows security systems to block zero-day attacks before they can weaponize a fleet of smart devices.
Adoption Is High, But Execution Is Fragmented
Recent cybersecurity data reveals a fascinating paradox: Organizations are purchasing AI security tools faster than they trust them to act independently.
AI cybersecurity adoption jumped from 50 percent to 78 percent in just one year. More than 90 percent of organizations now use AI or consider it a requirement when purchasing cybersecurity tools.
However, the reality on the ground paints a different picture. Companies are buying and deploying AI features in isolated silos. This fragmentation actually worsens the IoT threat because it creates a structural blind spot.
This is particularly true in the industrial and OT sectors, where IoT devices run critical infrastructure such as power grids and manufacturing plants. A State of AI in OT Cybersecurity report found that while 87.7 percent of organizations are piloting or planning to use AI, only about 7.9 percent have deployed it across multiple security functions.
Low Comfort with Agentic AI
Organizations are comfortable using AI for analysis, visibility and “human-in-the-loop” assistance. Roughly a third of industrial firms use AI to continuously monitor IoT traffic patterns and issue alerts when a device behaves strangely. They are also using AI chat assistants to help security analysts troubleshoot vulnerabilities or write firewall rules.
The true frontier is agentic AI, where the system acts autonomously without human intervention. Security teams are hesitant to let AI automatically shut down a device or firewall. If AI falsely flags a device as “malicious,” it could cause millions of dollars in downtime or endanger lives.
According to the AI & Cybersecurity Trends Report, only about 14 percent of organizations have made AI the center of their security strategy. More than 84 percent of industrial firms using AI admit they don’t yet have a policy governing how AI handles data privacy or operational risks.
How Technologent Can Help
The Technologent security team acts as a unifying force that transforms fragmented, siloed AI tools into a cohesive, secure ecosystem. Rather than just selling another software license, Technologent solves the IoT and AI readiness problem through integration, governance and unified architecture.
Technologent also helps organizations define strict rules for when AI can act autonomously. For instance, a playbook might give AI full authority to quarantine a compromised smart thermostat. However, if an industrial IoT sensor or medical device shows anomalies, the playbook routes the alert to a human engineer for verification before shutoff. This protects both physical safety and network integrity.
Because enterprises cannot protect what they cannot see, Technologent deploys advanced, agentless network monitoring solutions to eliminate legacy infrastructure blind spots. AI automatically discovers, inventories and maps every connected smart device, giving the organization greater situational awareness.
Ready to strengthen your IoT security strategy? Contact Technologent to discuss your organization’s needs.
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