Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Many IT professionals struggle to integrate artificial intelligence (AI) into their existing environments. You often find expensive hardware trapped in isolated clusters or dedicated hosts. Your infrastructure team manages access through manual ticket queues, which leads to low utilization and frustrating bottlenecks for developers. When you don’t have a standardized way to share and monitor accelerator resources, every hardware change risks downtime for your critical applications.

In 2026, software development speed is an AI-solved problem. Yet, as AI-generated code volumes surge, organizations face a new kind of risk visibility gap. Developers are increasingly copying third-party snippets into their codebases—from both AI prompts and open-source software components—creating large security and compliance blind spots that lead to significant risks.

Modern managed service providers (MSPs) are increasingly adopting RMM AI tools — remote monitoring and management software enhanced with artificial intelligence — to keep pace with growing IT demands. Traditional RMM platforms allow MSPs to remotely monitor client endpoints, deploy patches, run scripts and troubleshoot issues from a central console. Now, AI-powered RMM software is taking this a step further.

Your database stores a credit card number: 4532 1234 5678 9010. You encrypt it for security. Now it looks like this: %Xk92@!mQz#Lp&7. Problem. Your payment system can’t process that. It expects a 16-digit number. Your billing software breaks. Your downstream analytics fail. Your whole pipeline comes to a halt. This is the exact problem that format-preserving encryption was built to solve.

AI is transforming the cybersecurity landscape for both threat actors and defenders. Learn how AI is being used on both sides of the battle with practical tips to help your security team up-level its AI use.