Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In the constantly evolving world of cybersecurity, defense teams need all the resources they can get to keep up. Fortunately, the massive advances in generative AI present SOC teams with a powerful set of tools to optimize security practices and match even fully automated adversaries using natural language input. Microsoft Security Copilot is among the most advanced examples of these tools.

AI systems are quickly becoming critical elements of business technology. Imagine building an AI agent trained using your internal documents and guides to quickly improve customer experience, process loan applications, or provide tier 1 support to your customers. The potential is tremendous—but what happens if your models are trained using your own intellectual property like software code, customer data, or other sensitive information?

Imagine receiving an urgent email from your bank that looks perfectly legitimate. It warns you of a suspicious transaction and prompts you to verify your identity. You hesitate but click, and suddenly, your credentials are compromised. This scenario, crafted by AI-powered fraud-as-a-service, is happening now.

The rush to work faster with artificial intelligence (AI) risks encouraging employees to accidentally put sensitive data at risk. Take this scenario: someone in the procurement team has a tight deadline, so they upload a confidential contract into an AI tool to review a few redlines. It’s unclear if the AI system is storing the data from the contract, how long it’ll be retained, and if the data will resurface in a future prompt to someone else.

The EU AI Act is one of the world’s first comprehensive regulations aimed at AI-based systems. While we had voluntary standards like ISO 42001, the Act introduced mandatory requirements that in-scope organizations must meet to avoid considerable fines and operational disruptions. ‍ If you develop, use, or distribute AI systems, you may have to meet the obligations prescribed by this directive. Our EU AI Act summary will help you do so by covering: ‍

In the past year alone, the number of artificial intelligence (AI) packages running in workloads grew by almost 500%. Which is to say: AI is everywhere, and it’s settling in for the long haul. Naturally, as helpful as they are, these AI workloads come with security challenges, including data exposure, adversarial attacks, and model manipulation. So as AI adoption accelerates, security leaders must build an AI workload security program to protect their organizations while enabling innovation.