{"id":5463,"date":"2025-04-23T08:00:00","date_gmt":"2025-04-23T15:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/microsoft-cloud\/blog\/?p=5463"},"modified":"2026-02-26T16:00:29","modified_gmt":"2026-02-27T00:00:29","slug":"securing-ai-navigating-risks-and-compliance-for-the-future","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/microsoft-cloud\/blog\/2025\/04\/23\/securing-ai-navigating-risks-and-compliance-for-the-future\/","title":{"rendered":"Securing AI: Navigating risks and compliance for the future"},"content":{"rendered":"\n

AI is reshaping industries, revolutionizing workflows, and driving real-time decision-making. Organizations are embracing it at an astonishing pace. In fact, 47% of AI users already trust it to make critical security decisions.1<\/sup> That\u2019s a clear sign that AI is becoming an essential force in business. But here\u2019s the challenge\u2014if not secured properly, AI\u2019s immense potential can become a setback to deploying AI across your organization.  <\/p>\n\n\n\n

As AI becomes more deeply embedded in workflows, having a secure foundation from the start is essential for adapting to new innovations with confidence and ease. New regulations like the European Union AI Act demand greater transparency and accountability, while threats like shadow AI and adversarial attacks highlight the urgent need for robust governance. <\/p>\n\n\n\n

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Getting Started with AI Applications<\/h2>\n\n\n\n

Microsoft Guide for Securing the AI-Powered Enterprise<\/p>\n\n\n\n

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To help organizations navigate these challenges, Microsoft has released the Microsoft Guide for Securing the AI-Powered Enterprise Issue 1: Getting Started with AI Applications<\/a>\u2014the first in a series of deep dives into AI security, compliance, and governance. This guide lays the groundwork for securing the AI tools teams are already exploring and provides guidance on how to manage the risks associated with AI. It also dives into some unique risks with AI agents and how to manage these. Here\u2019s a look at the key themes and takeaways. <\/p>\n\n\n\n

Securing AI applications: Understanding the risks and how to address them <\/span><\/h2>\n\n\n\n

AI adoption is accelerating, bringing remarkable opportunities but also a growing set of security risks. As AI becomes more embedded in business decision-making, challenges such as data leakage, emerging cyber threats, and evolving and new regulations demand immediate attention. Let\u2019s explore the top risks and how organizations can address them. <\/p>\n\n\n\n

Data leakage and oversharing: Keeping AI from becoming a liability <\/h3>\n\n\n\n

AI thrives on data. But without guardrails, that dependence can introduce security challenges. One major concern is shadow AI\u2014when employees use unapproved AI tools without oversight. It\u2019s easy to see why this happens: teams eager to boost efficiency turn to freely available AI-powered chatbots or automation tools, often unaware of the security risks. In fact, 80% of business leaders worry that sensitive data could slip through the cracks due to unchecked AI use.2<\/sup> <\/p>\n\n\n\n

Take a marketing team using an AI-powered content generator. If they connect it to unsecured sources, they might inadvertently expose proprietary strategies or customer data. Similarly, AI models often inherit the same permissions as their users, meaning an over-permissioned employee could unknowingly expose critical company data to an AI system. Without proper data lifecycle management, outdated or unnecessary data can linger in AI models, creating long-term security exposure. <\/p>\n\n\n\n

Addressing the risk<\/h4>\n\n\n\n