How to Simplify Compliance Across Multi-Cloud Environments

What Is Multi-Cloud Compliance?

Multi-cloud compliance is a complex process of adhering to laws and industry mandates concerning data security and privacy in the cloud. It involves working across platforms to ensure consistent visibility and control over how data is stored, accessed, and shared.

Compliance requirements vary widely by region and industry with regard to data handling, data residency, encryption standards, and more. Cloud providers (CSPs) like AWS, Microsoft Azure, and Google Cloud each add to this with their own management tools, configurations, and security policies. Thus, the more clouds an organization uses, the more difficult it becomes to stay fully compliant.

To overcome this, organizations need a way to make configuring, maintaining, and attesting compliance easier and faster.

Why Simplifying Multi-Cloud Compliance Matters

Failing to meet compliance standards can have major consequences in these key areas:

• Financial penalties: Regulations like HIPAA and PCI DSS impose steep fines for violations. For example, HIPAA breaches can cost up to US$71,162 per record, and PCI DSS noncompliance can cost up to $100,000 per month (as of 2025). These penalties alone make compliance a top priority.
• Lost revenue and trust: Data breaches, failed audits, or negative press can erode customer trust and weaken business relationships. Many companies find it difficult to restore their reputation, leading to lost revenue and reduced growth opportunities.
• Operational disruption: Noncompliance can force organizations to pause their operations while they address violations or rework systems. This, in turn, can delay product launches, disrupt workflows, and create other ripple effects throughout the organization.

By automating monitoring, improving visibility, and addressing risks proactively, organizations can reduce the likelihood of violations. Investing in compliance upfront doesn’t just reduce penalties—it supports the ability to grow without interruptions.

Multi-Cloud Compliance Challenges

What is it, specifically, that makes multi-cloud regulatory compliance so difficult? Let's take a closer look at the major challenges:

Shared Responsibility Models

Most CSPs follow a shared responsibility model. The CSP handles certain security elements (like protecting physical servers), while the customer is responsible for securing workloads, user access, and configurations. Any confusion about who is responsible for what can lead to compliance issues. For example, a CSP might not notice a misconfigured database, but it still leaves the customer exposed to risks.

Lack of Unified Tools and Visibility

Each CSP offers its own compliance tools, but they often can’t integrate with other platforms. As a result, it can be difficult for customers to get a full view of their compliance across all cloud platforms. Without centralized monitoring tools, they will struggle to detect violations, track permissions, or manage data movement efficiently.

Shadow IT and Lack of Control

In multi-cloud environments, IT teams often lack visibility into unsanctioned tools that may violate compliance. For example, sensitive data could be stored in locations or processed by tools that don’t meet GDPR or HIPAA requirements. Without proper oversight, shadow IT expands the attack surface and undermines efforts to centralize control over compliance.

Constantly Changing Resources

Cloud resources constantly scale up or down to meet customers' evolving needs. This makes traditional compliance methods, like manual configuration reviews or static enforcement, ineffective because of how quickly they can become irrelevant. When controls can’t keep up, they can leave critical assets unprotected.

Wider Attack Surfaces and Data Sprawl

On top of the operational challenges, multi-cloud environments introduce a larger attack surface. Data is often stored in multiple locations and regions, increasing risk. For example, regulations like GDPR require region-specific handling of data, but tracking compliance for data across multiple jurisdictions can be highly complex without advanced tools.

Auditing Complexity and Overlap

In a multi-cloud setup, compliance audits require the gathering of evidence from multiple platforms. Compared to a single cloud, this increases the time and resources needed, especially when compliance frameworks overlap or conflict. Companies often find it takes months to prepare for audits—time they could be using to improve other aspects of the business instead.

Identity and Access Management (IAM) Failures

Access management across multi-cloud environments can be challenging when each CSP has its own IAM framework. Roles can vary widely between platforms. For instance, a user with admin access in one cloud may need wholly different permissions in another. Without centralized tools, it can be difficult to avoid overprivileged and unauthorized access, leading to compliance issues.

Evolving AI Compliance Norms

AI systems may process large amounts of sensitive data. However, AI regulations are still evolving, and they vary widely worldwide. Without proper oversight, organizations risk exposing data, introducing algorithmic bias, or failing audits as AI models interact with multi-cloud resources. This can get complicated quickly if models trained in one jurisdiction are deployed or accessed in another where different compliance mandates apply.

Why Traditional Strategies Don’t Work

Traditional compliance programs struggle to keep up with these challenges in modern cloud systems. They tend to focus on manual reviews, basic security controls, and annual audits. Compliance teams map out all resources, match them to regulations, and confirm controls are in place. As point-in-time assessments, they are functional for static environments, but less suited to the rate of change in the cloud.

Here are a few of the ways traditional strategies fall short:

• Time-intensive processes: Manual configuration monitoring across multiple CSPs is simply not practical when environments change constantly.
• Short shelf life: Traditional compliance reviews create "snapshots" that rapidly become outdated in dynamic cloud settings, leading to blind spots.
• Knowledge gaps: Compliance regulations can evolve rapidly. Without up-to-date knowledge and expertise, organizations will struggle to keep up with changes.
• AI complexity: Traditional programs lack the visibility and scale to effectively identify, benchmark, analyze, or remediate AI data breach risks.

Strategies to Simplify Multi-Cloud Compliance

To keep compliance in lockstep with their multi-cloud strategies, organizations need smarter approaches that limit effort while improving security and efficiency. Here are five key steps:

1. Create Clear Security Policies and Improve Visibility

Start by defining clear security rules that follow legal and industry standards. Translate these rules into practical actions that guide your users and IT. Use tools that simplify compliance monitoring across all cloud systems to ensure no blind spots are overlooked.

2. Automate Compliance Checks

Automated tools can analyze systems for risks, noncompliance, or misconfigurations in real time. By finding and fixing issues without relying on manual review, you'll save time and effort while reducing your exposure to violations and breaches.

3. Focus on High-Risk Areas

Some areas of your cloud environment carry more risk than others. Use risk-based controls to prevent high-priority security threats. Identify gaps before they turn into costly violations, and assign resources to address the most critical threats first. This is especially important to consider as you adopt tools like AI assistants.

4. Use Automated Reporting Tools

Manual audits often miss critical errors or become outdated quickly. Automated systems provide detailed, up-to-date compliance reports you can use during audits or to assess progress. With these systems in place, compliance teams can focus on improving systems instead of gathering paperwork.

5. Collaborate Across Teams

Compliance shouldn’t be the responsibility of just one team. Your development, operations, and security teams need to work together to share responsibility. Foster workflows that help your teams address security and compliance at every step of development and deployment, making it easier to prevent violations in the first place.

How Zscaler Can Help

Zscaler Data Security Posture Management (DSPM) delivers complete visibility, automation, and consistent controls to simplify compliance across public clouds and on-premises environments.

Built on a unified data loss prevention (DLP) engine, Zscaler DSPM helps prevent compliance violations at scale by identifying sensitive data, classifying it, and contextualizing exposure. This ensures consistent security for sensitive data across all channels, in line with GDPR, HIPAA, PCI DSS, and more.

• Compliance visibility: Gain real-time insights into compliance status, configuration drift, and policy violations.
• Compliance benchmarking: Assess gaps by auto-mapping your data security to compliance frameworks and best practices.
• Remediation: Prioritize and address compliance risks while tracking progress for stakeholders.
• Analytics and reporting: Automate reporting for audits, reducing resource strain and ensuring accuracy.

Built-in AI security posture management (AI-SPM) provides deep visibility into your AI services, agents, and models. Advanced LLM classification lets you easily discover, classify, and assess risks of sensitive data mapped to any AI service for a complete view of your data, AI, and correlated risks.