The rapid adoption of AI tools has created a new set of complex challenges for MSPs and MSSPs. While AI offers incredible efficiencies, it also introduces significant cybersecurity risks that many organizations are unprepared to handle. Service providers are now on the front lines, tasked with guiding their clients through this unfamiliar territory.
To help you navigate this new frontier, we sat down with Cynomi’s CISO, Dror Hevlin, and Product Manager, Ayla Fineberg. They shared their insights on the rise of AI-related threats, the importance of new security frameworks, and how the Cynomi platform empowers service providers to manage these risks effectively.
This post will explore the key challenges of AI security, explain how new frameworks within Cynomi vCISO Platform provide a roadmap for governance, and demonstrate how to transform this challenge into a strategic opportunity to scale your services.
The Biggest AI Security Challenges for Service Providers
The primary challenge for MSPs and MSSPs is understanding and mapping the new landscape of AI-related risks. These risks are not always obvious and can span across an entire organization, affecting both human and technological processes.
Identifying New and Amplified Risks
According to Dror, the first and most significant hurdle is identification. “The biggest challenge is knowing how to map the AI risks because some of them are fairly new and they’re all across the board,” he explains. Service providers often struggle to determine where to integrate AI risk management into their existing processes. To identify new or amplified risks, you must first understand how AI is used within a client’s organization.
One example is data leakage. This has always been a concern, but generative AI tools can dramatically increase the risk. An employee might unknowingly paste sensitive company data into a public AI model, creating a breach. As Dror notes, AI “amplifies existing risks, potentially exposing more data than intended or revealing sensitive information.”
Lack of Awareness Among Clients’ Management
MSPs frequently encounter a critical challenge: clients’ management often lacks awareness regarding the rapidly evolving cybersecurity and compliance risks associated with AI. These aren’t static threats; new AI-related dangers emerge daily, yet many leaders remain oblivious, operating under a false sense of security. It’s the MSP’s responsibility to bridge this knowledge gap. Before any protective actions can be effectively implemented, MSPs must proactively educate management, ensuring they fully grasp the specific, dynamic risks AI introduces to their organization.
The Unpredictability of “Shadow AI”
On top of insufficient awareness to risks, a common challenge MSPs face is the disconnect between a client’s management and their employees regarding AI usage. Often, leadership may confidently assert that their organization does not use AI tools, unaware that employees are actively incorporating these tools into their daily workflows.
Just like Shadow IT, this unsanctioned use called “Shadow AI” creates a massive blind spot for security teams. “People will use it because it saves them time,” Dror says. “They’re using AI tools without the formal approval of the CISO or IT team.” This makes it nearly impossible to govern data, manage access, and protect the organization from potential threats. Detecting and controlling this hidden usage is a critical first step.
The Evolution of Security Frameworks for AI Governance
To address this new reality, global standards organizations have begun releasing frameworks specifically designed for AI security and risk management. These frameworks provide the structure needed to govern AI use effectively. Cynomi has integrated leading AI frameworks into its platform to help MSPs and MSSPs guide their clients toward compliance.
Key Frameworks MSPs Need to Know
Cynomi supports several of the most critical AI security frameworks, chosen based on partner requests and international relevance.
- NIST AI Risk Management Framework (RMF): Developed by the U.S. National Institute of Standards and Technology, the NIST AI RMF is quickly becoming an international reference point for managing AI risks. It provides a structured approach to identifying, assessing, and mitigating AI-related threats.
- ISO/IEC 42001: This is another key international standard that provides a framework for establishing, implementing, maintaining, and continually improving an AI Management System (AIMS).
- EU AI Act: This landmark regulation is set to become a global standard. It will require organizations, even those outside the European Union, to demonstrate responsible AI practices if they serve EU customers. Its impending enforcement makes it a top priority.
As Ayla explains, “These are the most well-known, most supported frameworks that exist today.” By incorporating them, Cynomi enables service providers to stay ahead of the curve and prepare their clients for future compliance demands without adding any overhead on the MSP team.
How Cynomi Helps Operationalize AI Security
Understanding the frameworks is one thing; implementing them is another. This is where the Cynomi vCISO platform creates significant value for service providers.
Seamless Integration and Actionable Tasks
Cynomi simplifies compliance by integrating these new AI frameworks directly into its existing workflow. “It’s already part of your stack. You don’t have to do anything special for it,” says Ayla. During the normal assessment process, you can select the relevant AI frameworks. The platform then automatically maps the requirements to concrete, actionable tasks, so you follow the same workflow you and your clients are used to.
Instead of deciphering dense framework documents, you receive a practical remediation plan. “We take this information and digest it into something practical,” Ayla adds. This connects high-level compliance goals to the day-to-day tasks needed to achieve them, all within your existing risk management plan.
From Risk Identification to Management and Reporting
The platform provides a complete, end-to-end solution. It helps you:
- Identify risks: Use built-in assessments to discover where and how AI is being used.
- Manage compliance: Automatically align your security posture against multiple frameworks like the EU AI Act or NIST AI RMF.
- Generate reports: Create clear reports that demonstrate compliance and show progress to clients and their stakeholders.
This operational approach turns a complex, daunting challenge into a structured, manageable process, allowing you to offer advanced AI compliance services as a value-add for your clients.
The Broader Impact: Building Trust and Becoming a Trusted Advisor
Effectively managing AI security is about more than just mitigating risk. It’s about building trust and demonstrating accountability. Service providers have a crucial role to play in educating their clients and guiding them responsibly.
By addressing AI risks proactively, you position yourself as a forward-thinking strategic partner, not just a technical service provider. This opens the door for more meaningful conversations with client leadership about business-level risks.
This educational role is key. Many business leaders only see the upside of AI and are unaware of the dark side. By explaining the risks and providing a clear path to manage them, you enable your clients to innovate safely. You become the trusted advisor who helps them harness the power of AI without exposing their business to unacceptable threats.
The world of AI security will continue to evolve rapidly. With tools like the Cynomi platform, you can stay ahead of the trends, strengthen client relationships, and deliver the expert guidance your clients need to thrive in the age of AI. As AI becomes increasingly prevalent in our daily lives, it is crucial for organizations to prioritize security and mitigate potential risks. With the right knowledge and tools, you can help your clients navigate the complex world of AI security and stay ahead of potential threats.
The time to act is now. Start a conversation with your clients today about AI risks and demonstrate your commitment to protecting their future. You can start by using this AI Risk Cybersecurity Hygiene Checklist.
Frequently Asked Questions
How do we protect client data when employees use AI tools like ChatGPT or Copilot?
Protecting data starts with clear usage policies and employee education. Ensure staff know which data is safe to share and which must stay confidential. Implement robust access controls, data loss prevention tools, and monitor for uploads to unsanctioned AI platforms. Regular training on AI security best practices, combined with technical controls that restrict sensitive data sharing, reduces the risk of leaks.
How can we detect and control shadow AI use in client environments?
Shadow AI can be detected by shadow IT detection tools. For example, network monitoring and endpoint security solutions can identify unusual web traffic, unauthorized app installs, or access to external AI services.
Once detected, set clear policies about allowed tools and educate employees on approved usage. Consider dedicated shadow IT/AI detection software to enhance visibility and control.
Which security or compliance frameworks should we follow for AI risk management?
The leading frameworks for AI risk management include the EU AI Act, NIST AI RMF, and ISO/IEC 42001. These frameworks address the unique risks posed by AI and are becoming international standards for compliance. Your organization may also need to follow regional or industry-specific guidelines, so assess your client base and regulatory obligations carefully.
AI frameworks keep evolving, and therefore it is recommended to work with an automated platform that continuously updates to ensure compliance with the latest standards and regulations.
How can we include AI security in our vCISO or compliance service offerings?
Integrate AI risk assessments into your standard onboarding and risk management workflows. Use platforms like Cynomi that operationalize AI-specific frameworks and provide actionable tasks for compliance. Offer continuous monitoring, staff training, policy drafting, and regular reporting on AI-related risks as part of your vCISO or compliance packages to deliver added value for clients.
What specific AI threats or attack vectors should we worry about?
Key AI threats include data leakage (e.g., sensitive data shared with public AI tools), model manipulation or poisoning (feeding bad data to AI systems), misconfigurations that lead to unauthorized access, and autonomous AI agents taking unintended actions. Shadow AI use, lack of transparency in model decisions, and adversarial attacks against AI models are also growing concerns. Address these through a combination of technical safeguards, employee education, and adherence to recognized frameworks.