August 7, 2025
Why MSPs Should Offer AI Auditing Services (It’s More Than a New Revenue Stream)
Contents
Managed Service Providers, or MSPs, are stewards of information technology for organizations without internal IT teams. Businesses rely on their MSP of choice to advise on the technology tools they’ll need to enable operations to run smoothly, and in some cases, stay ahead of their competition. In recent months and years, a split has developed between “traditional” MSPs and more modern ones, with the main differentiator being AI offerings and capabilities. Smart MSPs are taking their services a step further than AI implementation and are also offering AI auditing services.
As organizations incorporate AI into their business processes, either with or without the assistance of an MSP, their associated AI risk is growing. Beyond compliance with local legislation, AI trust is in a delicate position right now. Consumers have concerns about bias and unfair practices that may come about due to AI use, and organizations should be proceeding eyes-wide-open to AI risk in order to maintain their brand reputation. MSPs have the opportunity to help in that effort by starting with AI auditing services.
Why MSPs are Positioned Well to Offer AI Auditing Services
MSPs are deeply embedded in their clients’ technology ecosystems, giving them unique insight into processes utilizing artificial intelligence. If a business hires an unknown third party for AI auditing services, it must go through an extensive access process. That includes granting entry to all relevant technology platforms. MSPs, however, often already have access to those platforms. In some cases, they even provide direct access to the client.
Beyond access advantages, AI auditing services are also well-aligned with MSP services from a technical expertise perspective. Most MSPs manage critical infrastructure, protect sensitive data, and work within complex regulatory environments. Adding AI to their scope is a natural step. For example, an MSP familiar with SOC 2 or GDPR compliance can apply similar processes to evaluate AI models. These models may need to meet frameworks like the EU AI Act or industry-specific standards.
Many organizations also have a difficult time determining who to trust regarding technology they may not fully understand. An MSP’s account manager, though, already holds a trusted position. They usually bring proven credibility and a history of solving the client’s tech challenges. In B2B sales, getting an attentive audience is often the hardest part. Fortunately, MSPs have already established those key relationships.
What AI Auditing Actually Involves (Demystifying the Service)
AI auditing may sound complex, but for MSPs, it’s a structured process that builds on skills they already have in data management, compliance, and security. Understanding the core components of AI auditing helps MSPs confidently explain the value to clients and integrate it into their service portfolio.
1. AI Model & Data Assessment
AI systems are only as good as the data on which they are trained. Errors, biases, and other factors that can limit performance and expose a company to AI risk often begin with the data. This step of the audit often involves the following tasks.
- Data source validation: Ensuring that the data feeding AI models is accurate, complete, and responsibly sourced.
- Bias and fairness checks: Identifying skewed datasets or model behaviors that could lead to discriminatory outcomes.
- Model performance testing: Verifying that AI models perform as expected under real-world conditions, not just in controlled testing environments.
2. Compliance and AI Risk Management Framework Alignment
Once the model and data are assessed, the next step is to map AI usage to applicable regulatory and industry frameworks. Organizations in sensitive industries like banking, healthcare, and insurance are subject to strict regulations already, even before introducing AI usage. Increasingly, though, governments are enacting laws to specifically regulate algorithm usage, such as the EU AI Act and NYC Local Law 144. Responsible teams should ensure they are compliant with necessary laws to avoid undue risk exposure.
Beyond a New Revenue Stream: Strategic Benefits for MSPs Offering AI Auditing Services
Of course, a new SKU can translate to an uptick in revenue simply because of an additional service available for purchase. The strategic advantages for MSPs offering AI auditing services extend much further than a new revenue source, though. Proactively identifying which clients may have a need for their AI systems to be audited and broaching the subject with them in a collaborative way demonstrates that the MSP has their best interests in mind. By embedding themselves into their clients’ AI processes, MSPs also strengthen the relationship. This deeper involvement helps extend client lifecycles and increases customer lifetime value.
Adding innovative AI services to their offerings can also position MSPs well in a competitive market. Demonstrating to clients – both existing and potential ones – that the business is future-focused and preparing for the solutions they’ll need in the coming years can demonstrate expertise and credibility that competitors may not have.
Partnerships to Scale AI Service Offerings
Managed service providers don’t need to build new AI services from scratch. Partnering with AI governance providers and AI consulting companies allows them to bring in dedicated, established expertise and processes to support their clients, without taking on massive internal development initiatives.
If you’re interested in exploring partnership options, we’d love to hear from you. Visit our partnership page to get started today.