Making sense of AI compliance from an MSP perspective

The 2020s will undoubtedly go down in history as the decade in which artificial intelligence truly emerged.

While AI concepts and programmes have been prevalent since the mid-20th century, it is only in recent years that we've seen the sophistication and deployment of real-world solutions really ramping up. 

The statistics speak for themselves. At the beginning of the decade, the global AI market was valued at $93 billion; by 2030, that figure is anticipated to reach $826 billion.

At the core of this rapidly evolving market is generative AI, with programmes such as OpenAI's ChatGPT and Google's Bard already being used for a broad variety of applications, from creating content to summarising complex data and generating code. 

The benefits of these technologies are clear, from boosting productivity to enabling better decision-making. However, their rapid advancement has also sparked widespread concerns regarding ethical and legal implications and the potential for misuse, be it misinformation, deepfakes, or other harmful content. 

Growing complexity in the AI regulatory landscape

Such debates have naturally drawn the attention of governments that are increasingly working to ensure that AI development is better monitored and managed through the introduction of relevant legislation. 

Here, the European Union is leading the way, having introduced the first legal framework on AI in an effort to develop standards for systems designed to mitigate risks related to bias, privacy, and transparency. Named the EU AI Act, the regulation outlines obligations that providers, deployers, importers, distributors, and product manufacturers of AI systems must follow to achieve compliance.

With that said, it isn't the only legislation that firms must pay attention to.  From the OECD's AI principles focused on improving AI transparency, safety, and accountability to ISO 42001 – an international standard that specifies requirements for establishing, implementing, maintaining and continually improving AI management systems – there are a host of new and evolving frameworks that enterprises must remain vigilant of.

While AI regulation is undoubtedly necessary, it poses a key challenge for enterprises as demands heighten. Indeed, by 2026, Gartner predicts that 50% of governments worldwide will enforce the use of responsible AI through regulations, policies and the need for data privacy.

Given these forecasts, Managed Service Providers must pay attention.

Not only will MSPs need to stay ahead of the curve to achieve AI compliance themselves, but they must also keep a finger on the pulse of evolving regulations to ensure that they align with the needs of clients seeking support in this domain. 

Outlining the CaaS opportunity for MSPs

Already, we're seeing these demands materialising in the form of a growing compliance-as-a-service market.

Again, according to Gartner's forecasts, legal and compliance department investment in governance, risk, and compliance tools is expected to increase by as much as 50% between 2023 and 2026.

Here lies a huge opportunity for MSPs. 

The shift towards frameworks like NIS2, DORA, and AI-related regulations will only further increase complexity moving forward. As a result, those that lack the knowledge of key standards or simply don't have the time or resources to get up to speed and remain on top of them as they evolve will be looking for partners to help them achieve compliance.

By positioning themselves as experts in AI compliance, MSPs can become go-to partners for managing this complexity, offering AI compliance services, support and solutions to help businesses avoid regulatory risks and adopt AI responsibly.

Achieving this offers a pivotal chance to diversify revenue streams and unlock major competitive advantages, adding significant value beyond traditional IT service and security support. In fact, a 2024 Statista report indicates that 39% of SMBs prefer working with MSPs who can provide end-to-end compliance services.

Moving beyond automation to deliver a holistic approach

As with any effort to diversify and explore new revenue opportunities, MSPs may have to adapt in order to capitalise effectively.

Primarily, it is important to recognise that effective AI compliance services require a mix of technologies, human oversight and solutions integration efforts. Further, this is a combination that potential clients have come to expect. According to PwC, 84% of businesses anticipate their compliance tool expenditure to increase by 2025, but most are also looking for solutions that include human oversight and adaptability.

For some MSPs, this might require a change in approach. Many MSP models are built on the effective use of automated solutions. With AI compliance, however, they will need to focus on balancing these solutions with additional compliance best practices, of which there are several:

#1 – Integrating people, processes and platforms

First, people, processes and solutions must all be working in a harmonious and complimentary manner to achieve holistic compliance. To help clients achieve this, MSPs should be looking to leverage key central platforms that can enable automated processes to easily be balanced with human involvement to drive greater accuracy and transparency. According to a 2022 survey, companies using compliance platforms with automated reporting saved 25% of their compliance costs. However, those combining automation with human oversight saw 40% higher compliance success rates.

#2 – Transparency and trust

Leveraging platforms that can both automate workflows and allow for human oversight is particularly crucial both in sectors where human judgement and experience are necessary, and in instances where clients need clear, easily accessible insights. According to a Forrester study, 70% of customers prefer transparency in compliance management and want regular updates on their status. Therefore, it is vital that firms offer this, providing clients with user-friendly compliance dashboards that make it easy to interpret key data. 

#3 – Time and cost savings

It's also essential to let AI's merits shine. In this sense, any AI compliance platform should be capable of integrating with existing business tools to minimise manual work while still allowing for crucial human oversight. Gartner estimates that poor data quality costs organisations an average of $12.9 million annually. Inefficient compliance processes often stem from inadequate data management, leading to increased operational costs and compliance risks. Automating routine tasks while leaving room for human expertise in risk assessments and audits helps MSPs achieve compliance faster and more cost-effectively.

Packaging AI security and compliance solutions as one comprehensive offering

By achieving these best practices, MSPs won't just be well placed to adhere to evolving regulatory requirements themselves. Equally, they will be able to use their expertise to help their clients seeking support on an ongoing basis.

With IBM's Cost of a Data Breach Report 2023, revealing that breaches cost almost $220,000 more on average when non-compliance with regulations was indicated as a factor in the event, the motivations for companies to seek effective CaaS solutions will only continue to grow as AI regulations evolve and expand.

By providing the tools to reduce the risk of penalties while also saving time and costs on audits and remediation efforts, MSPs can offer immense value as CaaS leaders, combining their existing skillsets in cybersecurity and IT best practices to provide a comprehensive client offering.

By packaging AI security and compliance as one integrated service offering, MSPs will be well placed to capitalise on a massive and growing market opportunity.