Guide for MSPs on Leading AI Adoption for Their Customers

AI adoption is rapidly accelerating across companies of all sizes, yet in most cases it is happening without strategy and governance, diminishing effectiveness and creating security risks. “Shadow AI” is the modern plague. This creates a major opportunity for MSPs to step up as trusted AI adoption advisors, increase customer satisfaction, and establish one more revenue stream.

Reviewing recent research by a variety of analyst firms, we identified the top three AI implementation risks for SMBs that MSPs can reduce: lack of visibility on AI usage, AI usage policy, and operational control.

1. Transition from “Shadow AI” to managed AI

The number one challenge for most businesses is unsanctioned AI usage by employees. They use a variety of services and produce results of unknown quality, as well as expose confidential business information to AI tools that do not provide privacy and confidentiality.

Guide for MSPs:

1. Audit AI usage across all endpoints. If you use Acronis, then enabling GenAI security on endpoints will enable AI usage tracking.
2. Define a list of approved tools.
3. Document a clear AI usage policy for the company.
4. Offer AI usage monitoring as an ongoing managed service
5. Offer automation of business processes using AI tools–deploying and configuring agents, implementing processes and workflows for customers. Those projects can be part of the ongoing managed services offering or one-off projects.

The key selling message for the customers is helping them to gain productivity in a managed environment.

2. AI literacy as a service

A lack of AI literacy among employees and management is one of the biggest blockers to gain productivity. Many organizations do not systematically train their employees on AI tools and prompt engineering, not to mention workflow automation. MSPs can lead here and add another training service in addition to security awareness training, making AI literacy a billable service.

Guide for MSPs:

1. Build or license AI literacy training.
2. Design an onboarding and continuous training process on AI tools for the employees.
3. Offer coaching on AI automation for business processes specific to a customer.

Key selling points here are that employees training on AI are more productive, delivering more value to the business, as well as reduced risk of a security breach or confidential data disclosure because of human errors.

3. Secure data and workflows

Data leakage via AI prompts is already causing incidents, including exposure of source code and confidential business data. The risk increases as employees upload files or reuse sensitive information in AI interactions.

Guide for MSPs:

1. Classify sensitive data and define policies for data usage with AI.
2. Enforce prompt restrictions and data loss prevention controls. If you use Acronis, the tools will be available as a security plan in the next three months.
3. Integrate AI usage into existing data security and compliance frameworks.

The key selling point here is that AI workloads should be treated the same as other types of workloads, like endpoints, servers, virtual machine or Microsoft 365 accounts. All workloads require cyber protection, management, and automation.

Call to action

AI is here. However, for many customers, safe AI adoption is still optional. Eventually, AI protection will be a default option like backup and endpoint protection. While few MSPs are providing those services, you can be one of the first and gain a competitive advantage.

Consider taking the following three steps now:

1. Educate your team on AI – for their own productivity and for the scenarios they could implement for your customers.
2. Design managed AI service offerings, and offer them on top of your traditional packages or include them into higher tier packages and use them to upsell customers to the next tier.
3. Upgrade your tools to enable AI workload protection, management and automation.

The opportunity is here to take, yet you have to act fast.