Description
AI is the biggest opportunity to come along for MSPs. This is one of those moments when you need to catch the wave. Being early to market and addressing AI can be a differentiator for your MSP. As national chains begin to take advantage of AI to automate solutions, you want your MSP package to stand out with its solution set tailored to top of mind issues for business owners. AI is that issue. In this 3-month course we will meet 7 times to understand the AI opportunity and how to integrate it into our MSP offering. We will jump out of the gate with an Acceptable Use and Ethics policy that will get your clients thinking about AI from a business and productivity perspective. Then we will look at the data governance and privacy protections and develop solutions for them. Next time we address security and then we look at measuring success. Finally, we take the entire learning and developing our AI offer and present those to each other for critique. At the end of this course, you will have a well-thought AI management consultancy built into your MSP package. Want to go further? Gain ideas for AI integration, development and training along the way. Communicate with fellow student and get valuable feedback.
Month 1: Foundation and Core Concepts (Weekly Meetings)
Week 1: Introduction to AI Consultancy for MSPs
- Overview of AI technologies relevant to MSP clients
- Market opportunities and potential revenue streams
- Quick start! Review of AI Acceptable Use and Ethics Policy
- Discussion on policy strengths and areas for improvement
Week 2: Data Governance in AI
- Importance of data governance in AI implementations
- Review of currently available tools
- Key components of a data governance framework:
- Data quality management
- Data security and privacy
- Data lifecycle management
- Regulatory compliance
Week 3: AI Security and Risk Management
- AI-specific security threats and vulnerabilities
- Best practices for securing AI systems
- AI risk assessment and mitigation strategies
- Review of currently available tools
Week 4: AI Monitoring and Performance Optimization
- Key performance indicators (KPIs) for AI adoption by employees
- Tools and techniques for monitoring AI use and security
Month 2: Advanced Topics, Policy Review, and Integration
Week 6: AI Integration and Interoperability
- Integrating AI solutions with existing MSP tools and workflows
- Example: Copilot connection to Autotask. Other integration examples?
Week 8: Developing an AI Consultancy Rollout Strategy
- Creating a phased approach for introducing AI consultancy services
- Identifying key milestones and success metrics
- Student Preparation for Presentations
Month 3: Presentations and Feedback
Week 10: Presentations of AI Offerings
- Students present their developed AI consultancy offerings.
- Peer and instructor feedback sessions.
- Discussion on next steps, including potential refinements, go-to-market strategies, and implementation plans.
