Artificial intelligence is changing how MSPs operate, but automating routine tasks is only part of the opportunity.
Mike Casey of FlowMind Networks explores how AI can help MSPs troubleshoot complex problems, improve service delivery, and strengthen operational efficiency. From live diagnostics to engineer development, Casey explains why MSPs should look beyond basic automation when evaluating AI solutions.
1. AI Needs to Go Beyond Routine Automation
Many AI solutions focus on historical information and established workflows. Casey believes MSPs should also consider how AI can investigate unfamiliar technical problems.
He points to issues such as poor Wi-Fi performance or email delivery problems, where identifying the cause requires more than retrieving documentation.
FlowMind’s approach emphasizes live diagnostics that examine current conditions and help engineers identify what needs attention.
For MSPs, the distinction is between automating familiar tasks and diagnosing problems that require deeper investigation.
2. Connecting Technology Systems Creates Better Visibility
MSPs rely on multiple platforms for networking, cloud services, security, documentation, and ticket management. Investigating problems across these separate systems can be challenging.
Casey describes FlowMind’s service orchestration engine as a way to connect information across these environments.
The technology runs diagnostics across connected platforms and returns findings and recommended remediation steps to the PSA ticket, with engineers making the final decisions.
His message is that AI becomes more useful when it can examine the broader technology environment rather than operate within isolated systems.
3. AI Can Help Engineers Become More Effective
Training, retaining, and developing technical talent remain important priorities for MSP owners.
Casey discusses FlowMind’s Intake Navigator, a digital coaching tool that guides engineers through questions needed to investigate customer problems.
He also describes an AI voice capability that gathers information from customers before an engineer becomes available.
These tools are designed to improve troubleshooting and support newer technicians. Casey also emphasizes how AI-supported workflows can encourage more consistent ticket documentation.
For MSPs, AI offers an opportunity to strengthen technical teams while improving service efficiency.
4. AI’s Value Should Be Measured in Real Results
Casey believes MSPs should evaluate AI based on measurable improvements rather than impressive demonstrations.
He discusses FlowMind’s 30-day trial and dashboard approach, allowing MSPs to assess time savings and productivity improvements within their own environments.
Activities such as password resets, onboarding, offboarding, and ticket management illustrate where operational savings can accumulate.
Casey encourages MSP owners to consider these results alongside customer satisfaction, service-level performance, and potential financial benefits.
The goal isn’t simply more automation, but greater efficiency and measurable business value.
What This Means for MSPs
Mike Casey’s perspective highlights why MSPs should look beyond basic automation when considering AI investments.
Live diagnostics, connected systems, stronger technical teams, and measurable operational improvements can help MSPs approach service delivery more effectively.
The central takeaway is that AI should help MSPs solve problems more efficiently while supporting the engineers responsible for their customers.