
As the CTO of an MSP, you’re constantly looking to improve efficiency without compromising the quality of support you deliver to your clients. With the increasing volume of tickets, the growing complexity of IT infrastructures, and the ongoing shortage of skilled technicians, AI has become a strategic game-changer.
But not everything should be automated. Some workflows are ripe for AI and can deliver an immediate return on investment. Others, however, still involve too much risk or require a human touch.
In this article, discover 10 workflows you can (and should) automate today using AI, along with 3 you should avoid for now to maintain service quality and client trust.
10 Workflows to Automate Now
1. Smart Ticket Triage
AI can automatically analyze the content of an incoming ticket to:
- Summarize the request
- Set the right priority
- Suggest a category
- Assign it to the right technician
The goal here is to eliminate repetitive tasks for your team. Many MSPs have dispatch coordinators (often highly experienced staff) who are limited to repetitive tasks with little value. AI can offload them and allow them to shift toward higher-impact roles: training, process optimization, quality reviews…
We recommend starting with AI-driven triage in a recommendation mode, allowing your coordinator to build trust in the results before switching to full automation. This also helps them adapt to their new responsibilities and reassures them that the goal is not to replace them, but to help them evolve.
2. Automated Responses to Repetitive Requests
By combining AI with your documentation (ITGlue, SharePoint, Hudu…), you can automate responses to common issues like password resets, VPN access, or software installations. But more importantly, you can enrich incomplete tickets. How often do you get a ticket that simply says, “I need help”?
Such tickets are unusable without context. AI can automatically suggest follow-up questions for the client, ensuring your technicians only deal with complete and actionable tickets.
Benefit: fewer L1 tickets, higher client satisfaction, 24/7 instant responses.
3. Ticket Data Extraction and Enrichment
AI can automatically detect:
- The device or user involved
- The impacted equipment
- Similar past incidents
Benefit: faster diagnostics, fewer back-and-forths, time saved for your techs.
4. Auto-Linking to Documentation
Your AI agent can insert a link to the most relevant documentation to help resolve the ticket. Let’s be realistic—there are two common cases:
- Senior technicians who solve tickets on their own without checking the documentation, which leads to inconsistencies or errors. Pushing them the right doc ensures a service level aligned with your standards.
- Junior technicians who often don’t even know where the documentation is. Giving them instant access to the right information speeds up resolution and promotes learning.
Benefit: more accurate answers, process standardization, faster onboarding.
5. Smart RMM Alert Filtering
AI can identify and remove false positives, group correlated alerts, and surface only critical issues. The goal is to reduce noise so you can focus on real emergencies—improving responsiveness and saving time.
6. Automatic Post-Ticket Summaries
Once a ticket is closed, your AI agent can generate a clear summary: action taken, root cause, recommendations. This is powerful because these summaries become reliable documentation for future tickets.
Benefit: better traceability, consistent reports, less admin work.
7. Proactive Maintenance Suggestions
AI can identify early warning signs in logs—like disk saturation or frequent network errors—before an incident occurs.
Benefit: shift from reactive to proactive support, preventing issues before they happen and reducing repetitive tasks. You’ll improve client satisfaction by demonstrating expertise and reduce ticket volume to boost your margins.
8. Call and Voicemail Transcription
AI can transcribe and summarize incoming calls or voicemails left by users. No more receptionists manually creating tickets from voicemails.
Benefit: faster documentation, better traceability, richer context.
9. Automated Client Reporting
AI can generate personalized periodic reports on:
- Ticket volume
- Response times
- Recurring issues
Benefit: improved client loyalty, greater transparency, time saved for account managers.
10. Customer Feedback Analysis
Semantic analysis lets AI extract trends and pain points, helping you act on client dissatisfaction before it’s too late.
Benefit: targeted continuous improvement, early detection of dissatisfaction.
3 Workflows You Shouldn’t Automate (Yet)
1. Resolution of Complex or Critical Tickets
Sensitive infrastructures or unique client environments require human expertise.
Risk: misjudged situations, loss of credibility, severe incidents.
2. Handling of Sensitive Escalations
Escalating a ticket requires a nuanced understanding of context, client relationships, and contractual obligations.
Risk: political or business errors, client dissatisfaction.
3. Human Interaction with End Users
When emotions, frustration, or conflict arise, empathy and human presence are irreplaceable.
Risk: client disengagement, feeling of dehumanization.
Conclusion
Artificial intelligence doesn’t replace your technicians; it amplifies them. By automating repetitive tasks, you give your team back the time to focus on what truly matters.
✅ Start with low-risk, high-ROI workflows.
⏳ Keep sensitive workflows in the hands of your human experts.
📈 Look forward to healthier, more sustainable growth powered by AI.