Dispatch Prioritization Rules in AI Autopilot

AI Autopilot’s dispatch prioritization system is designed to ensure that every service ticket is handled efficiently, based on a set of dynamic rules that evaluate ticket urgency, technician availability, skill set, and SLA compliance. By leveraging AI-driven insights, the platform automatically dispatches tickets to the most appropriate technician, ensuring that high-priority tickets are handled first while balancing workloads across your team.

Here’s an overview of the dispatch prioritization rules used in AI Autopilot:

1. Urgency and Impact-Based Prioritization

At the core of AI Autopilot’s dispatching system is an assessment of each ticket’s urgency and impact. These factors determine how critical the ticket is to the client’s operations and guide the platform’s prioritization process.

Urgency: This reflects how quickly the issue needs to be addressed. Tickets with high urgency—such as system outages or security breaches—are prioritized over lower-urgency tickets like routine maintenance.
Impact: This evaluates the effect the issue has on the client’s operations. High-impact tickets, such as those affecting an entire department or business-critical systems, are prioritized over low-impact issues affecting individual users or minor systems.

Rule Example: A ticket reporting a server outage affecting multiple departments would be assigned a higher priority than a request for a routine software update on an individual workstation.

2. SLA Compliance Monitoring

SLA compliance is critical for MSPs, and AI Autopilot ensures that tickets approaching their SLA deadlines are reprioritized to meet your service-level agreements.

SLA Deadline Monitoring: AI Autopilot tracks the remaining time for each ticket’s SLA deadline. Tickets nearing their deadline are automatically prioritized, even if they were originally lower in the queue.
SLA-Based Escalation: If a ticket is close to breaching its SLA, AI Autopilot can escalate it automatically to higher-tier technicians or management to ensure it receives the necessary attention.

Rule Example: A ticket categorized as low priority but approaching its SLA deadline would be moved up in the queue, ensuring compliance without manual intervention.

3. Skill-Based Ticket Assignment

AI Autopilot assigns tickets based on the expertise and skill set of each technician, ensuring that complex issues are handled by technicians with the right experience and knowledge.

Technician Skill Matching: The platform evaluates the ticket’s requirements (e.g., network issues, cybersecurity threats) and assigns it to a technician with the appropriate skill set. This avoids unnecessary delays caused by mismatched assignments.
Tiered Escalation: If the assigned technician cannot resolve the issue or if the ticket is escalated due to its complexity, AI Autopilot automatically routes the ticket to a higher-tier technician.

Rule Example: A cybersecurity breach would be automatically assigned to a technician specializing in security, rather than a generalist who handles routine desktop support.

4. Technician Availability and Workload Balancing

To prevent overloading certain technicians while others are underutilized, AI Autopilot factors in technician availability and workload when dispatching tickets.

Real-Time Availability Tracking: AI Autopilot monitors technician availability in real-time, ensuring that tickets are assigned to technicians who are ready to take on new work, avoiding delays caused by assigning tickets to unavailable team members.
Workload Distribution: The system balances ticket assignments to prevent technicians from being overloaded. If one technician has too many open tickets, the system assigns new tickets to other available technicians with similar skill sets.

Rule Example: If two network technicians are available but one has a heavier workload, AI Autopilot will assign the next network-related ticket to the technician with fewer active tickets.

5. Client Tier and Role Consideration

Not all clients and users are equal in terms of priority, and AI Autopilot takes client tier and user roles into account when prioritizing ticket dispatch.

Client Tier: Tickets from high-priority clients (e.g., those on premium service plans) are prioritized over those from lower-tier clients. This ensures that your top clients receive the best possible service.
User Role: The system also considers the role of the affected user within the client organization. For instance, tickets affecting C-level executives or critical personnel (e.g., finance directors, HR heads) are given higher priority.

Rule Example: A ticket affecting a CEO at a premium client would take precedence over a similar issue affecting a junior employee at a lower-tier client.

6. Ticket Type and Categorization

The nature of the ticket itself plays a significant role in dispatch prioritization. AI Autopilot uses ticket categorization to ensure that different types of tickets are handled according to their nature.

Incident vs. Request: Incident tickets (e.g., system outages, security breaches) are prioritized higher than service requests (e.g., new user setups, software installations), as they typically require faster resolution to minimize downtime.
Automation of Routine Tasks: For routine requests or recurring issues, AI Autopilot may automate parts of the resolution process (e.g., ticket creation or initial troubleshooting) before assigning it to a technician.

Rule Example: A request to set up a new user would be automatically assigned a lower priority than an incident ticket reporting a major system failure, regardless of when each ticket was submitted.

7. Real-Time Dynamic Reprioritization

Conditions change throughout the day, and AI Autopilot is designed to adapt. The platform continuously monitors all tickets in the queue and reprioritizes them in real-time based on changing factors such as new urgent tickets, approaching SLA deadlines, or shifts in technician availability.

Dynamic Queue Management: AI Autopilot constantly updates ticket priorities, moving high-priority tickets up the queue as conditions evolve. This ensures that your team stays focused on the most critical tasks.

Rule Example: If a new urgent ticket is submitted while a technician is working on a lower-priority ticket, AI Autopilot may reprioritize and reassign the technician to the more urgent issue.

Summary of Dispatch Prioritization Rules in AI Autopilot

Urgency and Impact: Higher priority for tickets affecting critical systems or multiple users.
SLA Compliance: Automatic reprioritization of tickets nearing SLA deadlines to prevent breaches.
Skill-Based Assignment: Ensures the right technician with the right expertise handles each ticket.
Technician Availability and Workload: Balances assignments to avoid technician overload and ensure efficient ticket handling.
Client Tier and User Role: Prioritizes high-tier clients and critical users to deliver exceptional service where it matters most.
Ticket Type and Categorization: Incident tickets take precedence over service requests, ensuring rapid response to critical issues.

Real-Time Reprioritization: Continuously adjusts the ticket queue based on real-time conditions, ensuring the most pressing issues are always addressed first.

Take Control of Your Dispatching with AI Autopilot

With AI Autopilot, you can ensure that every ticket is handled by the right technician, at the right time, based on the factors that matter most to your MSP and your clients. Our AI-driven dispatch system removes the guesswork and manual effort from ticket management, improving response times, SLA compliance, and technician productivity.