Level 1 requests are definitively resolved instantly without fundamental human intervention.
ConsultingServices.aiKI-Consulting für KMUUse Case in Detail
Automating IT Service Desk & Ticket Triage.
Up to 120,000 tickets per year, 25-30 minutes processing time per case, and only a 40% self-service rate tie up enormous internal resources. An AI copilot handles automatic categorization, immediately resolves standard Level 1 requests (password resets, access rights), and flawlessly routes complex problems to the right departments.
Starting Point
When is this Use Case worthwhile?
This is your bottleneck:
- High internal ticket volume, where 50%+ are pure standard requests (L1).
- Specialist departments (Level 2 & 3) complain about misassigned tickets (ping-pong effect).
- Employees ignore outdated intranet FAQs and IT portals because searching takes too long.
- "Time-to-resolve" for simple problems is too high (e.g., days instead of minutes).
Less suitable if...
- Your entire company has fewer than 50 employees and tickets are resolved informally.
- IT is managed entirely manually without a ticketing system (no Jira, no ServiceNow, no Zendesk).
Business Impact
Measurable Results in IT Support
AI analyzes the error (including screenshots) and assigns it directly to the correct L2 group.
Users receive immediate help instead of days of waiting for standard requests.
Fast amortization through dramatic savings on expensive support time.
ROI Transparency: How does this add up?
With 5 FTEs in support (~€250,000 personnel costs) and a 30% workload reduction via Level 1 AI, you free up time worth €75,000 per year. This is contrasted with pilot costs (approx. €20,000) and ongoing API costs (approx. €2,000). Result: An ROI of ~240% in the first year.
Your specialists finally use this freed-up time to solve real problems (Level 2/3), work on projects, and manage architecture.
Model calculations based on medium enterprise environments. Individual savings vary depending on the setup.
The Solution
The Process: From Problem to Resolved Ticket
The AI integrates seamlessly into your existing ITSM infrastructure as an "intelligent filter" before human support.
Intelligent Intake (Multi-Channel)
The user reports a problem via email, Teams chat, or a self-service portal. The AI reads the text and analyzes attachments (e.g., error message screenshots).
Extraction & History Match
The system retrieves background information: Who is the user? Which devices do they have? Are there known global disruptions ("Major Incidents")?
Resolution or Triage (RAG / Agent)
If the problem can be resolved (e.g., "Reconnect printer M-12"), the AI immediately provides instructions from the knowledge base (RAG) or executes actions via API.
Seamless Handover (L2/L3)
For complex cases, the AI creates a correctly categorized ticket, summarizes the problem, and assigns it to the specialist queue.
System Integrations
Typical IT Infrastructure Setup
We don't replace ticket systems; we make your existing tools smarter.
Connecting to ITSM Tools
Integration into systems like Jira Service Management, ServiceNow, Matrix42, or Zendesk via secure REST APIs and webhooks.
RAG (Retrieval-Augmented Generation)
The AI searches your internal IT wiki articles, Confluence pages, and resolved tickets to generate correct solution paths (without hallucinations).
Active Directory / Entra ID Identity
Secure user authentication to provide context-based answers (e.g., "Which servers do I have access to?") in compliance with data privacy regulations.
Channel Integrations
Instead of forcing users into portal forms, the support agent operates exactly where users are: in MS Teams, Slack, or via classic email inbox monitoring.
Possible Infrastructure
Security and data privacy are the top priorities here. Data does not flow back into public models.
Frequently Asked Questions
Implementation Details
Are our IT data and logs secure?
Absolutely. This concept is typically implemented on "Enterprise Grade" platforms like the Microsoft Azure Cloud (Europe regions). Ticket data is not used to train public models ("Zero Data Retention").
What happens if the AI guesses wrong?
Through RAG technology, the AI agent works strictly based on your verified IT articles. If the AI doesn't know the answer or an article is missing, it transparently routes it to a human instead of hallucinating.
How long does a start or pilot project take?
Based on experience, a typical Proof-of-Concept (integration into your ITSM + Chatbot frontend for a selected test group) takes about 3 to 6 weeks.
Does the AI replace the IT administrator?
No. It takes away the L1 "busy work". System administrators can finally return to infrastructure projects, architecture, security, and L3 level topics without drowning in daily operations.
AI Automation for processes.
Work ExampleHow a pilot report might look.
Prices & PackagesPilot implementations transparently calculated.
Vertiefung
Ausgangslage, Wirtschaftlichkeit und Umsetzung.
Damit ein Use Case nicht nur interessant klingt, muss er in Prozessvolumen, Datenlage, Risiko und messbarer Wirkung übersetzt werden.
Konkrete Ausgangslage
Der Use Case passt, wenn L1-Tickets, Passwortthemen, Softwarezugänge, Standardfehler und Routing-Fragen einen großen Teil des IT-Supports blockieren.
ROI-Logik
Der ROI ergibt sich aus reduzierter Erstbearbeitungszeit, höherer Self-Service-Quote und weniger Fehlrouting. Schon kleine Verbesserungen wirken stark, wenn das Ticketvolumen hoch ist.
Umsetzung in 4 Schritten
- Ticketkategorien und historische Lösungswege analysieren.
- L1-Wissensartikel und Servicekatalog strukturieren.
- Triage-Agent mit sicheren Eskalationsregeln testen.
- MTTR, Erstlösungsquote und Routing-Qualität messen.
Entscheidungsfragen vor dem Pilot
- Welche Ticketarten sind wirklich standardisiert?
- Wie wird Zugriff auf sensible Systeme abgesichert?
- Welche Fälle bleiben konsequent beim IT-Team?
ROI-Beispiel
Beispielrechnung: L1-Ticket-Triage
Der rechnerische Jahresaufwand liegt bei ca. 118.800 EUR. Eine 30-Prozent-Entlastung entspricht ca. 35.600 EUR Potenzial pro Jahr.
Wichtig ist, nur gut dokumentierte L1-Fälle zu automatisieren und kritische Berechtigungs- oder Sicherheitsfälle sauber zu eskalieren.Annahmen
- 900 L1-Tickets pro Monat
- 12 Minuten Erstbearbeitung und Routing
- 55 EUR interne IT-Vollkosten pro Stunde
- 30 Prozent Entlastung durch Self-Service und Triage