Service integration layer of an ADM operating model
The service integration layer acts as a critical bridge between business requirements and technical execution, orchestrating interactions across IT services. The integration of AI into this layer brings changes in service management and service governance.
Service management
The following table provides the current state and a corresponding future state with generative AI for key issues related to service management.
Current state |
Future state with generative AI |
|---|---|
Self-help using internal knowledge base search and manually created standard operating procedures (SOPs) |
AI-powered self-service agents that generate dynamic SOPs using an enterprise repository |
Self-service tools for standard service requests such as access to data and software installation |
Automated service requests using AI-powered agent workflows |
Human agents responding to user inquiries |
AI-powered chatbots for instant, context-aware responses |
Limited language and communication channel options |
Multi-language, multi-channel support across chat, voice, SMS, and virtual assistants |
Reactive issue management |
AI-powered service desk that predicts common issues and proactively suggests solutions to users before they encounter problems |
Service governance
The following table provides the current state and a corresponding future state with generative AI for key issues related to service governance.
Current state |
Future state with generative AI |
|---|---|
Reactive approach to service level agreement (SLA) management |
Predictive service level management to forecast potential SLA breaches |
Manual availability management |
AI-enhanced availability management for continuous service delivery |
Static capacity and performance management |
Intelligent capacity and performance management for optimized resource allocation |
Manual service validation and testing |
Automated service validation and testing |
Periodic configuration management database (CMDB) updates |
AI-driven configuration management for real-time CMDB updates |
The previous examples of future state with generative AI for the business layer and the service integration layer are just the beginning. As AI technologies evolve, expect more innovative solutions to emerge. These advancements can help to enhance proactive, efficient, and automated IT service management and governance.
Use these examples as a starting point for your organization's approach to generative AI transformation. Consider these examples along with your ADM operating model changes. Continuously evaluate new AI applications that align with your organization's needs and goals. This forward-thinking approach can help to keep you at the forefront of IT service management (ITSM) innovation.
