NovelVista logo

Certified Generative AI in ITSM Training Course

Discover How Generative AI Strengthens Industrial Sectors with NovelVista: The Top-Rated Training Provider for More Than 1,000 Global Companies.

  • Industry Expert Trainers
  • Online learning session
  • Interactive Sessions
  • Exam fee included
View Schedule
📞18002122003
Google4.9 Ratings onReviews
9000+ Professionals Enrolled

Certified Generative AI in ITSM Program Overview

The Certified Generative AI in ITSM is designed for professionals with all the skills required to integrate AI technologies into IT Service Management Processes that transform traditional service operations. Our certification focuses on how Artificial Intelligence like GANs, Variational Autoencoders and Recurrent Neural Networks can successfully automate and optimize the different aspects of ITSM. It includes incident management, ticket routing and predictive maintenance.

This certification covers real-world applications such as anomaly detection, automated service desk solutions and resource forecasting that aim to enhance efficiency, decrease human error and improve service delivery. By leveraging Artificial Intelligence for proactive issue resolution, IT systems will be more adaptive and resilient. Our certification is ideal for IT managers, service desk professionals and AI specialists who want to stay ahead in the evolving field of ITSM through cutting-edge tools.

Accredited By
Accreditation Logo

What You Will Get?

Blended Digital Learning curated by SMEs

Every Friday Live Mentor Session (7PM to 9PM IST)

Global Certification Exam with 2 Attempts

Learning Resources: Case studies, templates, and the BOK

Capstone project

AI-based Interview Practice Exam

Learning Outcome

After the completion of the course, the participants would be able to:

Develop AI-driven systems to automatically route service tickets based on context..
Use AI modes to predict system failures.
Use AI-powered chatbots and virtual assistance to handle routine IT support tasks.
Practice the AI models to analyse the event logs and training ITSM.
Deploy AI-powered chatbots and virtual assistants to handle routine IT support tasks.

Why Our Data Science Program Stands Out

Hands-on Training

  • ✓Real datasets and projects.
  • ✓Industry-aligned curriculum.

Expert Mentorship

  • ✓Learn from industry professionals.
  • ✓Career-focused guidance.

Industry Projects

  • ✓Solve real-world business problems.
  • ✓Build a job-ready portfolio.

Course Curriculum

Introduction to Generative AI+

  • Fundamentals of Generative AI
  • Types of Generative AI models
  • Use cases of Generative AI in various industries

Overview of IT Service Management (ITSM)+

  • Key ITSM processes
  • ITSM best practices and frameworks
  • Challenges and opportunities in ITSM

Generative AI in Core ITSM Processes+

Service Desk:


  1. Gen AI-powered chatbots for 24/7 support and self-service
  2. Intelligent ticket routing and prioritization
  3. Automated knowledge base article generation and Curation
  4. Automate routine tasks, such as ticket updates and notifications
  5. Analyze user sentiment in tickets and conversations to identify potential escalations
  6. Provide personalized support and recommendations to improve user satisfaction


Incident Management:


  1. Employ Gen AI to accurately classify and categorize incidents based on their descriptions
  2. Identify patterns in incident data to automatically prioritize incidents based on their impact and urgency
  3. Leverage Gen AI to automatically suggest relevant knowledge articles or solutions
  4. Deploy Gen AI-powered chatbots to provide self-service support to end-users
  5. Leverage Gen AI to predict potential system failures or performance issues based on historical data.
  6. Integrate with collaboration platforms to facilitate seamless communication and knowledge-sharing


Problem Management:


  1. Analyze historical incident and problem data to uncover recurring patterns and trends
  2. Generate potential root cause hypotheses based on analyzed data and knowledge
  3. Generate temporary workarounds to mitigate the impact of problems
  4. Automate the creation of change requests to address the root cause of problems


Change Management:


  1. Simulate the impact of a change on the IT environment to identify potential conflicts or issues before implementation
  2. Generate standardized change request templates based on the type of change
  3. Automatically assess the potential impact of a change on other systems and services
  4. Analyze failed changes to identify patterns and root causes
  5. Leverage machine learning models to predict the likelihood of a change being successful
  6. Provide recommendations to change implementers based on historical data and best practices


Service Request Management:


  1. Utilize NLP to understand and interpret user requests submitted in natural language
  2. Identify the underlying intent of user requests
  3. Automate routine request fulfillment tasks
  4. Optimize resource allocation based on predicted demand and workload
  5. Generate personalized responses and updates to users


Configuration Management:


  1. Gen AI-driven configuration item discovery, dependency mapping, and real-time updates
  2. Automated configuration baseline management, change tracking, and version control
  3. Predictive configuration drift analysis including drift detection, impact analysis, and proactive remediation
  4. Gen AI-powered CMDB querying and reporting


IT Asset Management:


  1. Gen AI-powered asset discovery, asset classification, and inventory updates
  2. Predictive asset maintenance and lifecycle optimization & management
  3. Automated asset compliance and security audits for license management, vulnerability assessment, and policy enforcement
  4. Gen AI-driven prediction for future asset needs based on historical usage patterns and business requirements


Release Management:


  1. Gen AI-assisted release planning and scheduling including dependency analysis, resource allocation, and risk assessment
  2. Automate the deployment of software releases across different environments
  3. Implement automated rollback procedures in case of issues or failures during deployment
  4. Integrate AI with CI/CD pipelines to enable faster and more frequent releases
  5. Predictive release risk assessment and impact analysis


Deployment Management:


  1. Leverage GenAI to automate deployment workflows, identify and manage dependencies, and integrate with configuration management
  2. Real-time deployment monitoring and troubleshooting
  3. Analyze failed deployments, risk evaluations, and deployment optimization

Generative AI in Supporting ITSM Processes+

Service Level Management:


  1. Gen AI-driven service level agreement (SLA) monitoring, automated reporting, and data visualization
  2. Predictive SLA breach analysis and prevention
  3. AI-powered performance analysis, resource optimization, and SLA negotiation support


Capacity Management:


  1. Leverage Gen AI to analyze historical usage patterns, business trends, and other relevant factors
  2. Build and simulate capacity models to predict the impact of different scenarios
  3. Predictive capacity bottleneck analysis and remediation
  4. Gen AI-powered capacity optimization recommendations


Availability Management:


  1. Gen AI-driven availability monitoring for collecting and analyzing potential availability issues and reporting
  2. Utilizing ML models for anomaly detection and generating timely alerts and notifications to relevant stakeholders
  3. Gen AI-powered recommended adjustments to allocate resources and optimize infrastructure design for availability and performance


Demand Management:


  1. Gen AI-driven demand forecasting and analysis to accurately predict future demand for IT services
  2. Predictive demand pattern identification and management to prevent service disruptions, optimize resource utilization, and improve user satisfaction
  3. AI-powered demand optimization recommendations


Information Security Management:


  1. Gen AI-powered threat detection and incident response
  2. Automated security policy enforcement and compliance checks
  3. Predictive security risk assessment and vulnerability management
  4. Gen AI-driven security awareness and training


Service Continuity Management:


  1. Utilize Gen AI to analyze vast amounts of data from various sources to identify potential risks and their impact on business operations
  2. Create and simulate various disruption scenarios using Gen AI
  3. Automated disaster recovery planning and testing
  4. Automate communication with stakeholders during a crisis


Organizational Change Management:


  1. Gen AI-powered change impact analysis to assess potential reactions and concerns
  2. Generate personalized communication materials tailored to specific stakeholder groups
  3. Develop Gen AI-powered surveys and assessments to gauge readiness for change
  4. Generate personalized training content and recommendations based on learning styles and knowledge gaps
  5. Create interactive and engaging training experiences using GenAI-powered gamification and simulations


Stakeholder Management:


  1. Gen AI-driven stakeholder sentiment analysis to identify potential issues and concerns
  2. Generate personalized recommendations for stakeholder engagement
  3. Automated relationship and supplier management workflows and communication
  4. Predictive risk assessment and mitigation


Continual Service Improvement:


  1. Automatically discover and map ITSM processes based on logs, data, and user interactions
  2. Analyze process flows to identify bottlenecks, inefficiencies, and areas for improvement
  3. Track and analyze key performance indicators (KPIs) across various ITSM processes
  4. Simulate the potential impact of proposed improvements on service performance, user experience, and other key metrics
  5. Suggest improvement actions based on industry best practices, historical data, and AI-driven insights.

Agile, DevOps, and SRE in ITSM with Generative AI+

Agile:


  1. Applying Agile principles to ITSM processes
  2. Leveraging Gen AI for process backlog prioritization and sprint planning thereby facilitating continual improvement


DevOps:


  1. Integrating development, operations, and security with AI
  2. Gen AI-powered continuous integration and continuous delivery (CI/CD) pipelines


SRE:


  1. Implementing SRE principles for service reliability and resilience
  2. Leveraging Gen AI for error budgeting and incident response automation

Implementing Generative AI in ITSM:+

  • Identifying suitable Generative AI use cases and defining business objectives
  • Data preparation and model training strategies
  • Integrating Gen AI solutions with existing ITSM tools and platforms
  • Measuring the impact and ROI of Generative AI implementations

Challenges and Ethical Considerations+

  • Data privacy and security concerns
  • Bias in Generative AI models and the need for transparency
  • Impact on IT jobs and the need for up-skilling
  • Ethical considerations in using Generative AI

Future Trends and Advancements+

  • Emerging trends and innovations in Generative AI
  • The evolving role of ITSM professionals in a Generative AI-powered environment
  • Integrating Gen AI solutions with existing ITSM tools and platforms
  • Measuring the impact and ROI of Generative AI implementations