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04-04-2024 08:55 PM
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04-04-2024 09:58 PM
Generative AI can be leveraged in ServiceNow for various use cases, enhancing automation, decision-making, and user experience.
Natural Language Processing (NLP):
- Virtual Agents and Chatbots: Generative AI can power virtual agents and chatbots within ServiceNow, enabling natural language understanding and generation for interactions such as IT service requests, HR inquiries, and more.
- Auto-suggest and Auto-complete: Implementing generative models can enhance auto-suggestion and auto-completion features in ServiceNow's forms and search functionalities, improving user productivity and experience.
Content Generation:
- Knowledge Management: Generative models can assist in creating and updating knowledge base articles, automating the generation of documentation, FAQs, and other informational content within ServiceNow.
- Automated Responses: Utilizing generative AI, ServiceNow can automatically generate responses to common user inquiries, service requests, or incidents, reducing response times and workload for support staff.
Data Augmentation:
- Data Quality Improvement: Generative models can be used to generate synthetic data for testing, training, and augmenting real-world datasets in ServiceNow, improving the quality and diversity of data available for analytics and machine learning applications.
- Anomaly Detection: By generating synthetic data, ServiceNow can create realistic scenarios for testing and training anomaly detection algorithms, helping organizations identify and respond to unusual patterns or behaviors.
Automation and Process Optimization:
- Workflow Automation: Generative AI can automate repetitive tasks and processes in ServiceNow by generating scripts, workflows, and business rules based on historical data and user-defined criteria, streamlining operations and reducing manual effort.
- Predictive Maintenance: Using generative models, ServiceNow can predict equipment failures, maintenance needs, and resource utilization patterns, enabling proactive maintenance scheduling and optimization of asset management processes.
Personalization and Recommendations:
- Service Catalog Personalization: Generative AI can analyze user preferences, historical data, and contextual information to personalize the ServiceNow service catalog, recommending relevant services, products, or resources to users based on their profiles and needs.
- ITSM Incident Prioritization: Generative models can assist in prioritizing IT service incidents and requests by analyzing historical incident data, severity levels, and business impact, helping organizations allocate resources more effectively and improve incident resolution times.
Please Mark ✅Correct if this solves your query and also mark 👍Helpful if you find my response worthy based on the impact.
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04-04-2024 09:44 PM
Hi @Snehal13 use cases are
- Customer experience.
- Empower the whole company to serve the customer.
- Technology excellence.
- Automate and optimize technology service operations.
- Employee experience.
- Boost employee productivity and engagement.
- Operating excellence.
- Drive efficiencies through global business services.
For more check below link
https://www.servicenow.com/community/in-other-news/servicenow-and-generative-ai/ba-p/2579347
https://medium.com/@BhagabanTechnical/generative-ai-use-cases-with-servicenow-df01c7e5c2fd
https://www.servicenow.com/blogs/2023/unleash-possibilities-generative-ai.html
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04-04-2024 09:55 PM
Hi @Snehal13
Some Use Cases of Generative Ai are:
-Automated Incident Response and Resolution
-Enhanced Virtual Agent Conversations
-Predictive Analytics and Trend Analysis
-Customized Knowledge Base Articles
-Optimized Workflow and Process Automation
-Custom Application Development
-Security Incident Response
-HR and Employee Experience
-Customer Service and Engagement
For More Details: --> https://www.servicenow.com/now-platform/generative-ai.html?state=seamless
Note: Please Mark this Helpful and Accepted Solution. If this Helps you to understand. This will help both the community and me..
- Keep Learning
Thanks & Regards
Deepak Sharma
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04-04-2024 09:58 PM
Generative AI can be leveraged in ServiceNow for various use cases, enhancing automation, decision-making, and user experience.
Natural Language Processing (NLP):
- Virtual Agents and Chatbots: Generative AI can power virtual agents and chatbots within ServiceNow, enabling natural language understanding and generation for interactions such as IT service requests, HR inquiries, and more.
- Auto-suggest and Auto-complete: Implementing generative models can enhance auto-suggestion and auto-completion features in ServiceNow's forms and search functionalities, improving user productivity and experience.
Content Generation:
- Knowledge Management: Generative models can assist in creating and updating knowledge base articles, automating the generation of documentation, FAQs, and other informational content within ServiceNow.
- Automated Responses: Utilizing generative AI, ServiceNow can automatically generate responses to common user inquiries, service requests, or incidents, reducing response times and workload for support staff.
Data Augmentation:
- Data Quality Improvement: Generative models can be used to generate synthetic data for testing, training, and augmenting real-world datasets in ServiceNow, improving the quality and diversity of data available for analytics and machine learning applications.
- Anomaly Detection: By generating synthetic data, ServiceNow can create realistic scenarios for testing and training anomaly detection algorithms, helping organizations identify and respond to unusual patterns or behaviors.
Automation and Process Optimization:
- Workflow Automation: Generative AI can automate repetitive tasks and processes in ServiceNow by generating scripts, workflows, and business rules based on historical data and user-defined criteria, streamlining operations and reducing manual effort.
- Predictive Maintenance: Using generative models, ServiceNow can predict equipment failures, maintenance needs, and resource utilization patterns, enabling proactive maintenance scheduling and optimization of asset management processes.
Personalization and Recommendations:
- Service Catalog Personalization: Generative AI can analyze user preferences, historical data, and contextual information to personalize the ServiceNow service catalog, recommending relevant services, products, or resources to users based on their profiles and needs.
- ITSM Incident Prioritization: Generative models can assist in prioritizing IT service incidents and requests by analyzing historical incident data, severity levels, and business impact, helping organizations allocate resources more effectively and improve incident resolution times.
Please Mark ✅Correct if this solves your query and also mark 👍Helpful if you find my response worthy based on the impact.
Thanks
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04-05-2024 01:00 AM
Hi @Snehal13
You can do the Gen Ai / Non Assit training on Now learning , that wil give you more clarity along with mentioned by @Deepak Shaerma @Maddysunil @Harish Bainsla
If my response proves useful, please indicate its helpfulness by selecting " Accept as Solution" and " Helpful." This action benefits both the community and me.
Regards
Dr. Atul G. - Learn N Grow Together
ServiceNow Techno - Functional Trainer
LinkedIn: https://www.linkedin.com/in/dratulgrover
YouTube: https://www.youtube.com/@LearnNGrowTogetherwithAtulG
Topmate: https://topmate.io/atul_grover_lng [ Connect for 1-1 Session]
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