Limitless Possibilities
Generative artificial intelligence (GenAI) is ready to ignite a surge of innovation with far-reaching effects — especially for IT operations and technical support. From streamlining and automating tasks to increasing productivity and reducing costs, the possibilities are limitless.
GenAI Capabilities
Among the many capabilities of generative AI are:
- Learning from input data, such as text, software code, product designs, and images
- Creating new, customized content data like video, music, speech, text, software code, and product designs from the amalgamation of inputs
- Delivering customized and personalized content on demand and at scale
- Helping to automate tasks without human intervention
GenAI allows issues to be solved faster and provides an improved user experience. Knowledgeable and contextually sensitive responses are possible in chat sessions. Chat can also be used for better documentation or for resolving more technical issues by escalating to Level 3 agents. Consequently, agents become capable sooner, and Level 2 and Level 3 involvement in issues is reduced. Moreover, escalation to end-user support can enhance responses with transitions, animations, and motion.
IT Support Team Benefits
Generative artificial intelligence (GenAI) is ready to ignite a surge of innovation with far-reaching effects — especially for IT support services.
The user experience with IT support services will dramatically improve by having great conversations with intelligent, understanding, and domain-specific, customer service chatbots. When the customer service chatbot cannot meet the user needs, the IT support engineers will be able to solve for the users faster and provide a better user experience.
The IT support engineers will be faster and more productive with the ability to have natural language conversations with an intelligent assistant while doing root cause analysis and resolving day-to-day support issues within their IT environment. The GenAI support assistant will be able to summarize logs and events from multiple places and recommend fixes, bringing in more people and data as directed by the IT support engineer.
IT support automation tools and scripts will be easier to deploy and maintain with the assistance of an intelligent agent who has unified knowledge of existing automation and the ability to generate new automation code.
GenAI’s capabilities provide numerous benefits for IT support teams, such as:
- Resolving more — and more complex — issues quickly through chat
- Reducing manual searches or the need to scour the internet for clues to fix an issue
- Recommending responses to issues and triggering automation code
- Streamlining documentation updates
- Documenting issue resolution immediately after ingestion
- Generating code and design suggestions for additional automation.
Current IT Support
The graphic below illustrates an old-fashioned IT support service:
On the left are the different input types with different colors representing different data and new knowledge gained from the data and IT support services on an ongoing basis. In this model, different types of users (IT end users, IT operations, IT technical support engineers) are constantly connecting the red, blue, and green dots to solve IT support incidents and fulfil IT service requests. There are also many support tools, policies, and procedures in place today to facilitate this process.
Enter machine learning (ML) and generative AI. This is a very simple representation of the new IT support world — a vision of an IT support world where ML and the use of large language models and generative AI combine all the documentation and create links among all the colors, producing new content relevant to the business and technology as needed. The ML model parses domain-specific data and tokenizes it. The new IT support engineer will be interacting with and updating the ML model rather than toggling between different tools, logs, and events to solve IT support incidents and fulfill IT service requests. A key part of this model is to configure and update the ITSM and IT automation tools with the assistance of the ML model on an ongoing basis, thereby driving up the adoption of automation.
Training Model
Production IT Support Assistant (PISA)
The new IT support organization will include a production IT support assistant (PISA). PISA offers several advantages for end users, operations/help desk, and the technical team, such as:
End-User Benefits:
- End-user chats provide guidance in technical and business context.
- Fewer calls are made to the help desk.
- The help desk is augmented by a more customized chat as the copilot.
- Automation is available to correct issues from chat with minimal intervention (if any).
Operations/Help Desk Benefits:
- More users can be supported without increasing staff.
- Staff can be trained faster, and the ability to close tickets quickly is increased.
- Ticket documentation is enhanced.
- Ticket generation, escalation, management, closure, and feedback collection can be automated.
Technical Team Benefits:
- Fewer escalations to interrupt work
- More availability for business issues and projects
- Faster delivery using chat as a copilot
- Runbook builds/updates
- More complex issues automated
“From the very beginning, Windsor Group’s team of experts was not just knowledgeable but also incredibly patient. They took the time to understand my project requirements and my limited understanding of generative AI. They provided me with comprehensive guidance on how to get started, breaking down complex concepts into understandable terms.”
Technology company CIO
Getting Started
Starting a pilot project in the IT support area gives IT leaders a chance to understand the risks, value, and adoption of machine learning and generative AI before deploying large-scale projects into the business units.
As noted above, there are several high-value use cases in the IT support area. IT support is a set of commodity support functions (help desk/field services, operations, technical support) that are well defined and well understood, with a large data set of tools, technical data, instructions, logs, and events. This is a great place to leverage machine learning and generative AI.
To get started with a pilot project, first define the expected outcomes. Is the objective to improve user experience, increase support team productivity, accelerate new products/services, and/or reduce costs? How will you measure the outcomes? Other questions to be answered as part of the pilot project planning process include:
- What is your current landscape of IT support service and cost, IT support tools, and vendors?
- How do machine learning/generative AI and the pilot project fit within your current state and future direction?
- What is the technical feasibility of implementing the pilot project? What technologies are required? What are the options? Will you see the results in 3-6 months?
- What skill sets are required to plan and execute the pilot project? What partners are available to assist? What is the role of your existing staff/vendors?
Why Windsor Group?
Windsor Group helps companies incorporate GenAI into their IT support strategy to create an operational structure with the flexibility and agility to adapt to the ever-changing marketplace. By empowering organizations to shift daily management and responsibilities of nonstrategic business initiatives to external service providers, Windsor Group enables companies to significantly reduce their IT costs while establishing a more efficient operation — one that positions them for a future of stability and success.
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