IT service and operations teams increasingly benefit from the enrichment of their work systems with modern technology. Artificial intelligence (AI) reduces toil, identifies important information, summarizes information, and makes recommendations, enabling IT organizations to focus their critical skills more effectively.
However, the data collected during this work is frequently underutilized or overlooked once its immediate purpose is complete. Transactional data records used by IT management tools have two distinct phases of value. First, a data object is created to describe and categorize the scenario and to manage a resolution to completion. Some familiar examples of the “tickets” created in such scenarios are detected infrastructure events, incidents, and change requests.
Once the work is completed, there is a second, extended value phase. The ticket data stored about the work becomes a small component of a large, aggregated set of information. Over weeks and months, organizations accumulate thousands or even millions of these transactional records. The result is a data set with vast potential to provide valuable information about the people, processes, and systems involved in day-to-day activities. Collectively, this information is a rich resource for organizational improvement, enabling intelligent decisions, informed strategies, and accurate answers to inquiries.
The data analysis bottleneck
Unlocking the value within this data has long been a specialist skill, requiring dedicated reporting tools and a knowledge of complicated database structures. This challenge creates a bottleneck in many organizations, with the demand for fast information often exceeding the capacity of reporting teams to provide it.
Simply increasing the number of people dedicated to data analysis does not usually solve the problem. Many organizations have experienced an induced demand effect, with the visible benefits of effective data analytics leading more people to want to consume those analytical services. The more successful reporting teams are in delivering valuable insights, the more the demand increases on the time and skills of reporting teams!
Unlocking and extending the value in IT data
However, just as AI has enabled optimization of the active phase of a data record’s life, the technology is now transforming this secondary phase.
As one of the agentic AI assistants in the BMC Helix platform, BMC HelixGPT Insight Finder, enables any consumer of operational data to gain deep and broad insights from large datasets simply by conversing with the assistant. This practical use of generative AI enables employees to fulfill their own data needs, rather than joining the back of the work queue of a specialist data analysis team.
BMC HelixGPT Insight Finder allows consumers simply to express the information they need in plain language. The fine-tuned agentic AI assistant translates requests into the data queries required to retrieve appropriate information, then presents the information to the user via visualizations. This AI assistant easily combines multiple data sources into structured insights, reducing the need for complex query building.
The conversation can also continue beyond the first response. On receipt of the initial presentation of data, the user can ask for deeper analysis, clarifications, or secondary queries. These secondary insights are gained instantly without needing to join the back of the queue to access the reporting team once more.
The transformative value of AI
The skills of expert data analysis teams are too valuable to be used in repetitive reporting work. As enterprises and large organizations continue seeking ways to increase the value of their data through new technologies, generative AI is taking center stage. Providing enterprise teams with an AI-driven facility to fulfill most reporting needs liberates expert data analysts from routine request fulfillment. Solutions like the BMC HelixGPT Insight Finder make everyone in the enterprise a data expert and enable enterprises to deliver differentiating and transformational value from the vast storage of data collected daily.
Visit here to discover how agentic AI can transform your enterprise data into a proactive force that improves business results in your organization or contact BMC.
