Gartner® recently released their 2025 Market Guide for Event Intelligence Solutions, and BigPanda was thrilled to be named as a Representative Vendor in this report.
“Event intelligence solutions (EISs) apply AI to augment, accelerate, and automate responses to signals or events detected from digital services. Gartner states, “These solutions are designed to process event streams into actionable insights and enable proactive responses that reduce toil and improve performance and availability.”
EISs have the potential to significantly improve IT event management, offering insights for faster and more accurate decision-making, optimized operations, and better business outcomes. However, achieving these outcomes requires more than technology. Your organization needs to put the data, processes, people, and strategic plans in place to ensure these solutions deliver value and results.
What are event intelligence solutions, and how can your organization maximize their value
Since Gartner coined the term AIOps in 2017, it has become almost ubiquitous, catching the imagination of practitioners, vendors, and their marketing teams alike. However, its definition has become increasingly blurred, with associated applicability and use cases ever more varied. AI’s increasing prominence makes classifying products and tools strictly based on the inclusion of AI confusing rather than helpful.
The change in nomenclature also provides space within the IT operations landscape for AI-based tools and capabilities that do not process events and supports the creation of additional such markets where appropriate.
“The renaming of this market from AIOps platforms to EIS serves to direct focus to the intended domain and set of use cases,” according to Gartner. “Namely, the application of AI, ML, and advanced analytics to cross-domain events from monitoring and observability tools to augment, accelerate, and ultimately automate response.”
At BigPanda, we believe this shift in terminology validates positive market change. Regardless of the name, the value that the technology delivers—whether you call it AIOps or event-intelligence solutions—remains the same or is improving.
However, it is critical that I&O leaders separate the hype of AI and focus on setting up their operations to ensure they get tangible value from these investments. To that end, here’s our perspective on the market recommendations that Gartner has stated in this report for I&0 leaders to successfully deploy and maximize the value EISs.
Recommendation 1: Focus on getting value from AI, not just implementation
A year ago, generative AI was relatively new territory for ITOps, with CIOs, and CTOs still racing to define and understand these technologies’ potential use cases and impacts. Since then, AI adoption for IT operations has accelerated dramatically.
However, this race to adopt and integrate generative AI into your IT operations comes with risks. There is a tremendous amount of hype surrounding AI’s potential to transform ITOps. And amid the pressure to innovate, companies can easily invest in these technologies without a clear path to value.
“AI should not be seen as a cure-all, but rather as a means to an end,” Gartner states. “When evaluating the application of AI across IT operations, I&O leaders must focus on specific pain points and use cases that drive the value proposition specific to their organization.”1
To successfully demonstrate the ROI of event intelligence solutions, I&O leaders must clearly understand the pain points they want these platforms to solve and how to measure their tangible benefits. At BigPanda, we have a clearly defined and proven path to value from AIOps.
For example, during initial adoption, our customers typically focus on reducing the overwhelming number of alerts that their applications and infrastructure create.
Reducing alert noise can significantly improve incident management by allowing teams to focus on critical issues instead of being overwhelmed by false positives and irrelevant alerts. BigPanda customers experience rapid efficiency gains, often reducing alert noise by 80% within eight weeks of implementation.2 In some cases, this exceeds 90% or more over time.
Identifying specific desired business outcomes upfront and tailoring your deployment of AI into your operations to achieve them ensures that your organization achieves tangible results. Gamma, a leading European supplier of communication services, faced alert-management challenges from its email-alerting system. Gamma could review only 3% of its alerts, as they relied on inefficient manual identification and correlation processes. By adopting BigPanda AIOps, Gamma was able to reduce alert noise by 93%.
“Within two weeks, we had a substantial reduction in alerts — and better alerts. An instant bang for the buck.”
Dan Bartram
Head of Automation and Monitoring
Gamma
Recommendation 2: Clearly understand your data requirements and process maturity
According to Gartner, the messaging from EIS vendors typically focuses on the benefits of successful implementation, with little regard for the prerequisites required to achieve these results.
To ensure success, I&O leaders should carefully evaluate the data quality and process maturity prerequisites required to achieve their desired business outcomes.
“For example, the degree to which a solution relies on a mature CMDB or integration to third-party orchestration solutions varies across vendors,” Gartner states.
A well-maintained CMDB can provide valuable insights for managing infrastructure, resolving incidents, and optimizing IT operations. However, maintaining an up-to-date CMDB is complex and resource-intensive. It requires continuous updates to ensure an accurate configuration. Without proper governance and management processes, a CMDB can quickly become outdated, inconsistent, or filled with duplicates, diminishing its value and effectiveness for event and incident management.
“Siloed information makes it difficult to centralize data and identify important alerts, which creates inefficiencies and extends incident resolution times,” said C Beers, Principal Solutions Architect at BigPanda. “GenAI can help democratize access to operational knowledge so your responders know what’s happening and can act quickly.”
BigPanda helps overcome the limitations of and modernize CMDBs. Our platform improves the accuracy of CMDBs by automatically identifying and writing back missing configuration items (CIs) referenced in alerts but not cataloged in the CMDB. In addition, our platform applies AI to instantly correlate and enrich alerts with valuable context, including topology and CMDB data. BigPanda customer Autodesk saw a 69% reduction in incidents, partially due to our platform’s alert enrichment capabilities.
Recommendation 3: Evaluate tools across your IT ecosystem
An EIS functions within a broader IT operations management (ITOM) ecosystem, which includes observability and monitoring, CMDB, IT Service Management (ITSM), and automation tools. Seamless integration between these components is crucial for successful deployment. Given the interdependencies of these tools, I&O teams should assess EIS solutions across the entire IT ecosystem. This evaluation should focus on integrating the EIS with the existing IT operations portfolio, optimizing workflows, and consolidating redundant tools.
For example, integrating platforms like BigPanda with ServiceNow can enhance ITSM capabilities. When properly deployed, an EIS allows IT teams to proactively detect issues by transforming IT noise into relevant insights using context. Every operator, regardless of where they’re working, gets the context and expertise they need to get ahead of evolving incidents. They can triage incidents quickly and maximize productivity, improving the value of ITSM platforms and observability tools.
Recommendation 4: Mandate organizational change
Implementing an EIS will impact existing processes, roles, and organizational culture. When assessing the value drivers and use cases of an EIS, organizations must consider the process changes required. Conservative organizations, particularly those in regulated industries, should adopt a pragmatic approach to change, focusing on incremental optimization to build trust and manage risk effectively. The goal is to move towards a more integrated, data-driven approach to incident management and service delivery, with a focus on proactive problem-solving and automation.
“In IT, new technology developments like generative AI have been adopted cautiously for fear of causing too much disruption,” said Jason Walker, Chief Innovation Officer at BigPanda. “But technology revolutions of this magnitude eliminate the organizations that are too entrenched in old methodologies, creating space and opportunity for those that can quickly adapt and accelerate innovation.”
Organizations can leverage the rapid development of GenAI to transform their existing operational models, drive operational improvements, and gain a competitive edge. However, achieving these results requires that I&O leaders mandate organizational change, and accept that innovation comes with risk and potential disruption. There are a number of teams that are required to make these changes happen, and getting those teams to align and collaborate can be difficult.
“I spend my days in the field with our enterprise clients, talking to all the teams that are involved in these solutions, and I’ve found that you need to provide extreme specificity,” said C Beers. “If you have a platform that shows your teams exactly who they need to talk to, why they need to be discussing the issue, and how that they could go about solving that issue, it’s a game changer.”
To improve incident management and service delivery, a unified platform for collaboration across observability, IT operations, and service management teams is essential. It’s critical to deploy a data-driven approach to eliminate silos between these teams and provide them with actionable insights to facilitate collaboration and continuous operational improvement.
“It’s really hard when you’re trying to change technology and processes across different teams who have done things the same way for 20 years,” said C Beers. “BigPanda Unified Analytics helps break down information silos, identify gaps, and give teams data-driven insights so they can collaborate more efficiently and resolve incidents faster.”
Learn more about event intelligence solutions
Event Intelligence Solutions have the potential to significantly enhance, optimize, accelerate, and automate IT operations response. BigPanda offers a complete EIS, combining cross-domain event ingestion, advanced analytics, event correlation and enrichment, and GenAI capabilities to accelerate remediation into a unified AIOps platform. BigPanda offers:
✅ AI-Powered Event Management to increase the speed and productivity of IT Operations teams.
✅ AI-powered event correlation and enrichment to improve anomaly detection and reduce noise.
✅ BigPanda Biggy AI, which uses GenAI capabilities to accelerate incident investigation by surfacing highly relevant insights from fragmented data.
✅ GenAI-powered natural language incident summaries to facilitate fast, accurate incident analysis and decision-making.
✅ Automated workflows and processes to accelerate incident investigation and resolution.
✅ Advanced analytics and dashboards to recognize, cluster, predict, and prevent recurring incidents.
Get your free copy of the research to learn more about separating the hype of AIOps from the achievable value of optimized operations, reduced toil, and improved performance and availability.
1Gartner, Market Guide for Event Intelligence Solutions, Matt Crossley, Gregg Siegfried, 10 March 2025
2These statistics are aggregated from BigPanda customer data and reflect average results. Since each organization is unique, individual results may vary based on specific use cases and configurations. Contact us to learn how your organization can benefit.
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