As AIOps use cases expand and evolved, Research in Action GmbH suggests a more apt meta-market descriptor is Artificial Intelligence Predictive Analytics (AIPA).
The use of artificial intelligence in operations (AIOps) has gained acceptance, with many different functional areas within IT adopting the technology. The problem is that as the market grows and its applications expand, the term no longer matches the reality of the existing solutions as each solution vendor has somewhat of a unique approach, according to a report from the research and consulting company Research in Action GmbH. Instead, the consultancy suggests a more apt meta-market descriptor is Artificial Intelligence Predictive Analytics (AIPA), which includes AIOps and expands the use cases.
In its report, Research in Action GmbH noted that AIPA solutions “automate the ingestion of fast volumes of data, leverage machine learning to analyze the data, present findings to either predict, alert, or advise on issues, and aid its user with proactive decision making.”
The consultancy noted that the solutions should support a broad set of stakeholders to observe, analyze, act, and predict upon a fast amount of data available. As such, Research in Action GmbH believes AIPA solutions should offer certain features and capabilities. The report noted that these attributes include:
- Access and ingest data from multiple sources such as existing tools within development and IT operations teams. AIOps is a subset of AIPA.
- Include real-time and historical data analysis capabilities using machine learning algorithms.
- Enable the storing of relevant data (including access for further analysis or deep dives).
- Input for action and additional insights with prescriptive responses to the analysis of observed and ingested data.
- Action suggestions then can be integrated with automatic remediation or fulfillment solutions.
- Role-based dashboards for overview and insights (result of analysis).
AIPA report findings
Research in Action GmbH interviewed 1,500 enterprise managers with budget responsibility in enterprises globally for the report. It found that the current vendor landscape within AIOps is bewildering. “There are many vendors leveraging AI, all with different roots. While some vendors are using the term AIOps specifically for IT operations, others are using the term for broader use cases and expansion of their APM or ITOM offerings,” noted the report.
On the plus side, the survey found that companies are interested in AIPA for its promise to provide end-to-end visibility. AIPA also has the potential of bringing existing silos together.
The survey findings were presented in a full report title “Vendor Selection Matrix™ Report – Artificial Intelligence Predictive Analytics: The Top 20 Global Vendors 2021.” The report surveyed enterprise IT and business decision-makers to gain insights on strategy, investments, and ongoing technology innovation challenges in the IT industry. It classified vendors on a variety of criteria that fall into the categories of strategy and execution and was put together based on raw feedback from interviews with enterprise managers with budget responsibility in global enterprises.
Moogsoft, an AI-driven observability leader, was named a top vendor. “Moogsoft is on the cutting edge of observability in AIOps and is only continuing to gain momentum,” said Eveline Oehrlich, Research Director of Research In Action GmbH.
Moogsoft also achieved the highest Recommendation Index out of all evaluated vendors at 99%. The Recommendation Index is compiled by asking participants for their insight and opinion on what vendor they would recommend to peers. The company received badges for both achievements as a Market Leader and #1 Recommendation Index.
