In a June 8 article for HBR, Nexus Frontier Tech executives Terence Tse, Mark Esposito, Takaaki Mizuno and Danny Goh explain the missing component businesses often leave out when pursuing AI projects: AI operations, also referred to as “AIOps.”
Five things to know:
1. AIOps is the process of “building, integrating, testing, releasing, deploying and managing the system to turn the results from AI models into desired insights of the end-users,” according to the report.
2. Businesses often spend time and resources working on the AI models themselves, but often fail to consider how to make the tech work with the systems they already have. AIOps relies on the necessary hardware, software and team members to integrate the new AI into the company’s existing processes and systems.
3. Achieving a successful AI integration begins with a well-designed production environment, which requires dependability. The AIOps team must avoid data slowdowns by putting proper processing and storage systems in place that can handle latency issues.
4. The production environment must also be flexible enough to support quick system reconfiguration and data synchronization without compromising running efficiency. The architecture should be flexible and separated into manageable portions that can be added or replaced if an issue arises.
5. Scalability and extendibility is also critical in a successful production environment, because when integrating a new AI solution, the existing infrastructure must adapt. The team’s ability to “adjust, tinker and test the existing system with the new proposed system” is important for business to continue while implementing upgraded AI models.
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