Towards Enterprise-Ready AI Deployments Minimizing the Risk of Consuming AI Models in Business Applications
Aleksander Slominski, Vinod Muthusamy, Vatche Ishakian
TL;DR
This paper presents an approach to mitigate risks in deploying AI models in business applications by using AI techniques for monitoring and controlling model usage in production environments.
Contribution
It introduces a novel method for managing AI model deployment risks through insights and control mechanisms tailored for enterprise settings.
Findings
Enhanced monitoring of AI model usage
Reduced deployment risks in business applications
Framework for controlling AI model deployment
Abstract
The stochastic nature of artificial intelligence (AI) models introduces risk to business applications that use AI models without careful consideration. This paper offers an approach to use AI techniques to gain insights on the usage of the AI models and control how they are deployed to a production application. Keywords: artificial intelligence (AI), machine learning, microservices, business process
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Taxonomy
TopicsBig Data and Business Intelligence · Software System Performance and Reliability · Data Quality and Management