Gartner® Report – A CTO’s Guide to Top Artificial Intelligence Engineering Practices November 16, 2021 in All Resources › Industry Reports Access the ReportAccess to this Report is now expired.You can access more content like the Report, and all the latest content in All Resources →See why Gartner® named us a Commercial Vendor Although many enterprises are prioritizing investment in AI and machine learning, the business value is still obfuscated today because of challenges with moving AI models and proofs of concept out of the lab, into production, at scale. In order to truly unlock the value of AI, more focus must be given to model operationalization and integrating with existing infrastructure and applications. This report delves into AI engineering best practices for CTOs to get to the benefits and values of AI faster. Gartner defines AI engineering as “a discipline focused on the governance and life cycle management of a wide range of operationalized AI and decision models. AI engineering methods enable better governance and consistency in reusing, retraining, rebuilding, interpreting and explaining AI models. These methods aim to provide an uninterrupted flow between the development, operationalization, and full maintenance of AI models.” AI engineering is built upon the following disciplines: DataOps DevOps ModelOps Responsible AI Read this report for recommendations on establishing a healthy AI engineering practice to unlock the value of AI at scale. Gartner, A CTO’s Guide to Top Artificial Intelligence Engineering Practices, Arun Chandrasekaran, Farhan Choudhary, Erick Brethenoux, 29 October 2021. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. was part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Share this post About Modzy Modzy is the ModelOps and MLOps software platform that businesses use to deploy, integrate, run, and monitor AI—anywhere.