The Relationship between Cloud Computing and Deep Learning towards Organizational Commitment
P. Shanmugha Priya, Poonam Malik, Abolfazl Mehbodniya, Vijesh Chaudhary, Aarti Sharma, Samrat Ray
Abstract
This article provides an integrative research model that integrates environmental, organizational, and technical capacity components to analyze theinfluence of cloud computing and deep learning adoption on company commitment. This study examines firms at various business factors to identify critical organizational characteristics that positively drive influence cloud computing appraisal and deep learning. In this context, a literature review on technological innovation features is conducted to recognize potential gaps in ongoing research. Cloud computing is altering the way goods are developed, allowing for greater collaboration between corporate IT and other business divisions such as sales, finance, and forecasting, and encouraging increased customerinvolvement, even to the point of collaboratively designing products with customers. The unique insights provided by the findings can aid businesses in improving their cloud computing usage and deeplearning. Big data and machine-learning capabilities are becoming more available from cloud computing, in addition to primary processing and storage. Due to the relationship between deep learning and the cloud, the firm gains competitive advantages that speed up processes and procedures, placing it on par with the market's key competitors and making it more strategically competitive and technologically well-organized. However, deep learning with the cloud cantransform business in productivity and efficiency to fulfil its commitment. This collaboration increases the company's ability to identify commercial opportunities by offering a comprehensive, well-defined, aggressive, and limitless (thanks to the cloud) database to manageand use strategically. Furthermore, the relationship between deep learning and cloud computing has acommercial impact since it enables automatic transaction identification and allocation, anomalydetection, and the ongoing development of predictive solutions. A cloud environment learns from the data itgathers, makes predictions, and fixes possible issuesbefore the user even realises they exist. These developments lead the company to recognise that cloudcomputing and deep learning are becoming increasingly entwined.