Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Singh, Shanu; Awasthi, Yashmita Title A name given to the resource Assessment of AI Companies Operational Performance in India Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AIP Conference Proceedings;Volume;3224;Issue;1;Article No.;20001; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1063/5.0245928" target="_blank" rel="noreferrer noopener">https://doi.org/10.1063/5.0245928</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85218694482?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218694482?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Singh S., School of Commerce, Finance &amp; Accountancy, Christ (Deemed to be University), Delhi-NCR, Mariam Nagar, Meerut Road, Ghaziabad, 201003, India; Awasthi Y., School of Commerce, Finance &amp; Accountancy, Christ (Deemed to be University), Delhi-NCR, Mariam Nagar, Meerut Road, Ghaziabad, 201003, India Description An account of the resource The article has delved into understanding the importance and performance of Artificial Intelligence companies in India with the data of the past five years. It scrutinizes the performance and significance of Artificial Intelligence (AI) companies in India over the past five years. It delves into the financial data, specifically examining Profit After Tax as an independent variable and its relation to net cash flows in these companies. The analysis involves nine prominent AI companies in India and employs statistical tools such as correlation, regression, standard deviation, and one-way ANOVA. The findings indicate varying relationships between Profit After Tax and net cash flows across different companies, underscoring the complexities within their financial dynamics. While some companies exhibit a positive correlation, others show no direct relationship. Additionally, the article explores government guidelines and existing laws that impact AI companies in India, emphasizing ethical and responsible AI usage. Despite the evolving market, the article suggests a promising future for AI companies in India, contingent upon their ability to tailor solutions to the unique challenges and opportunities in the Indian landscape. 2025 Author(s). Subject The topic of the resource AI Solutions; Artificial Intelligence Companies; Net Cash Flow; Operational Performance; Profit After Tax Publisher An entity responsible for making the resource available American Institute of Physics Relation A related resource ISSN: 0094243X; ISBN: 978-073545120-9; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online