From CRM to Cognition: Autonomous Revenue Operations Systems (AROS) A Framework for AI-Native Sales Execution in Enterprise Environments

From CRM to Cognition: Autonomous Revenue Operations Systems (AROS) A Framework for AI-Native Sales Execution in Enterprise Environments | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 April 2026 V1 Latest version Share on From CRM to Cognition: Autonomous Revenue Operations Systems (AROS) A Framework for AI-Native Sales Execution in Enterprise Environments Author : Arjun Pardasani 0009-0000-0961-2036 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177574458.87877153/v1 83 views 48 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Enterprise sales organizations are systematically hampered by what this paper terms 'Revenue Friction'-the accumulative productivity loss caused by fragmented, human-mediated data entry across disconnected CRM, ERP, and quoting systems. While automation technologies such as Robotic Process Automation (RPA) [van der Aalst et al., 2018; Lacity & Willcocks, 2016] and AI copilots [Noy & Zhang, 2023; Brynjolfsson et al., 2023] have partially addressed transactional inefficiencies, no unified architectural paradigm has emerged to govern end-to-end autonomous sales execution. This paper introduces the Autonomous Revenue Operations System (AROS): a novel five-layer AI framework that transforms unstructured commercial inputs-emails, phone calls, purchase orders, and images-into fully executed downstream workflows including quote generation, order entry, ERP reconciliation, and sales intelligence synthesis. AROS is distinguished from existing approaches by its integration of large language model (LLM)based semantic understanding [Brown et al., 2020; Wei et al., 2022], real-time human-in-the-loop correction mechanisms [Christiano et al., 2017; Ouyang et al., 2022], and continuous reinforcement learning within a production enterprise environment. Empirical grounding from the Ventura AI platform (2026) demonstrates that AROS-aligned systems achieve 3x productivity improvement, a 3-5% increase in deal conversion rate, and approximately 25% reduction in order entry errors. We formalize the framework through an Input-Understanding-Decision-Execution-Learning (IUDEL) model and propose a quantitative Revenue Friction Index (RFI) to measure systemic sales inefficiency. This work establishes the conceptual and technical foundation for post-CRM sales infrastructure [Davenport, 1998; Klaus et al., 2000] and identifies key research directions in autonomous multi-agent negotiation, voice-first ERP interaction, and AI-native revenue forecasting. Supplementary Material File (from_crm_to_cognition_autonomous_revenue_operations_systems_pardasani_2026.pdf) Download 253.93 KB Information & Authors Information Version history V1 Version 1 09 April 2026 Copyright This work is licensed under a Creative Commons Attribution 4.0 International License Keywords ai agents autonomous revenue operations crm demand analyst enterprise ai erp integration human-in-the-loop large language models revenue friction rlhf sales automation supply chain Authors Affiliations Arjun Pardasani 0009-0000-0961-2036 [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 83 views 48 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Arjun Pardasani. From CRM to Cognition: Autonomous Revenue Operations Systems (AROS) A Framework for AI-Native Sales Execution in Enterprise Environments. Authorea . 09 April 2026. DOI: https://doi.org/10.22541/au.177574458.87877153/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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