AI-Powered Enterprise System for CRM and Inventory Management in Low-Digital MSMEs

Zachary Matthew Alabastro, Beatrice Anne Lui, Joseph Benjamin Ilagan, Jose Ramon Ilagan, Gabrielle Anne Uy

In HCI in Business, Government and Organizations (HCII 2026), LNCS, pp. 3–21. Springer, 2026.

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Abstract

Many micro, small, and medium enterprises in developing economies continue to rely on handwritten records and informal chat-based transactions, limiting their ability to analyze data and make informed decisions. This paper presents the design and evaluation of an AI-powered enterprise system intended for MSMEs operating in low-digital contexts. The system integrates optical character recognition, large language models, entity resolution, and multilingual conversational interfaces to transform handwritten and chat-based business records into structured, analytics-ready data. Field deployments with Philippine MSMEs demonstrate how natural language querying and human-in-the-loop validation lower barriers to adoption while supporting trust, usability, and explainability. The study contributes to HCI research by showing how hybrid human–AI architectures can democratize data-driven decision-making for small businesses in emerging markets.

Keywords: ERP; MSME; Generative AI; OCR; Human-in-the-loop; LLM

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Accepted manuscript. This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-032-30044-7_1. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms.

Cite as

Zachary Matthew Alabastro, Beatrice Anne Lui, Joseph Benjamin Ilagan, Jose Ramon Ilagan, Gabrielle Anne Uy (2026). AI-Powered Enterprise System for CRM and Inventory Management in Low-Digital MSMEs. In HCI in Business, Government and Organizations (HCII 2026), LNCS, pp. 3–21. Springer. https://doi.org/10.1007/978-3-032-30044-7_1