| _version_ | 1866901794459746304 |
|---|---|
| author | Santhosh Reddy BasiReddy |
| author_facet | Santhosh Reddy BasiReddy |
| contents | <p>Customer Relationship Management and enterprise workflow platforms increasingly rely on artificial intelligence to automate decisions related to customer engagement, compliance enforcement, risk evaluation, and operational prioritization across complex organizational environments. While AI-driven automation improves efficiency, consistency, and scalability, it also introduces ethical, legal, and governance challenges that traditional workflow systems were not designed to address. Automated decisions can directly affect customer rights, financial outcomes, regulatory compliance, and organizational reputation, making responsible AI integration a critical architectural and operational concern. This article examines ethical and responsible AI frameworks as they apply to CRM and business workflows, with particular emphasis on governance structures, human oversight mechanisms, transparency, and accountability. By synthesizing established standards, process modeling practices, and human-centered AI research, the paper proposes a structured framework for embedding ethical safeguards into enterprise automation while maintaining operational effectiveness, regulatory alignment, and long-term organizational trust.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18326172 |
| institution | Zenodo |
| language | |
| publishDate | 2023 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | From Automation To Accountability: Ethical AI In CRM Workflows Santhosh Reddy BasiReddy Ethical AI, Responsible Automation, CRM Systems, Business Workflows, AI Governance, Human-in-the-Loop, Explainable AI, Compliance Automation, Decision Accountability, Enterprise Process Design. <p>Customer Relationship Management and enterprise workflow platforms increasingly rely on artificial intelligence to automate decisions related to customer engagement, compliance enforcement, risk evaluation, and operational prioritization across complex organizational environments. While AI-driven automation improves efficiency, consistency, and scalability, it also introduces ethical, legal, and governance challenges that traditional workflow systems were not designed to address. Automated decisions can directly affect customer rights, financial outcomes, regulatory compliance, and organizational reputation, making responsible AI integration a critical architectural and operational concern. This article examines ethical and responsible AI frameworks as they apply to CRM and business workflows, with particular emphasis on governance structures, human oversight mechanisms, transparency, and accountability. By synthesizing established standards, process modeling practices, and human-centered AI research, the paper proposes a structured framework for embedding ethical safeguards into enterprise automation while maintaining operational effectiveness, regulatory alignment, and long-term organizational trust.</p> |
| title | From Automation To Accountability: Ethical AI In CRM Workflows |
| topic | Ethical AI, Responsible Automation, CRM Systems, Business Workflows, AI Governance, Human-in-the-Loop, Explainable AI, Compliance Automation, Decision Accountability, Enterprise Process Design. |
| url | https://doi.org/10.5281/zenodo.18326172 |