Einstein GPT in Practice: Empowering Salesforce Developers and Admins with Generative AI

Generative artificial intelligence is transforming enterprise platforms by extending automation into conversational assistance. Einstein GPT is a nascent form of generative CRM and platform-work augmentation within the Salesforce ecosystem. Nevertheless, peer-reviewed evidence on Einstein GPT in real-world enterprise settings has not been extensively studied. This review therefore draws on adjacent but highly relevant literature, such as AI-enabled CRM, enterprise AI adoption, low-code/no-code augmentation, and AI-assisted software engineering, to develop a Salesforce-specific understanding of how generative AI can be used to facilitate platform work. The paper proposes a role-sensitive framework by integrating these fragmented streams of the needs, opportunities, and risks associated with Salesforce administrators and Salesforce developers. The common themes present throughout the literature reviewed are organizational readiness, governance, trust, workflow integration, low-code augmentation, and productivity support in the conditions of human supervision. The review also identifies major research gaps, including the lack of operationalized role-specific metrics, and the shortage of longitudinal evidence. The review argues that Einstein GPT should not be understood merely as a productivity feature, but as a socio-technical capability whose effectiveness depends on data quality, platform context, structured prompting, and governance architecture. The paper concludes with a research agenda outlining how Salesforce-native generative AI should be examined in future empirical studies.