Integration of AI for Routine Tasks Using Salesforce

Aims: In the previous decade, developments in machine learning techniques have drawn interest from the literature and corporate organizations to artificial intelligence technologies. However, despite the immense promise of AI technology for problem resolution, there are still limitations with practical application and a lack of expertise in employing AI strategically to produce business benefits. Customer Relationship Management (CRM) has recently experienced substantial developments. Companies have implemented AI-based CRM to effectively react to client inquiries and increase customer loyalty.

Study design: Qualitative analysis.

Methodology: We have selected 15 publications from the research database for further investigation. The rapid growth of modern sales technology literature has resulted in a rich but fragmented representation of what sales technology is, raising the question of how its position within the sales process can be effectively defined.

Results: The results of the literature review enabled the author to recognize three major subfields of AI literature within the CRM domain (AI and machine learning techniques used for CRM activities, strategic management of AI-CRM integrations, and AI integration in Salesforce) and gather promising future development paths for each of these subfields. This study also proposes a three-step theoretical framework for AI deployment in CRM, which may help scholars further improve their expertise in this sector and managers create a suitable and consistent approach.

Conclusion: A conceptual framework is offered, with four sources of value creation discussed: (i) decision assistance; (ii) consumer and employee involvement; (iii) automation; and (iv) new services and products. These findings add to both conceptual and administrative views, with several prospects for developing new theories and management techniques.