The Future of AI in Salesforce: Intelligent Virtual Assistants & Automation |
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© 2025 by IJCTT Journal | ||
Volume-73 Issue-4 |
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Year of Publication : 2025 | ||
Authors : Arun Kumar Mittapelly, Vasanta Kumar Tarra | ||
DOI : 10.14445/22312803/IJCTT-V73I4P112 |
How to Cite?
Arun Kumar Mittapelly, Vasanta Kumar Tarra, "The Future of AI in Salesforce: Intelligent Virtual Assistants & Automation," International Journal of Computer Trends and Technology, vol. 73, no. 4, pp. 88-94, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I4P112
Abstract
From chatbots to predictive and virtual assistant, conversational AI has made businesses communicate with their customers in a human-like and intelligent way. One such platform with integrated AI-driven solutions is Salesforce, a leading Customer Relationship Management (CRM) platform with AI-powered solutions like Einstein AI to help businesses boost customer engagement, automate workflows and streamline business processes. This paper explores how Conversational AI and Salesforce converge and discusses improvements in Natural Language Processing (NLP), Machine Learning and Deep learning. This study compares the available chatbot models, how they have been implemented in Salesforce, and how a business can benefit from using them to increase efficiency and customer satisfaction. Furthermore, we present a novel hybrid Conversational AI system that unifies Salesforce’s Einstein AI with 3rd Party AI models to create a more contextually aware and agile conversational experience. We then show a use case where we implement an AI-powered chatbot in a sales environment and evaluate the performance to see how the chatbot can increase customer engagement and automate lead generation.
Keywords
Conversational AI, Salesforce, Chatbots, Virtual Assistants, NLP, Deep Learning, Customer Relationship Management.
Reference
[1] Joseph Weizenbaum, “ELIZA-A Computer Program for Studying Natural Language Communication between Man and Machine,” Communications of the ACM, vol. 9, no. 1, pp. 36-45, 1966.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Steve Young et al., “POMDP-Based Statistical Spoken Dialogue Systems: A Review,” Proceedings of the IEEE, vol. 101, no. 5, pp. 1160 1179, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Julia Hirschberg, and Christopher D. Manning, “Advances in Natural Language Processing,” Science, vol. 349, no. 6245, pp. 261-266, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Robert Dale, “The Return of the Chatbots,” Natural Language Engineering, vol. 22, no. 5, pp. 811-817, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Richard Socher et al., “Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank,” Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, Seattle, Washington, USA, pp. 1631-1642, 2013.
[Google Scholar] [Publisher Link]
[6] Li Zhou et al., “The Design and Implementation of Xiaoice, an Empathetic Social Chatbot,” Computational Linguistics, vol. 46, no. 1, pp. 53-93, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Tom Bocklisch et al., “Rasa: Open-Source Language Understanding and Dialogue Management,” arXiv Preprint, pp. 1-9, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Emma Strubell, Ananya Ganesh, and Andrew McCallum, “Energy and Policy Considerations for Modern Deep Learning Research,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 9, pp. 13693-13696, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Reuben Binns, “Fairness in Machine Learning: Lessons from Political Philosophy,” Conference on Fairness, Accountability and Transparency, vol. 81, pp. 149-159, 2018.
[Google Scholar] [Publisher Link]
[10] Arooj Basharat, and Zilly Huma, “Streamlining Business Workflows with AI-Powered Salesforce CRM,” Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 313-322, 2024.
[Google Scholar] [Publisher Link]
[11] Meera M. Shah, and Hiren R. Kavathiya, Unveiling the Future: Exploring Conversational AI, Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom, pp. 511-526, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Shailesh Kediya et al., “Chatbots in Customer Service: A Comparative Analysis of Performance and Customer Satisfaction,” 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, Wardha, India, pp. 1-6, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Chadi Khneyzer, Zaher Boustany, and Jean Dagher, “AI-Driven Chatbots in CRM: Economic and Managerial Implications across Industries,” Administrative Sciences, vol. 14, no. 8, pp. 1-16, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[14] John N. Davies et al., “Personalize the E-learning Process using AI-Powered Chatbot Integration,” Mathematical Modeling and Simulation of Systems: Selected Papers of 15th International Scientific-practical Conference, Chernihiv, Ukraine, pp. 209-216, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Stephen Denning, “Successfully Implementing Radical Management at Salesforce.Com,” Strategy & Leadership, vol. 39, no. 6, pp. 4-10, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Kiryl Kaliuta, “Economic Benefits of Using Salesforce in Business: Analysis and Practical Recommendations,” Futurity Economics & Law, vol. 4, no. 2, pp. 83-99, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Christian Hildebrand, and Anouk Bergner, “AI-Driven Sales Automation: Using Chatbots to Boost Sales,” NIM Marketing Intelligence Review, vol. 11, no. 2, pp. 36-41, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Sorin Anagnoste et al., “The Role of Chatbots in End-to-End Intelligent Automation and Future Employment Dynamics,” Business Revolution in a Digital Era: 14th International Conference on Business Excellence, Bucharest, Romania, pp. 287-302, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Heiko Fischer et al., “Artificial Intelligence in B2B Sales: Impact on the Sales Process,” Artificial Intelligence and Social Computing, vol. 28, no. 28, pp. 135-142, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Teik Toe Teoh, AI in Sales, Artificial Intelligence in Business Management, Springer, pp. 175-208, 2023.
[CrossRef] [Google Scholar] [Publisher Link]