Agentic AI for Seamless Scheduling

  • Unique Paper ID: 196627
  • Volume: 12
  • Issue: 11
  • PageNo: 3299-3303
  • Abstract:
  • Efficient appointment scheduling remains a persistent operational challenge across healthcare clinics, salons, and service-based organizations. Traditional manual booking methods depend heavily on human receptionists, leading to missed calls, scheduling conflicts, increased workload, and limited-service availability outside working hours. This research presents an Agentic AI-driven multimodal scheduling system capable of autonomously managing appointments through both voice calls and text-based interactions. The proposed system integrates telephony services, automatic speech recognition (ASR), natural language understanding, real-time calendar synchronization, and conversational AI reasoning to perform booking, rescheduling, cancellation, and reminder delivery without human intervention. Unlike conventional chatbots or standalone voice bots, the system operates as an autonomous AI receptionist, capable of understanding conversational context, invoking scheduling tools, confirming appointments via voice or text, and maintaining secure interaction logs. Experimental deployment demonstrates improved scheduling accuracy, reduced administrative workload, continuous 24/7 availability, and enhanced user satisfaction. The study highlights the transformative role of agentic artificial intelligence in automating administrative workflows and presents a scalable foundation for intelligent service management across multiple domains.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{196627,
        author = {Prem Thakur and Yash Shirgaonkar and Shubham Tiwari and Janhavi Toraskar and Prof. Punam Bagul},
        title = {Agentic AI for Seamless Scheduling},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {3299-3303},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196627},
        abstract = {Efficient appointment scheduling remains a persistent operational challenge across healthcare clinics, salons, and service-based organizations. Traditional manual booking methods depend heavily on human receptionists, leading to missed calls, scheduling conflicts, increased workload, and limited-service availability outside working hours. This research presents an Agentic AI-driven multimodal scheduling system capable of autonomously managing appointments through both voice calls and text-based interactions. The proposed system integrates telephony services, automatic speech recognition (ASR), natural language understanding, real-time calendar synchronization, and conversational AI reasoning to perform booking, rescheduling, cancellation, and reminder delivery without human intervention. Unlike conventional chatbots or standalone voice bots, the system operates as an autonomous AI receptionist, capable of understanding conversational context, invoking scheduling tools, confirming appointments via voice or text, and maintaining secure interaction logs. Experimental deployment demonstrates improved scheduling accuracy, reduced administrative workload, continuous 24/7 availability, and enhanced user satisfaction. The study highlights the transformative role of agentic artificial intelligence in automating administrative workflows and presents a scalable foundation for intelligent service management across multiple domains.},
        keywords = {Agentic AI, Appointment Scheduling, Calendar Integration, Conversational AI, Multimodal Interaction, Telephony Automation, Voice Assistant.},
        month = {April},
        }

Cite This Article

Thakur, P., & Shirgaonkar, Y., & Tiwari, S., & Toraskar, J., & Bagul, P. P. (2026). Agentic AI for Seamless Scheduling. International Journal of Innovative Research in Technology (IJIRT), 12(11), 3299–3303.

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