Abstract: In recent years, the emergence of agentic AI frameworks has revolutionized the landscape of customer lifecycle management within Business Support Systems. These frameworks leverage intelligent agents to automate and optimize the myriad interactions and processes that occur throughout the customer lifecycle, from acquisition to retention. This paper explores the deployment of agentic AI within BSS systems, hypothesizing that these advanced technologies can generate significant efficiencies and improved customer experiences. The complexity of customer lifecycle management necessitates sophisticated solutions capable of interpreting and acting upon diverse data points. Agentic AI frameworks meet this challenge by offering a confluence of autonomy, adaptability, and machine learning capabilities, allowing them to dynamically respond to evolving customer demands and operational conditions.
The application of such frameworks extends beyond mere automation, enabling genuine intelligence-driven decision-making in customer engagement processes. Agentic AI models create a seamless integration between predictive analytics, current customer interactions, and future strategic planning. This proactive approach not only facilitates personalized customer journeys but can also identify potential churn, upsell opportunities, and optimal engagement channels. The adaptability of these systems ensures they remain relevant and effective in the face of changing market trends and customer preferences. Moreover, by leveraging AI's ability to process and analyze vast amounts of data, businesses can gain deep insights into customer behavior and preferences, informing both strategic and operational decisions. Consequently, the implementation of agentic AI in customer lifecycle management holds the potential to transform traditional BSS systems, offering enhanced service delivery, increased customer satisfaction, and ultimately, a competitive advantage in an increasingly digital marketplace.
Keywords: Agentic AI,Customer Lifecycle Management,Business Support Systems (BSS),AI Automation,Intelligent Agents,Telecom BSS,Autonomous Customer Management,AI-Driven Workflow Automation,Context-Aware Agents,Adaptive AI Frameworks,Digital Customer Experience,Predictive Customer Engagement,AI-Orchestrated BSS,Multi-Agent Systems,Self-Learning AI Models.
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DOI:
10.17148/IJARCCE.2022.111257
