This work investigates the integration of artificial intelligence (AI) into customer lifecycle management (CLM) with a specific focus on business-to-business (B2B) customers within the telecommunications sector. The research highlights the importance of effectively managing customer expectations and experiences across various stages of their relationship with a company, from brand recognition to potential churn. It emphasizes the need for businesses to leverage AI to enhance decision-making, personalize customer journeys, and optimize customer lifetime value to stay competitive in saturated markets. 

We conducted a literature review to provide a more complete view of AI in CLM and to identify research gaps, particularly in practical AI implementations aimed at improving customer lifecycles. The work aims to provide actionable insights and models applicable to organizations seeking to utilize AI in their CLM strategies. We employed an empirical approach to evaluate our proposed methods and AI models, which showed a good capability in predicting churn in B2B, email response time in customer service, and non-routing email detection. Throughout this work, we have taken a practical approach and based all work on real-world data to demonstrate a potential business impact.