Insights from MWC 2025: Redefining Brand and Customer Experience in the Agentic Era

However, key questions remain. Among them, how can CSPs ensure that AI agents truly carry their brand, reflect their values, and deliver the right customer experience? It’s no longer just about the technical aspects—performance, GPUs, and tokens. The challenge lies in creating agents that act as authentic extensions of the brand, forging meaningful connections with customers while meeting their high expectations.  
 
AI Agents: Transforming Customer Experience   
Last year at Mobile World Congress, we introduced an AI avatar to greet guests at our booth. In hindsight, we realized it didn’t feel like a true extension of our brand. The avatar lacked the depth of knowledge and communication style needed to embody who we are. This experience reminded us that for AI agents to be effective, they must authentically represent the brand, supported by the right data, expertise, and personality.   
 
CSPs face similar challenges as they begin adopting AI agents. These agents are set to revolutionize customer engagement by serving as dynamic brand ambassadors. Far beyond traditional approaches, they can deliver personalized, empathetic, and efficient service tailored to individual customer needs. By seamlessly aligning with a CSP’s unique values and tone, AI agents can build trust and foster loyalty while enhancing every interaction.  
 
Meeting consumer expectations, however, is no small task. Research from Amdocs highlights that consumers often hold AI agents to even higher standards than human representatives. They expect AI agents to demonstrate empathy (80%), professionalism (85%), quick issue resolution (87%), and first-time resolution (74%). To meet these high expectations, AI agents must combine emotional intelligence with advanced technology, ensuring that every interaction is functional, meaningful, and impactful.  
 
Going Beyond Customer Care  
AI agents are not just reshaping customer care—they are also redefining how CSPs manage their operations. These agents can automate complex backend workflows, increasing speed, accuracy, and cost efficiency. For instance, in enterprise sales, AI agents can streamline and manage intricate Configure, Price, Quote (CPQ) processes, dramatically reducing the time from order to activation. This transformation enables CSPs to deliver services faster, with fewer errors, and improved customer satisfaction. 
 
Beyond sales, AI agents proactively streamline tasks, manage networks, and integrate seamlessly with legacy systems to drive operational excellence and enhance customer experience. They also enable CSPs to predict and address potential issues before customers are impacted, boosting reliability, and ensuring consistent service delivery.  
 
By bridging the gap between automation and adaptability, AI agents empower CSPs to deliver exceptional customer experiences while maintaining operational scalability. This dual transformation positions CSPs to thrive in an increasingly competitive market, where both innovation and efficiency are essential for success.  
 
Data Readiness: Moving Beyond Just Availability  
While the potential of AI agents is vast, CSPs must address several key challenges to unlock their full value. Integrating AI agents with legacy systems remains a significant barrier. Overcoming this requires investment in modernization and system interoperability.   

Further, data readiness is misunderstood. It’s not just about making datasets available—it’s about ensuring AI agents can identify and use the right data for specific processes. For example, when answering a query like, “Is my order activated?” an agent must know how to retrieve relevant information from a search process and take the appropriate action. This requires more than data availability; it demands a layer of logic that trains agents to apply data intelligently within the context of the task.  

This complexity highlights why the journey to the agentic era has been slow and skepticism remains. To overcome this, CSPs need unified data strategies that not only break down silos but also enable agents to learn and act on data in ways that deliver predictive, meaningful outcomes. 
 
Solving Challenges Requires a Comprehensive Solution  
With this, the evolution of AI capabilities necessitates a shift in data architecture. To help CSPs navigate this, Amdocs launched its amAIz Suite, a comprehensive and modular offering designed to break down data silos, predict customer intents and proactively act upon them. This is done by combining telco-specific insights and analytical layers, a holistic approach to data, autonomous standalone Agents and embedded Copilots, and optimized data management built on AI and GenAI platforms.  
 
With this holistic approach, CSPs can make a significant leap forward to meet this critical moment, transforming their business, network, and operational domains by preparing vast amounts of data for GenAI-enabled apps, proactive Agents and copilots, improving customer experiences and business efficiencies across the board. 
 
A Future Redefined   
The agentic era offers telecommunications a chance to move past its legacy of low customer satisfaction scores. This is the moment for CSPs to move beyond long wait times and deliver amazing, humanized customer experiences—available 24/7 and rivaling the world’s most beloved services. No more excuses.  
 
Achieving this vision requires more than technology; it demands a commitment to aligning AI with customer expectations, prioritizing personalization, and ensuring seamless experiences. Those who act now will not only elevate their customer experience but redefine what it means to succeed in the agentic era.   
 
Gil Rosen will be speaking about the agentic era and its impact during the session, The Web is Dead: Agentic AI and the Rise of the Post-Web Era, on Wednesday, March 5, 15:45-16:45 CET, Marconi Stage, Hall 6 

This article first appeared in Mobile World Live, Insight Magazine 2025