At DTW Ignite, Tara Neal spoke with Jeff Spiess, Product Director at Motive, where he focuses on product strategy and innovation across service assurance and customer experience solutions for communication service providers.

The discussion explored the evolution of Agentic AI, Model Context Protocol (MCP), autonomous operations, predictive care, digital-first customer experiences, and the platform capabilities required to support 5G-Advanced, eSIM, and IoT at scale.

Tara: As communication service providers accelerate their AI strategies, where are you seeing the greatest opportunities for AI to move beyond experimentation and deliver measurable improvements in customer experience and operational efficiency?

Jeff: As communication service providers move from AI pilots to production deployments, the biggest opportunity lies in combining Agentic AI with operational systems through the Model Context Protocol (MCP). MCP provides a standardized way for AI applications to securely access network, customer, service assurance, and business systems, helping CSPs move beyond isolated proofs of concept and deploy AI solutions at scale. At the same time, Agentic AI enables a new generation of use cases that can reason across multiple data sources, identify issues, recommend actions, and even automate approved workflows. This creates opportunities to improve both customer experience and operational efficiency. One of the most visible applications is the rise of intelligent virtual assistants. When backed by MCP-enabled tools, these assistants can provide personalized support, diagnose service issues, answer complex customer questions, and initiate corrective actions, delivering faster resolutions and more seamless customer experiences.

Tara: DTW increasingly highlights the move toward autonomous networks and simplified operations. How are service assurance and orchestration evolving to support cloud-native, multi-domain environments that are becoming more dynamic and complex?

Jeff: While autonomous networks often focus on network assurance and orchestration, Motive’s primary focus is service assurance from the customer experience perspective. As CSP environments become more cloud-native and multi-domain, the challenge is no longer just understanding network health—it is understanding how network, device, and service issues impact individual subscribers. On the network side, predictive maintenance is emerging as a significant opportunity. By analyzing telemetry and operational data, AI can identify potential issues before they result in outages or service degradation, reducing operational costs, and improving reliability. A similar approach is now being applied to customer service through predictive care. By combining network, device, and customer interaction data, CSPs can proactively identify subscribers who are likely to experience issues, take corrective actions before the customer contacts support, and deliver a more personalized, proactive service experience. This shift from reactive support to proactive care is a key step toward autonomous operations that directly improve customer satisfaction.

Tara: With operators balancing cost pressures against the need to differentiate, how can CSPs create genuinely digital-first customer experiences without adding further complexity to their operational stacks?

Jeff: CSPs can create truly digital-first customer experiences by simplifying how AI and digital channels interact with existing operational systems rather than replacing those systems. A key enabler is an integration platform with MCP capabilities that exposes legacy OSS/BSS applications through standardized MCP servers. This allows AI applications, virtual assistants, and automation tools to securely access the data and actions they need without requiring extensive point-to-point integrations. Virtual assistants powered by AI will play a central role in delivering digital-first experiences through natural voice and chat interactions. Customers increasingly expect conversational, personalized support that can resolve issues and complete transactions without friction. At the same time, omnichannel capabilities remain essential. Customers want consistent experiences across mobile apps, web portals, chat, voice, and assisted service channels. AI should unify these interactions, ensuring context follows the customer regardless of how they choose to engage.

Tara: As 5G-Advanced, eSIM and IoT adoption continue to expand, what platform capabilities will be most important for operators seeking to manage billions of connected devices while maintaining agility and service quality?

Jeff: As 5G-Advanced, eSIM, and IoT deployments scale toward billions of connected devices, operators will need platforms that simplify operations while improving visibility across increasingly complex environments. One critical capability is AI-assisted troubleshooting. With devices, networks, and services generating massive volumes of telemetry, AI can help quickly identify the source of issues, reduce mean time to resolution, and guide operations teams toward the most effective corrective actions. Natural language reporting will also become increasingly important. Operations, customer care, and business teams should be able to explore data, analyze trends, and investigate performance issues using conversational interfaces rather than relying solely on specialized analytics skills or predefined dashboards. Finally, operators need unified platforms that support multiple device management stacks and protocols. A multi-stack approach enables consistent management, monitoring, and automation across diverse device ecosystems, helping operators maintain service quality while remaining agile as new technologies and device types are introduced.