Enabling Business Agility With Autonomous Networking

Presented by

Alex Arcilla-Principal Analyst-Validation Services, Omdia; James Graham-Associate Director of Business Strategy, Verizon Business; Chris Whitfield- Senior Manager of Product Management, Verizon Business

About this talk

In today's rapidly evolving business landscape, enterprises face mounting pressure to modernize network infrastructure while managing increased data volumes, IoT proliferation, and sophisticated cyber threats. This technical validation webinar explores how Verizon Managed Network Services leverages three strategic pillars—integration, automation, and artificial intelligence—to transform network operations from reactive to predictive.

Join Verizon’s Associate Director of Business Strategy, James Graham, and Senior Manager of Product Development, Chris Whitfield, to discover how a customer-centric operational support model, combined with advanced AIOps capabilities, delivers measurable outcomes such as a 75% reduction in change window times and proactive issue resolution before incidents occur. Learn how managing 4,000+ global networks and 500,000+ devices help Verizon Managed Network Services to provide unique insights to its customers for building self-healing, autonomous networks that support AI readiness and operational efficiency.

This session examines real-world implementation strategies, from ITSM integration and zero-touch automation to predictive analytics that shift operations from repair to prevention. Whether you're beginning your network transformation journey or advancing toward autonomous operations, gain practical insights on leveraging managed services to accelerate digital transformation while reducing operational complexity.

Key Takeaways:

  • Strategic approach to network automation and AI integration
  • Customer-centric operational models that align network performance with business outcomes
  • Practical implementation pathways for enterprises at various transformation stages
  • Real-world case study demonstrating 75% reduction in deployment time

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