Artificial intelligence (AI) is widely used across multiple industries, particularly in the communications sector, to enhance, optimize, and automate network infrastructure. Key AI capabilities include machine learning, data analytics, and network automation. AI helps synchronize data and improve usability, thereby increasing scalability. Demand for rigorous AI infrastructure testing for lifecycle analysis will pave the way for emerging government regulations and compliance requirements. Despite the exponential growth of AI, most major networks are unable to support data-intensive applications and cloud processing. This produces a massive challenge for both network infrastructure manufacturers and AI test and measurement (T&M) vendors.

• In what ways is AI creating growth opportunities for optimizing and automating network infrastructure, and how can you capitalize on them?
• What growth gaps can manufacturers and T&M vendors address to support data-intensive AI applications and cloud processing?
• What best practices can help test vendors in AI networks develop cutting-edge T&M solutions to gain a competitive advantage?