As telecommunications networks evolve toward 6G and beyond, artificial intelligence is rapidly becoming the cornerstone of operational efficiency, service innovation, and customer experience. For industry leaders, the challenge is clear: How can we ensure that AI-driven functions that impact everything from network reliability to user safety are truly trustworthy, fair, and explainable?
This webinar is designed for telecom executives and decision makers who are shaping the future of intelligent networks. Learn why trust in AI is not just a technical concern but a strategic differentiator in a market where compliance, safety, and customer confidence are now demanding explainability of AI. Understand how advanced certification and testing frameworks are being redefined for AI, moving from traditional linear models to dynamic, non-linear assurance processes that reflect the complexity of modern telecom environments.

Watch the webinar and learn about:

• See how trust is vital for deploying AI in performance and safety-critical roles
• Understand how certification and testing enable AI fairness and explainability
• Why new non-linear (W-shaped) assurance processes are needed for validating complex AI systems
• Building high-quality, unbiased datasets is essential for trustworthy AI
• Discover strategies to address AI “hallucinations” and validate edge cases in testing
• Unique challenges in 6G network/device testing: data diversity, standardization, real-time inference, and the need for ongoing validation
   

Presenters:

Jonathan Borrill
CTO Test & Measurement business, Anritsu
Jonathan Borrill is a Chartered Engineer with over 30 years of experience in advanced RF and wireless systems. His career spans millimetre-wave research at the UK Ministry of Defence applications leadership at Motorola, and senior roles at Anritsu where he is currently appointed as CTO for the Test & Measurement business.
Today, he supports next-generation telecom testing and certification, bringing deep expertise to the evolution toward 6G and AI-driven networks.

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