In many sectors, AI projects die in pilot purgatory, but telecom has managed to make substantial, practical AI implementations, particularly in network optimization, predictive maintenance and customer service. In an insightful conversation with RCR Wireless, Cédric Foray, EY global and EMEIA telecommunications sector lead, pointed out the ways in which AI infrastructure is influencing telcos today, and where it may go tomorrow. “They’re currently at the intersection of AI and infrastructure decision-making,” which is leading telecom leaders to invest in key foundational areas, such as cloud native functions and apps, computing resources, edge AI infrastructure, and upgraded network infrastructure to handle AI workloads (fiber optics and virtualized network functions).

In addition, Foray points out that telcos are increasingly building partnerships with cloud companies and hyperscalers like AWS, Microsoft Azure, and Google Cloud. Indeed, companies like Verizon, AT&T, Vodafone, Deutsche Telekom, Telefónica, KDDI, and others are making themselves invaluable to tech giants and AI visionaries, not only providing the fiber and wireless infrastructure that transports data among data centers, but also the dark fiber and network services that will bolster redundancy and scale. And as Foray notes, “They also provide the regional expertise and last-mile partnerships that will be increasingly essential in expanding AI infrastructure and services.” See the full article here.

When it comes to the impact of current AI infrastructure investment on future value creation, it’s worth reading our recent piece about private 5G and industrial AI at the enterprise edge — through the lens of agricultural innovator John Deere. Jason Wallin, senior principal architect for ‘TechStack’ at Deere & Company, makes the case that industrial AI and private 5G reinforce each other within an Industry 4.0 context — where the former drives smarter operations on the factory floor, and latter provides the deterministic connectivity to support it. See what “practical AI deployments” look like on factory floors (for quality control, predictive maintenance, process optimization), and what’s on the horizon with AI retrieval-augmented (RAG) assistants, data governance, and edge compute. As enterprises deploy AI confidently across industrial environments, they will unlock productivity, efficiency, and resilience at scale.