While AI training is data-center-intensive, Cisco's CEO sees the move to AI inference as a massive growth opportunity. Inference will happen at distributed edge locations to be close to users, requiring robust, high-performance networks to connect everything, which plays directly into the company's core strengths.

Direct AI disruption is a minimal concern for telecom companies. The more significant threat comes from hyperscalers like AWS and Azure, which already dominate Europe's B2B cloud market with an 85% share. The real risk is these giants leveraging their cloud infrastructure to enter the B2C telecom space via virtualized networks.

The proliferation of sensors, especially cameras, will generate massive amounts of video data. This data must be uploaded to cloud AI models for processing, making robust upstream bandwidth—not just downstream—the critical new infrastructure bottleneck and a significant opportunity for telecom companies.

Unlike 4G/5G revolutions driven by consumer video, 6G will be defined by its utility for enterprise AI applications. Key advancements will be in managing network performance, reducing latency, and adding security layers crucial for business, rather than just increasing consumer bandwidth.

Despite attempts to articulate an AI strategy, the telecom sector is largely seen as a non-participant in the current AI boom. From a stock market perspective, investors are selling positions in telcos to finance investments in high-growth AI companies, effectively making the telecom industry an involuntary funding source for the trend.

In 2026, the AI investment narrative will expand from foundational model creators to companies building applications and services. It also includes sectors enabling AI growth, such as energy generation and data centers, offering a wider range of investment opportunities beyond the initial tech giants.

The recent economic push for AI to demonstrate a clear return on investment is not new to the edge AI space. Edge applications have always been driven by strict cost and productivity constraints, fostering a culture of rational, value-focused development that the broader AI world is now adopting.

AI enables companies to sell outcomes rather than just product usage. To do this profitably, they need greater control over the entire delivery process. This is driving a trend of vertical integration, where companies expand into adjacent parts of the value chain to own the end-to-end experience and capture more value.

Qualcomm's CEO argues that real-world context gathered from personal devices ("the Edge") is more valuable for training useful AI than generic internet data. Therefore, companies with a strong device ecosystem have a fundamental advantage in the long-term AI race.