AI spending boom in telecom may face a reality check – World Broadband Association DG

The surge of investment in artificial intelligence across the global telecom industry may not last indefinitely. While AI currently dominates boardroom conversations and industry conferences, some telecom leaders caution that the spending wave could slow within a few years as companies confront the challenge of turning experimentation into sustainable business models.

According to Martin Creaner, Director General of the World Broadband Association during the Africa Hyperscalers Conversation series, the telecom sector is still in the early stages of understanding where AI will generate real economic value.

Speaking about discussions at recent industry gatherings including the Mobile World Congress, Creaner said AI has rapidly become the focal point of telecom strategy, but the industry is still exploring how to translate that excitement into revenue growth.

“Everyone expected AI to be important, but the scale of the conversation around it has been extraordinary,” Creaner said. “Every vendor had an AI-enabled product. Every operator was discussing AI.”

Much of the initial investment, however, has been driven by the promise of efficiency gains. Telecom companies have been exploring AI to automate network operations, improve fault detection, and reduce operational costs across complex infrastructure systems.

For an industry that has spent two decades focused on cost control, those efficiency gains are appealing. Telecom revenues in many markets have remained largely flat, forcing operators to prioritize operational improvements over expansion.

But Creaner notes that the next phase of AI investment will depend on something telecom operators have historically struggled to achieve: meaningful new revenue streams.

“For the last twenty years telecom has focused on reducing costs to maintain profitability,” he said. “Attempts to generate new revenue streams have often struggled. Industry growth has been relatively flat.”

AI could eventually change that equation by enabling new digital services, advanced enterprise platforms, and network-based AI offerings. Telecom operators are already experimenting with AI-powered services in areas such as enterprise cloud platforms, data analytics, gaming infrastructure, and GPU-as-a-service.

Yet the economic model remains uncertain.

The industry’s challenge is that while AI can improve efficiency relatively quickly, revenue-generating applications often take longer to mature. If telecom companies fail to demonstrate clear returns on their AI investments, spending could slow as executives reassess priorities.

That potential adjustment may arrive within the next few years.

As Creaner explained, telecom leaders are increasingly aware that AI strategies must move beyond operational optimization toward improving customer experience and creating new services that generate revenue.

“There are really three dimensions to how the industry is thinking about AI,” he said. “The first is efficiency. The second is improving customer experience. But the third – and the one that matters most – is revenue growth.”

That final dimension remains the most uncertain.

Telecom operators are still searching for scalable AI-enabled services that customers will consistently pay for. Without those services, the current wave of investment could resemble earlier technology cycles where enthusiasm outpaced commercial returns.

For now, however, the industry remains firmly in the experimentation phase.

AI dominates telecom strategy discussions from network automation to enterprise platforms and digital services. Operators, vendors, and investors all see the technology as a potential catalyst for industry transformation.

But whether that transformation ultimately delivers sustained revenue growth may determine how long the current AI spending boom continues.