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According to Developing Telecoms, artificial intelligence (AI) continues to dominate discussions in the telecom industry, but concerns about unclear strategies and lack of measurable returns are mounting. Despite the enormous investments and pressure to integrate AI tools, many operators are struggling to demonstrate tangible benefits, fueling speculation about an AI ‘investment bubble.’

AI Adoption in Telecoms: Key Challenges and Trends

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AI adoption in the telecoms sector is largely characterized by exploratory projects and proofs of concept, rather than initiatives delivering significant operational outcomes. Opanga CEO Cole Brodman highlighted that while AI has transformative potential, operators are failing to connect it to practical use cases like network optimization or energy efficiency. According to Brodman, AI can address key challenges such as improving spectral efficiency, reducing congestion, and enhancing customer experiences when tied to meaningful data sets. These targeted applications are crucial for realizing AI’s full value in the industry.

ADG CIO Cliff de Wit echoed similar concerns, criticizing the trend of ‘jumping on the AI bandwagon’ without a strategic plan. Larger telecom giants often hire data scientists without defining clear problems for AI to solve, leading to poorly defined success metrics. On the other hand, emerging market operators are taking a more pragmatic, ROI-focused approach to AI deployments, which appears to yield better results in specific use cases.

The Broader Industry Context: AI’s Role in Telecom Transformation

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The telecom industry is not alone in its AI challenges. As global hyperscalers like Amazon, Microsoft, and Alphabet race to dominate AI development, the sector is caught in what Matt Walker from MTN Consulting describes as an AI ‘gold rush.’ Investments in AI have skyrocketed, but a winner-takes-all mentality has exacerbated fears of a bubble. Walker points out that excessive capital expenditures are not yielding proportional revenue growth, especially in contrast to Chinese AI models like DeepSeek and Alibaba Qwen, which are delivering competitive results with lower investments.

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For telecoms, particularly in emerging markets, high AI implementation costs and elevated risks of failure underscore the need for a disciplined investment strategy. Companies that focus on high-impact areas like operational efficiency or bandwidth optimization will likely see the most measurable returns. However, smaller players risk being left behind if they cannot meet the scale or sophistication of hyperscaler initiatives, creating further market imbalances.

Future Outlook: Pragmatism Over Hype

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While there is significant criticism of AI investments lacking clear ROI, industry experts suggest that a more structured approach could unlock the real value of AI. De Wit believes the industry is moving through Gartner’s hype cycle, transitioning from inflated expectations to a more grounded application of the technology. This ‘sanity check’ is especially pertinent for operators in regions like Africa, where budget constraints necessitate precision in deploying AI for high-impact projects.

Brodman advocates for prioritizing practical AI solutions—such as network automation and cost-reducing technologies—that offer immediate benefits to emerging markets. With economic stress weighing heavily on these regions, AI investments must address familiar, solvable challenges such as energy consumption reductions or real-time network visibility to avoid falling into the ‘solution in search of a problem’ trap.

Walker warns that scaling indiscriminately will only further exacerbate the bubble. He critically notes signs of over-leveraging, lack of profitability metrics, and circular financing among major US firms driving AI innovation—all of which could create economic vulnerabilities if the investment bubble bursts. He advises operators to evaluate Chinese-developed models and diversify AI adoption strategies to mitigate their risks.

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Is the Telecom AI Hype Sustainable?

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As the hype surrounding AI continues to grow, telecom operators must take a measured and ROI-oriented approach to their investments. While AI clearly holds the potential to revolutionize network operations and customer experiences, the lack of strategic alignment in its application is causing many players to struggle with demonstrating returns. Emerging markets, in particular, have a significant opportunity to take the lead by focusing on practical AI solutions that address immediate operational needs.

What’s your perspective? Is AI set to transform telecoms, or will the investment bubble burst before real returns are observed? Join the conversation below!

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