Are Telecoms Facing an AI Bubble? Experts Discuss Strategies for Real Returns

According to Developing Telecoms, the telecom sector’s growing investment in artificial intelligence (AI) is raising critical questions about the lack of measurable returns. While AI is touted as a transformative force, experts argue that operators are struggling to connect these investments with tangible value, fueling concerns of an impending ‘AI bubble.’

The Announcement: AI Investments May Lack Strategic Focus

Major telecom operators are doubling down on AI to showcase innovation, but experts highlight a key issue: many of these investments lack clear metrics and strategic alignment. Cole Brodman, CEO at Opanga, believes that while AI has potential, much of the spending seems to focus on exploratory projects like dashboards and tools that fail to address core network problems.

“Areas like spectral efficiency, congestion reduction, and energy savings should lead the AI agenda,” says Brodman. “AI can solve real network issues, but many operators are not applying it effectively to deliver measurable ROI.” He adds that AI-driven operational efficiencies, such as pinpointing network faults or improving customer experiences, can create immediate cost-saving opportunities—especially critical in emerging markets where financial pressures loom larger.

Meanwhile, Cliff de Wit, CIO of ADG, warns that many firms invest in AI projects without defining core problems or clear goals. He explains that larger companies often create AI-centric teams but fail to provide actionable direction, resulting in diluted outcomes. De Wit suggests that smaller, more pragmatic firms may find better success by implementing AI solutions tailored to specific challenges.

Market Context: Is AI Investment Fueling a Bubble?

The telecom industry’s AI ambitions echo similar investment booms in other sectors, leading experts like Matt Walker of MTN Consulting to voice caution. He compares the current AI craze to a gold rush, where the fear of missing out (FOMO) drives unchecked spending. “Operators are chasing broad AI use cases without clear profit visibility. There’s a ‘winner takes all’ mindset, but inflated expectations could lead to significant financial pitfalls,” says Walker.

Walker also draws parallels between AI investments and the cloud computing “land grab” era, noting that while hyperscalers like Amazon, Google, and Microsoft gained ground with tangible assets, AI investment outcomes remain uncertain. Emerging technologies such as DeepSeek and Alibaba’s Qwen have demonstrated competitive results with far lower investment costs, putting additional pressure on Western telecom operators to justify their ballooning budgets.

Emerging markets face distinct challenges. Companies in Africa and Southeast Asia often operate under tighter economic constraints, making unmeasured AI spending a risky proposition. Brodman underscores the need for practical, cost-effective AI implementations in these regions, emphasizing that results must outweigh risks.

Future Outlook: Moving Beyond the Hype Cycle

De Wit and Brodman agree that the hype surrounding AI may settle as pragmatic use cases emerge. De Wit likens the current AI swell to the Gartner Hype Cycle, where inflated expectations eventually give way to disillusionment—but also pave the way for meaningful adoption. He notes a shift in emerging markets where businesses are now identifying specific, measurable problems that AI can solve before investing heavily.

Brodman stresses the importance of prioritizing solutions aligned with measurable returns, particularly for network optimization and customer experience improvements. “Emerging market operators must focus AI spending on projects that ensure swift cost reductions and superior ROI,” he advises.

Walker takes a more cautious stance, warning that signs of an AI bubble are becoming evident: hidden financing mechanisms, lack of profitability metrics, and unsustainable spending sprees. He predicts that while some operators may succeed, others risk being left behind with unrealized solutions and sunk costs.

Conclusion: Pragmatism Key to Avoiding the AI Pitfalls

Telecom operators stand at a crossroads as the AI bubble continues to inflate. While investment in AI holds potential for transformative changes, a lack of strategic focus and measurable returns could derail this momentum. For emerging markets especially, Brodman and De Wit stress that a cautious, purpose-driven approach is essential to ensure AI investments create tangible value without sinking finances.

What’s your take on the AI investment hype? Should telecom operators pull back until profits match expectations, or is bold risk-taking necessary for long-term transformation? Share your thoughts in the comments below!