AI Investment in Telecom Faces Reality Check as Revenue Growth Lags
The massive wave of artificial intelligence investment currently sweeping the global telecommunications industry may be heading for a significant reality check, as operators struggle to translate technical hype into tangible bottom-line revenue growth. While AI has dominated recent industry agendas, including summits like the Mobile World Congress, experts warn that the spending spree could cool within years if companies cannot advance beyond simple experimentation.
Operational Efficiency vs. Revenue Generation
Martin Creaner, Director General of the World Broadband Association, highlighted during the Africa Hyperscalers Conversation series that while AI-enabled products are now ubiquitous, the industry is primarily using them for a familiar goal: cutting costs. For the last twenty years, telecom has focused on reducing costs to maintain profitability, Creaner said. Attempts to generate new revenue streams have often struggled. For an industry plagued by flat revenue growth, the appeal of using AI to automate network operations and detect faults is clear. However, Creaner argued that efficiency alone will not sustain the current level of investment.
The industry is currently operating across three strategic dimensions, but only one determines long-term viability. These are:
- Operational Efficiency: Reducing overhead, which is the current focus.
- Customer Experience: Improving retention and service quality.
- Revenue Growth: Creating entirely new services.
The scale of the conversation has been extraordinary, Creaner remarked, noting that every vendor and operator has pivoted to an AI-first strategy. Yet, he cautioned that the economic model remains shaky. The industry's challenge is that while AI can improve efficiency relatively quickly, revenue-generating applications often take longer to mature.
New Revenue Streams and Future Risks
According to Creaner, telecom operators are currently pivoting toward GPU-as-a-service, gaming infrastructure, and enterprise cloud platforms to justify their AI spend. However, he stressed that if these new revenue streams fail to scale, the industry risks repeating previous technology cycles where capital expenditure far outpaced commercial returns. As the experimentation phase matures, the next 24 to 36 months will be a defining period. Telecom leaders are increasingly aware that if they cannot prove AI can grow the top line, not just trim the bottom line, the spending boom may face a sharp correction.
The Rise of Agentic AI and Contract Negotiation
Creaner further noted that the next phase of AI may not simply recommend products or generate content, but could negotiate on behalf of consumers, reshaping how everyday services are bought, priced, and delivered. He explained that agentic AI, a new class of autonomous digital assistants capable of making decisions and acting on behalf of users, could fundamentally alter consumer contracts across industries such as telecom, insurance, utilities, and finance.
Instead of signing long-term service agreements, consumers may soon rely on AI agents to secure and renegotiate services dynamically, sometimes daily or weekly, based on price, quality, and personal preferences. Once you're using agents for contract negotiation, a 12-month contract doesn't make sense anymore, Creaner said. You might end up with one-day phone contracts, one-week health insurance, or one-hour or one-month travel insurance – whatever fits.
For decades, consumer services have relied on fixed-term contracts to stabilize revenue and reduce administrative complexity. Telecom operators, insurers, and utilities typically lock customers into multi-month or multi-year agreements even as consumer needs fluctuate. By continuously monitoring prices, network performance, service quality, and user preferences, AI agents could renegotiate contracts in real time, switching providers or adjusting plans automatically. The agents will be constantly renegotiating all of my outgoings to optimize my spend, Creaner said.
Trust as a Deciding Factor
He noted that such a shift could compress the lifecycle of consumer contracts dramatically, saying telecom subscriptions might become daily services. Insurance policies could be activated only when needed, and utilities might dynamically adjust tariffs based on consumption patterns. While many of the world's most powerful AI systems are currently being developed by global technology companies, the institutions that ultimately deploy agentic AI for consumers may be very different. Creaner argued that trust, not just technological capability, will determine who controls these agents. When you're being asked to trust an agent with something as sensitive as your investment portfolio – and to have it negotiate every contract you have – trust becomes the deciding factor, he said.
