Mobile’s next US$4.5 trillion won’t come from connectivity

The GSMA's Mobile Economy 2026 report reveals that mobile technologies and services contributed $7.6 trillion to global GDP in 2025, or 6.4 percent of total economic output. This figure is projected to increase to $11.3 trillion, or 8.4 percent by 2030. During the same period, operator revenues are expected to rise from $1.19 trillion to $1.36 trillion, with $1.2 trillion committed to capital expenditures in between.

The sector generates roughly $3.7 trillion in economic value over five years, while operators generate about $170 billion in revenue and spend $1.2 trillion to enable this value creation. This value, however, is not reflected in the profit and loss statements of the businesses that facilitate it. The report suggests that the industry has shifted from a connectivity-centric model to a focus on digital platforms and data-driven innovation.

Currently, 45 percent of operators consider new digital revenue streams as a strategic priority. The challenge lies in identifying where the value is being lost in the mobile ecosystem. In high-engagement markets, daily mobile use is extensive, and operators primarily monetize a small portion of this usage, such as minutes spent topping up, checking balances, or paying bills.

The remaining daily activity occurs on infrastructure built and maintained by operators, but which is not directly monetized by them. Other sectors face similar issues, such as financial services and gaming, where transaction-based products struggle to capture value from the hours spent by users outside of these transactions. The standard solutions to address this issue involve increasing user attention rather than generating sustainable revenue.

Price promotions and content bundles are effective in buying usage during their validity but do not create long-term value. Additionally, these approaches do not change the behavior of users during the periods when operators are not directly involved. The root of the problem lies in the measurement and attribution of value. Operators often cannot determine which specific in-app behaviors lead to retained subscribers due to the lack of systematic data collection.

Similarly, the AI models used in operator strategies are trained on billing records and network telemetry but cannot predict alternative actions that could prevent churn, as these actions were not instrumented. The global usage gap between people with coverage and those who do not use mobile internet stands at 38 percent, while the coverage gap is only four percent.

This discrepancy is not due to a lack of network infrastructure but rather an incentive and participation gap. The retail industry provides a useful precedent for addressing this problem. Online retail existed for years before it scaled due to the absence of a unified settlement system. Card networks, gateways, and standardized payment processing transformed a collection of isolated experiments into a robust infrastructure, enabling commerce to grow.

The current challenges in the mobile ecosystem are primarily at the attribution and measurement stage. Operators, wallets, and platforms need to develop a unified framework that sits between users and existing services without replacing them. This framework should work across sectors, as users' behaviors do not adhere to the boundaries between different applications or services.

Crucially, it should attribute outcomes to specific interactions, enabling partners to trace which actions led to commercial results. Most importantly, this approach should not require users to change their behaviors, as large-scale behavior change is notoriously difficult to achieve. Looking ahead to 2027, operators, wallets, and platforms should be able to answer three key questions.

What percentage of users' daily device time is currently spent on services that generate revenue for the operator, and how is this ratio evolving? Which specific behaviors within their applications are predictive of user retention, determined through data analysis rather than intuition? How should they evaluate the effectiveness of engagement initiatives, ensuring that any metrics used accurately reflect the impact on revenue generation?