AI spending in telecom to increase threefold by 2025: Report

The buzz around Artificial Intelligence (AI) is not just hype anymore, especially within the demanding world of Telecommunications and Cloud Service Providers across the Asia-Pacific (APJ) region. According to the latest IDC CIO Playbook 2025, commissioned by Lenovo, Asia-Pacific telecommunications and CSPs are moving beyond pilot projects to embed AI at scale, fueling network optimisation, predictive maintenance, and richer customer experiences. 

The AI adoption signal: Strong but still connecting

While the potential is clear, the report reveals the sector is still navigating the early-to-mid stages of AI integration. A significant 40% of Telcos or CSPs are currently supporting pilot projects or use cases, with another 10% in the early stages of development. Only 11% report systematic adoption across the enterprise, while 20% are planning to start within the next 12 months, and 19% are still evaluating.

This cautious-but-accelerating adoption comes with hefty expectations and a significant financial commitment. According to the report, Telcos and CSPs anticipate a remarkable 3.6x growth in AI spending as a percentage of their total IT budget between 2024 and 2025. 

Reportedly, in the next 12 months, GenAI is set to capture 40% of AI implementation efforts, indicating a strong prioritisation of its capabilities for tasks like automation and content creation.

However, Interpretive AI, crucial for understanding patterns and anomalies like network issues, remains a major focus, accounting for 36% of planned implementations, down from 74% in the past year, but still substantial. Predictive AI, used for forecasting and maintenance, also holds significant priority at 24%.

This distribution highlights that while GenAI is the fastest-growing area, Telcos require a blend of AI types to address their complex operational needs. The primary investment areas underpinning this growth across APJ are foundational: data science, AI-ready cloud and edge infrastructure, and robust data management and governance frameworks.

Why AI? Priorities shifting beyond the network core

The investments now are no longer just about network speeds. For 2025, the top business priorities for Telcos and CSPs leveraging AI are around improving sustainability, reducing business risk and cyber threats, increasing business agility and responsiveness, optimising supply chain or inventory and improving customer experience and satisfaction.

From Back Office to Customer-Facing

The report highlights where AI is making inroads initially. The top 5 business functions adopting AI use cases are:

1. IT Ops

2. Legal

3. Supply Chain

4. Engineering or Research and Development

5. Marketing

Roadblocks Ahead: Data, Budgets, and Scale

Despite the momentum, significant hurdles remain. The top inhibitors preventing AI projects from meeting expectations include:

1. Data quality issues: The single biggest roadblock, hindering reliable AI outcomes.

2. Lack of budget or management buy-in

3. Challenges include deploying AI at endpoints while integrating AI effectively into edge devices and distributed networks.

4. IT infrastructure or network costs, like the expense of building and maintaining AI-ready systems.

5. Challenges include scaling AI across the enterprise and moving beyond pilots to widespread, integrated deployment.

Infrastructure choices: The hybrid imperative

Where will these demanding AI workloads run? The report shows a clear preference for control and compliance. A dominant 67% of Telcos or CSPs primarily use on-premises, private, or hybrid cloud solutions for their AI workloads, compared to just 25% relying mainly on public cloud. This suggests the need to manage sensitive data, meet regulatory requirements, and address network latency concerns inherent in the sector.

The outlook: AI as the new network standard

For Telcos and CSPs in the APJ region, AI is transitioning from a 'nice-to-have' to a fundamental component of future operations. While challenges around data quality, integration, cost, and scaling are significant, the strategic imperatives, from sustainability and risk reduction to customer experience and agility, are too compelling to ignore.

Here, the success will depend on building strong data foundations, choosing the right infrastructure mix, predominantly hybrid, fostering internal skills, and leveraging strategic partnerships to navigate the complexities of deploying AI effectively and responsibly across their vast networks. 

The race is not just about connectivity anymore; it's about intelligent connectivity.