The telecommunications industry in Indonesia, a vital backbone of the nation’s digital economy, is currently undergoing a major transformation. It is a giant industry with an estimated market size of USD 18.12 billion in 2025, projected to reach USD 23.97 billion by 2030, growing at a CAGR of 5.76% during the forecast period (2025–2030). This growth has been mainly caused by a possible increase in users. However, it may also be fueled by more revenue per user as the nation's earnings rise.

As the sector becomes more competitive and customer expectations evolve rapidly, traditional planning and forecasting methods have proven to be inadequate. In 2025 and beyond, telecommunications companies must move beyond manual, outdated planning approaches and utilize Machine Learning and AI-driven solutions to remain relevant.

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The Limits of Traditional Planning

Indonesian telecom operators have historically relied on manual planning systems that are siloed, disconnected from real-time conditions, and incapable of accounting for volatile variables such as inflation, regulatory shifts, and sudden surges in demand. These outdated practices often lead to reactive rather than proactive decision-making, causing inefficiencies in both capital and operational expenditures, and .and result in the company being unable to keep up with dynamic market changes. Moreover, despite having vast volumes of customer and operational data, Indonesian telcos often underutilize this resource. The result is a lack of agility and foresight, particularly in revenue forecasting, cost optimization, and risk management.

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Global Trends in Leveraging Artificial Intelligence (AI) and Machine Learning (ML)

Globally, telecommunications companies are leveraging Artificial Intelligence (AI) and Machine Learning (ML) to revolutionize planning and forecasting processes. These technologies enable real-time data analysis, predictive modeling, and scenario planning, allowing for more agile and informed decision-making.

These trends are supported by the use of Big Data, which can now be collected from various sources such as:

• Customers: Usage behavior, payment history, service feedback, and churn signals.

• Government: Regulatory updates, infrastructure data, and population statistics.

• Third-party Data Providers: Market research, economic forecasts, and location-based trends.

• IoT Devices: Network sensors, smart devices, and infrastructure telemetry.

• Call Detail Records (CDRs): Information about each call, such as the caller’s and recipient’s phone numbers, call duration, time of call, and location data.

Analyzing this vast amount of data allows telecom companies to gain valuable insights and make informed decisions. These data—when aggregated and structured—serves as the fuel for Machine Learning (ML) models. The models learn from historical patterns to recognize relationships, detect anomalies, and forecast future outcomes. This capability forms the foundation of predictive analytics.

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Board's Foresight: Empowering Strategic Planning

To support Indonesian telecom operators in this shift, Board’s “Foresight” platform offers a comprehensive suite of tools designed to transform planning into a strategic, forward-looking function. Built on a foundation of AI, econometric modeling, and real-time global data integration, Foresight empowers decision-makers with capabilities previously accessible only to the world’s most advanced telcos. With Foresight, companies can anticipate dynamic market shifts and plan confidently by utilizing more than 5 million datasets and advanced analytics.

The practical applications of Board's Foresight in the telecommunications sector are manifold:

• Global Intelligence Cloud: Access to 5.5M+ global datasets across 10K+ sources, 168 industries, and8 macro sectors. Helps telcos contextualize decisions within global and local trends.

• AI-Powered Correlation Engine: Automatically identify which external variables (e.g., inflation, interest rates) are most impactful to KPIs like churn or Average Revenue per Unit (ARPU).

• Hypothesis Testing and Validation: Enables exploration of "what-if" questions using visual analytics—vital for market response strategies and CAPEX planning.

• Advanced Predictive Analytics: Runs AI/ML models and econometric simulations in minutes to forecast revenue, churn, or OPEX.

• Integrated Intelligence: Combines internal planning with external signals—supporting budget alignment, resource planning, and cross-departmental collaboration.

• Macroeconomic Intelligence with Gen AI Explainability: Allows telcos to simulate effects of economic events (e.g., wage increases, tariffs), with natural language explanations from Generative AI.

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Conclusion: Embracing the Future of Telecom Planning

The integration of AI-driven planning and forecasting tools is no longer a luxury but a necessity for Indonesia's telecommunications industry and other sectors. By adopting platforms like Board's Foresight, companies can transition from reactive to proactive strategies, ensuring resilience and competitiveness in a rapidly evolving landscape. As Indonesia's digital economy matures, tools like Foresight will become indispensable for telcos striving to lead—not follow—within a dynamic, data-driven world.

Talk to our expert

Hananto Pandu SE., S.Kom., Ak., CA., CPA., ASEAN CPA. - 0896 3626 1684

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Best Regards,

Yohannes Ekaputra Sananto SE.

yohannes.sananto@sazankahenig.com

Financial Product Consultant

PT Sazanka Henig Solusi

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