This article is part of the monthly APAC AI Radar series, highlighting recent AI innovations and key company updates from various companies across the Asia Pacific. This edition will dive into Indonesia and their latest AI deployments to support business executives. Read more and uncover how Indonesia’s technology leaders aim to shape their AI initiatives and strategic plans.

Deployment/Initiatives

Blibli has launched its AI-powered Instant Return Solution to streamline product returns. By automating damage detection and return recommendations, the system reduces return handling time by 50%, improving operational efficiency. With over 47,800 return points nationwide, the solution enhances customer satisfaction through faster, more convenient returns.

BRIBRAIN, an AI-driven platform by PT Bank Rakyat Indonesia (BRI), enhances customer engagement and operational efficiency through AI and big data analytics. Its AI Recommendation System boosts conversion rates by 60% and improves debtor acquisitions by 49%, while contributing to BRImo’s growth to 31.6 million users and IDR 4.158 trillion in transactions.

AeroBuddy, an AI-powered platform by PT Angkasa Pura II, integrates real-time data to enhance airport operations. It allows personnel to generate operational plans in just one minute, improving decision-making speed and accuracy, and optimizing coordination through advanced analytics.

CLIK leverages AI to enhance credit scoring and risk management by analyzing alternative data, such as transaction history and social behaviors. Its AI-driven solutions, including Soft-Pull Credit Reports, CLIK Spectrum, and predictive alerts, streamline decision-making and provide more accurate, data-driven insights for financial institutions.

Kalbe Farma integrates AI across its operations, enhancing drug discovery, predictive maintenance, demand forecasting, quality control, and sales optimization. These AI applications improve operational efficiency, streamline processes, and enhance precision across production, quality control, and sales.

Introduction: Indonesian AI Market Landscape

Indonesia’s digital economy is accelerating rapidly, with artificial intelligence (AI) becoming a cornerstone of this growth. By 2030, AI is projected to contribute USD 366 billion to the nation’s GDP, positioning Indonesia as a leader in the global digital economy. The country already ranks as the third-largest global user of AI, with investment in generative AI alone surging from USD 4 billion in 2021 to USD 25 billion in 2023. According to the IMF’s AI Preparedness Index 2024, Indonesia outperforms regional peers such as Malaysia and India in digital infrastructure, innovation, human capital, and regulatory frameworks—key enablers for sustained AI-driven growth.

Recent AI developments reflect Indonesia’s commitment to digital transformation. The launch of Sahabat AI, a homegrown large language model (LLM), underscores efforts to bridge linguistic diversity and foster local innovation. Spearheaded by Indosat, GoTo, and NVIDIA, this initiative leverages advanced AI capabilities to empower local businesses, government agencies, and education. Complementing this is NVIDIA’s GPU Merdeka cloud service, providing cutting-edge AI infrastructure tailored to Indonesia’s needs. With plans to train 20,000 students and a $200 million investment in an AI center in Surakarta, NVIDIA’s commitment reinforces the nation’s goal of becoming an AI hub in Southeast Asia.

As AI reshapes industries, its transformative potential is being realized in sectors such as financial services, healthcare, agriculture, and aviation. From optimizing supply chains and improving credit scoring to enabling predictive healthcare solutions, AI’s influence is driving innovation across the board. Yet, challenges in infrastructure, talent, and regulation remain, requiring continued collaboration and investment. To explore these advancements and their impact, Twimbit AI Radar: Indonesia Edition showcases the latest AI use cases across industries, highlighting innovations that are shaping the country’s future. This edition focuses on key sectors, including financial services, agriculture, and aviation, offering a comprehensive view of how Indonesia is leveraging AI to accelerate its digital ambitions.

Instant Return Solution with AI: Blibli’s Smart Return Process

Blibli, one of Indonesia’s leading e-commerce platforms, has launched its Instant Return Solution, an AI-powered feature designed to simplify and accelerate the product return process. This solution leverages Artificial Intelligence (AI) and Machine Learning (ML) to provide customers with a quick, seamless return experience.

The process is straightforward for customers: after submitting a return request through the Blibli app or website, they upload a photo of the product. Blibli’s AI Damage Product Detection then automatically inspects the item’s condition, while the AI Auto Solution Recommendation uses customer data and product policies to provide personalized return options. This allows customers to process returns independently, with minimal effort.

How is it ranked?
⚙️ Operational Transformation ●●●○○

Commentary
Blibli’s Instant Return Solution demonstrates a noticeable operational impact by automating the damage detection and solution recommendation process. The AI platform has reduced return handling time by nearly 50%, showcasing its efficiency in improving workflows.

The solution’s nationwide accessibility, with over 47,800 return points across Indonesia, further highlights its scalability and ability to streamline return operations on a large scale. The improvement in customer satisfaction, due to faster resolution times, also reflects significant gains in operational efficiency and resource management.

Overall, the solution exemplifies operational transformation by optimizing internal processes and enhancing the customer experience at scale, contributing to Blibli’s ongoing commitment to innovation.

BRIBRAIN: Revolutionizing Banking with AI-Driven Innovation

BRIBRAIN is an AI-driven platform developed by PT Bank Rakyat Indonesia (BRI) as part of its digital transformation. It integrates AI and big data analytics to enhance customer engagement, improve operational efficiency, and support decision-making across the bank’s services. Since its implementation, BRIBRAIN has developed over 107 use cases across 13 BRI products, driving innovation in multiple areas of the bank’s operations.

One of the standout features of BRIBRAIN is the AI Recommendation System, which is used both internally and externally. Internally, the system analyzes customer data, including transaction history, demographics, and savings patterns, to identify potential clients and offer personalized product recommendations. This allows sales teams to engage with clients in a more targeted and effective way. Externally, within the BRImo mobile banking app, AI is utilized to provide transaction recommendations and customized product offers, further enhancing personalization for each user.

How is it ranked?
⚙️ Strategic Innovation ●●●●○

Commentary

BRIBRAIN has made a substantial impact on both customer engagement and operational efficiency through its AI and big data analytics. The AI Recommendation System has resulted in a 60% increase in conversion rates and a 49% improvement in the quality of debtor acquisitions, demonstrating its effectiveness in driving sales and improving customer targeting.

Furthermore, BRIBRAIN has played a key role in the growth of BRImo, helping transform it into a super app. As of December 2023, BRImo reached 31.6 million users with a transaction volume of IDR 4.158 trillion, growing 55.8% year-on-year, which underscores the platform’s significant impact on BRI’s digital transformation.

BRIBRAIN is categorized as Level 4: Strategic Innovation due to its transformative impact on BRI’s operations, enhancing both internal processes and customer engagement through personalized services. However, while these improvements mark a significant shift for BRI, the platform does not yet disrupt the entire banking industry or create new business models, which would characterize Level 5: Industry-Wide Disruption. It remains focused on optimizing existing operations rather than reshaping the sector as a whole.

Through BRIBRAIN, BRI continues to lead the way in AI-powered banking, enhancing both customer satisfaction and operational performance. As BRI continues to expand its use of AI across various aspects of its services, it sets a strong example of how digital transformation can shape the future of the banking industry.

AeroBuddy AI Platform: Enhancing Airport Operations with Artificial Intelligence

PT Angkasa Pura II (AP II), the company managing airports in western Indonesia, including Jakarta, has introduced AeroBuddy, an AI-powered platform that integrates operational data across its airports. AeroBuddy acts as a smart assistant, leveraging AP II’s big data to provide real-time, data-driven insights to personnel, aiding in quicker and more accurate decision-making for efficient airport operations.

AeroBuddy comes with several advanced features designed to support seamless airport operations:

• Real-time data analysis: Provides comprehensive insights by analyzing operational data in real time.
• Advanced analytics: Processes large datasets to deliver actionable insights for decision-making, including predictive and prescriptive analysis.
• Operational plan generation: Empowers personnel to generate operational plans in just one minute, accelerating decision-making processes.

How is it ranked?
⚙️ Operational Transformation ●●●○○

Commentary

AeroBuddy has significantly impacted AP II’s airport operations by improving the speed and accuracy of decision-making. The platform enables operational plans to be generated in just one minute, reducing the time spent on these tasks from hours to minutes, optimizing response time. Its real-time data analysis and advanced analytics help enhance decision-making and collaboration, particularly by improving coordination at the Airport Operation Control Center (AOCC). Personalized notifications further support real-time management, ensuring that relevant information reaches stakeholders when needed most.

While AeroBuddy optimizes operational workflows, it doesn’t create a company-wide strategic shift or disrupt the aviation sector, which would define Level 4. It enhances efficiency within existing processes but doesn’t fundamentally alter the business model, placing it at Level 3.

By introducing AeroBuddy, AP II has set a pioneering example of AI usage in Indonesia’s aviation sector, demonstrating the transformative power of AI in optimizing public service operations and enhancing the efficiency of airport management.

Kalbe Farma’s AI: Revolutionizing Healthcare Processes

PT Kalbe Farma Tbk, a leading healthcare company in Indonesia, is integrating artificial intelligence (AI) into various aspects of its operations, from research to sales. According to Edwin Simjaya, Head of Kalbe’s AI Center, the company is pioneering AI initiatives to address unmet medical needs and optimize processes across its business lines. Key AI-powered features include:

• Drug Discovery: Leveraging AI to develop treatments for diseases currently without effective medications.
• Predictive Maintenance: Using IoT devices and AI models to monitor and predict potential machinery failures, ensuring seamless production.
• Demand Forecasting: Applying AI to predict medication needs, such as increased demand for Promag during Idul Fitri, enabling better raw material purchasing.
• Quality Control: Employing AI vision systems with cameras to ensure the accuracy and consistency of drug formulations.
• Sales Optimization: Developing AI-based recommendation systems to align product offerings with target market preferences.

How is it ranked?
⚙️ Operational Transformation ●●●○○

Commentary

Kalbe Farma’s AI applications, such as drug discovery, predictive maintenance, and demand forecasting, have significantly improved operational efficiency and responsiveness. These initiatives streamline processes and enhance precision across production, quality control, and sales.

Although drug discovery is transformative, its impact remains part of Kalbe’s broader operational framework rather than an industry-disrupting force. This positions Kalbe’s AI integration at Level 3: Operational Enhancement, focusing on operational improvements without reshaping the entire industry.

Kalbe’s AI-driven advancements highlight the company’s commitment to innovation and efficiency, setting a strong foundation for future growth in the healthcare sector.

CLIK Credit AI: Smarter Scoring for Financial Institutions

CLIK (PT CRIF Lembaga Informasi Keuangan) is a private credit bureau in Indonesia that provides innovative solutions for financial. It offers services like credit scoring, alternative data analysis, and risk management tools. By leveraging AI, CLIK helps financial institutions manage risk and meet customer expectations through intelligent insights.

Soft-Pull Credit Reports
AI quickly assesses potential risks by analyzing alternative data, such as transaction history and social behaviors, without impacting a customer’s credit score. Machine learning models predict creditworthiness based on this data, offering a risk-free evaluation.

CLIK Spectrum
AI and alternative data sources, including telecommunication and financial histories, are used to generate a comprehensive credit score. Machine learning algorithms process diverse data to create a more complete understanding of a customer’s credit behavior, going beyond traditional metrics.

Portfolio Alert System
Using predictive analytics, the system proactively monitors customer data for changes, detecting emerging risks and sending customizable alerts.

CLIK Dashboard
AI-driven analytics are applied to real-time data, transforming it into interactive visual insights. Customizable statistical displays assist financial institutions in making faster, data-driven decisions by highlighting key trends and anomalies.

How is it ranked?
⚙️ Operational Transformation ●●●○○

Commentary

CLIK’s AI-driven solutions enhance how financial institutions evaluate and manage credit risk. By analyzing alternative data and leveraging machine learning, CLIK refines the way creditworthiness is assessed, providing more nuanced insights and early alerts for potential risks. These improvements streamline decision-making and support more precise financial assessments. However, while these innovations significantly improve credit risk management, they still operate within the existing financial structure, making them more of an operational enhancement rather than an industry-shaping disruption. This positions CLIK at Level 3.

Key Takeaway

The AI Radar showcases the breadth of AI adoption in Indonesia, from financial technology to logistics. While most companies studied are at Level 3 (Operational Transformation), this analysis highlights a growing trend of AI-driven improvements in operational processes, customer experiences, and decision-making. The AI landscape in Indonesia is evolving rapidly, with companies exploring diverse applications of AI to address industry-specific challenges.

The key to successful AI adoption lies in identifying internal families of use cases that align with your industry’s unique challenges and your business’s core value chain. Each example in this report demonstrates that impactful AI deployment is not a one-size-fits-all solution—it requires tailoring to specific needs and objectives.

Beyond identifying the right use cases, companies must prioritize investments in scalable infrastructure to support advanced AI workloads and focus on developing AI talent internally. Building a skilled workforce capable of managing and innovating with AI technologies is essential for long-term growth and competitiveness.

The AI Radar will continue highlighting emerging use cases and innovations, guiding businesses navigating Indonesia’s AI transformation. By leveraging these insights, companies can contribute to shaping the nation’s future as a leader in the global digital economy.

AI Maturity Framework Introduction

The AI maturity framework used in this report offers a structured approach to evaluating the impact of artificial intelligence across industries in Indonesia. It categorizes the deployment of AI solutions based on their transformative potential, ranging from basic automation to industry-wide disruption.

Level	Description	Impact
Level 1: Basic Automation	Minimal impact; routine automation of repetitive tasks.	Streamlined operations with low disruption.
Level 2: Incremental Improvements	Modest impact with improvements in isolated areas.	Small gains in efficiency and performance.
Level 3: Operational Transformation	Significant improvements in workflows or resource management.	Noticeable impact on daily operations.
Level 4: Strategic Innovation	AI transforms core processes, delivering major efficiency gains.	High-level impact on core business functions.
Level 5: Industry-Wide Disruption	Disruption of industries or creation of new business models.	Major market changes, reshaping entire sectors.

This framework helps understand how AI deployments are evolving, enabling companies to assess their readiness for digital transformation and the scale of change they can expect from AI adoption.