Indonesia: GenAI market size 2030

In 2023, the market size for generative artificial intelligence (GenAI) in Indonesia was estimated to reach 116.25 million U.S. dollars. Projections indicated that the market size will continue to increase significantly and reach over two billion U.S. dollars by 2030.

The rising popularity of ChatGPT

With GenAI technology, users can generate text, images, videos, or other content through deep-learning algorithms. As of 2023, Indonesia stood among the leading countries in terms of awareness of ChatGPT, resulting in its widespread adoption as one of the most popular GenAI platforms in the country. Nearly 60 percent of Indonesian users access ChatGPT on a weekly or daily basis for various intentions, from work to entertainment purposes. Holding over six percent of the total traffic share on the ChatGPT website, Indonesia is arguably one of the largest markets for this platform.

AI and its risks

It is inevitable that the many advantages of artificial intelligence come with its risks. For instance, AI-generated deepfakes can increase the spread of misleading information, leading to various negative consequences. However, a recent study revealed that a considerable portion of the Indonesian population remained unaware of deepfake technology. Additionally, the potential misuse of AI for malicious purposes was found to be the main concern among the population. Given that there remains a large room for growth in digital literacy in Indonesia, it becomes even more crucial to address the risks of AI to ensure safety as the technology continues to grow rapidly across the country.

Market size of generative artificial intelligence (GenAI) in Indonesia from 2021 to 2030 (in million U.S. dollars)

Characteristic	Market size in million U.S. dollars
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Supplementary notes

Data provided by Statista Market Insights are estimates.

Definition:
Generative artificial intelligence (AI) is a field of artificial intelligence that focuses on creating models and systems capable of generating new content, such as images, videos, music, or text. By training on large datasets, generative AI models learn patterns and structures within the data to produce novel and realistic outputs that mimic the original data distribution. Using techniques like generative adversarial networks (GANs) or variational autoencoders (VAEs), generative AI has the potential to enhance creativity, enable data synthesis, and revolutionize various industries including art, entertainment, and content creation.

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