India has emerged as the largest market for AI mobile applications, contributing 21% to global AI app downloads in the first eight months of 2024.
Data from Sensor Tower revealed that over 2.2 billion AI apps were downloaded globally during this period, with India playing a significant role in driving adoption. Popular AI apps such as ChatGPT, Microsoft Copilot, and Google Gemini were among the most downloaded, along with various image and video editing tools.
Free usage dominates in India.
While India leads in downloads, most users in the country use these apps for free. In contrast, North America and Europe accounted for 68 percent of the global in-app purchase revenue for AI apps.
With global AI app revenues surpassing $2 billion so far this year, India’s contribution remains under 2 percent. Despite this, Sensor Tower forecasts that total AI app revenue for 2024 will hit $3.3 billion, marking a 51 percent increase from the previous year.
The explosive growth of AI and chatbot apps was already evident in 2023, with downloads skyrocketing by over 14 times to nearly 600 million. This upward trajectory continued into 2024, with over 630 million downloads in just the first eight months, surpassing the entire 2023 total.
OpenAI’s ChatGPT led the way in global downloads, followed by the AI image editing app Remini, Photoroom AI Photo Editor, and Google’s Gemini.
Moving towards an ‘app-less ecosystem’
Experts predict that AI-powered apps will see increased adoption for various generative purposes, such as text, image, and video creation, as well as more straightforward use cases like transcription, translation, and voice assistants.
Future agentic AI systems could autonomously perform tasks without human input. These systems will be able to gather information, process data, and act on users’ behalf.
For example, an AI agent might automatically book a user’s favorite restaurant for a special occasion or order items based on their preferences. This opens up significant opportunities for monetizable advertising.
However, increasing AI use on the edge brings new challenges for device makers. Innovations for faster processors and enhanced memory storage will be needed to support on-device AI models.