This chapter introduces the rapidly evolving AI-powered Android ecosystem, explaining the rise of agentic AI, on-device AI versus cloud AI, and Google’s Gemini-driven developer tools. It provides Android developers with a clear foundation for building intelligent, autonomous, and multimodal applications in the new AI-first…

Discover how Android AI supercharges your development workflow. This chapter focuses on the enhanced AI features within Android Studio, including Gemini in Android Studio for code generation, bug fixing, and UI transformation…

This chapter explores best practices for building AI-powered Android applications, examines key ethical considerations in AI development, and highlights emerging trends shaping the future of Android AI. Readers will gain insights into responsible AI design, strategies for maintaining user trust, and the technologies that will drive the next generation…

This chapter helps you navigate Google’s Android AI ecosystem. You’ll learn how Gemini models work, when to use on-device vs cloud AI, and how to select the best Generative AI or ML solution for your…

…device AI. This chapter covers delivery strategies, device targeting, and deployment workflows that help you build fast, scalable, and resource-efficient AI experiences on Android…

Artificial Intelligence has transformed from a futuristic concept into an essential technology powering modern Android applications. Whether you’re building productivity tools, creative apps, or intelligent assistants, AI and machine learning capabilities are now within reach for every Android developer. This book guides you through the full landscape…

Learn how to harness Firebase’s cloud-based generative AI capabilities to build smarter, more dynamic Android apps. This chapter walks you through setting up Firebase AI Logic, integrating models like Gemini and Imagen, and adding AI-powered image generation and text creation to elevate your app’s intelligence…

This chapter explores how to build a real-time interactive Android app using Gemini Live. You’ll learn to set up and configure the Live API, manage audio streaming sessions, implement natural voice interactions, and enable function calling so the model can trigger real app actions…

…introduction of ML Kit was meant to serve as the bridge between the worlds of Android and Machine Learning. In the previous chapter, you’ve worked with on-device ML using ML Kit – you built your custom Document Scanner, recognized text within images, and shared them effortlessly with…

…will need a combination of software, hardware, and Google accounts. The items below cover the general prerequisites referenced throughout the chapters. Development environment Android Studio (Otter): It’s recommended to use the latest stable version of Android Studio and the SDK components (Android SDK Platform, emulator images). The minimum version…

This chapter introduces on-device AI in Android using Google’s ML Kit. You’ll build a document scanner and text extractor while learning how to use key Vision and Natural Language APIs. Along the way, you’ll understand when on-device inference is most valuable—such as for privacy…

What a journey it’s been! From exploring the AI-powered Android landscape to diving deep into on-device intelligence with ML Kit and custom ML with MediaPipe, to harnessing the power of the cloud with Firebase and Gemini Live, you’ve gotten a taste of building intelligent Android applications…

…ideas! To Foyzul Karim, my first tech-lead and AI enthusiast, who dared to hire a university student (me) and taught “Hello World” in Android – paving the path of my Mobile Engineering career. And of course, to my family, friends, colleagues, and the team at Kodeco, who inspire…

…editor of this book. He resides in Bengaluru, India, and is an MBA graduate working at a leading credit card company. His interests span Android app development, Flutter, DeepTech, and Finance. He’s a big time foodie, exploring breakfast places in Bengaluru. He loves trekking and flying his drone…