Context‑aware personal AI assistants are systems that use long context windows, multimodal inputs, retrieval from personal and web sources, and app integrations to provide tailored, ongoing support across devices and workflows. By 2026 this category centers on models and platforms that combine generative reasoning with data hygiene, user controls, and enterprise governance. Google’s Gemini family emphasizes multimodal capability and tight integration with Google Cloud, Vertex AI, and developer APIs for building assistants that access documents, images, and enterprise data. OpenAI’s ChatGPT family (with chat, plugins, memory and developer APIs) focuses on conversational workflows, retrieval-augmented answers and extensibility through integrations. Anthropic’s Claude line targets conversational reliability and safety, offering developer- and user-facing assistants for writing, research, code, and analysis. Complementary services—Microsoft 365 Copilot for app‑embedded productivity, Perplexity for web‑grounded, cited answers, PDF.ai for document-centric Q&A, Cohere and IBM watsonx for private/customizable enterprise models, and Kore.ai for multi‑agent orchestration—round out the ecosystem. Key trends shaping this space include larger multimodal contexts, tighter retrieval from personal and organizational sources, real‑time web grounding, on‑device or private‑cloud deployments for privacy, and stronger governance/observability for enterprise use. Practical differences focus on where an assistant runs (cloud vs private), how it accesses and protects personal data, and how it integrates into apps and workflows. For users and organizations choosing between Gemini, ChatGPT, Claude and related tools, the tradeoffs are interoperability, integration depth, privacy controls, and compliance support rather than raw model capability alone.