AI email assistants and writing tools now range from embedded client copilots to standalone writing platforms and enterprise LLMs. This topic examines how Gmail’s Gemini family (including the Gemini 3 generation), ChatGPT-style services, and Microsoft Copilot approach common email tasks—drafting, summarization, translation, tone editing, and automation—while also considering complementary tools and developer platforms. Relevance in 2026 comes from near‑ubiquitous integration of generative models into mail clients and work apps, rising demand for context‑aware drafts, and increasing enterprise needs for customization, privacy controls, and retrieval‑augmented workflows. Google exposes Gemini variants via Google AI Studio, Cloud Vertex AI, and developer APIs; OpenAI/ChatGPT-style services remain popular for conversational drafting and integrations (note: some public endpoints and pricing tiers are gated behind client-side controls); Microsoft Copilot is positioned as an integrated assistant across Outlook and 365 apps. Specialized tools expand capabilities: DeepL and DeepL Write for high‑quality translation and localized tone; QuillBot for paraphrasing, grammar and citation aids; Copy.ai and Frase for marketing content and SEO/GEO optimization; Notion for embedding AI into knowledge workflows; and Cohere for private, customizable enterprise models. Key considerations for selection are integration depth (native client vs API), model modality (text vs multimodal), privacy/hosting options, hallucination mitigation via retrieval, and task specialization (translation, SEO, GTM content). This comparison offers a practical viewpoint for users and IT teams weighing embedded copilots (Gmail Gemini 3, Microsoft Copilot) against standalone or integrable assistants (ChatGPT, DeepL, QuillBot, Copy.ai, Frase, Notion, Cohere) based on workflow, compliance, and scalability needs.