AI assistants and “digital colleagues” have matured into a spectrum of tools that businesses use to automate routine work, augment knowledge work, and coordinate multi-step processes. As of 2025-12-26 this topic covers personal assistants for individual productivity, meeting and email assistants that summarize and triage communications, and voice-based schedulers that integrate calendars and telephony — plus enterprise platforms that orchestrate multiple agents with governance and observability. Choices range from general-purpose, multimodal model families to domain-tailored and workflow-focused products. Anthropic’s Claude family targets conversational and developer use cases — writing, research, code and analysis — while Google’s Gemini line offers multimodal models and developer APIs via Google AI Studio and Vertex AI for embedding vision, text and code capabilities into apps. Enterprise products emphasize integration and control: IBM watsonx Assistant provides no-code and developer paths for virtual agents and multi-agent automations; Kore.ai focuses on orchestrating agent workflows with governance and observability; Yellow.ai targets CX/EX automation across channels; Harvey delivers domain-specific assistants, knowledge and workflows for law and professional services; Notion blends workspace, knowledge and automation with embedded AI for team productivity. For organizations deciding what to adopt, key trade-offs are domain specialization, data governance, integration with existing systems, and the need for explainability and observability. Practical deployments increasingly combine a foundation model (Claude, Gemini) with platform features (watsonx, Kore.ai, Yellow.ai, Harvey, Notion) to deliver meeting summaries, email triage, and voice scheduling while retaining enterprise controls and compliance.