Exploring the Three Main AI Integration Patterns for PC: Agents, Co‑pilots, and Embeddings

Introduction

When AI breakthroughs such as ChatGPT continually astonish us, new product‑AI integration trends emerge. This article reviews the mainstream AI integration forms on PC and offers insights for designers.

Main AI Forms on PC

Three primary forms dominate: immersive AI agents, accompanying AI co‑pilots, and embedded AI (embedding). They differ in capabilities, interface, interaction experience, and suitable scenarios.

1. Immersive Agents

Powerful AI partners that act proactively, not entirely dependent on user input. Two main types exist: conversational agents that present information as a dialogue flow, and goal‑oriented agents that deliver a reliable result in a single step with optional sidebars.

Example – Gemini (Conversational Agent)

Gemini uses a visualized prompt card on its cold‑start page, supports multimodal content generation, and provides an information index that can be toggled by the user. The index improves answer authority and transparency while preserving reading flow.

Example – Perplexity (Goal‑oriented Agent)

Perplexity, built on RAG technology, delivers precise answers in a single interaction and features a dual‑panel layout for deeper processing of the result. A side panel offers supplemental searches when users need additional information.

Design Reflection

Both Gemini and Perplexity aim to provide the best answers: Gemini encourages iterative questioning, while Perplexity offers a single, highly accurate response, akin to an AI‑powered Q&A platform.

2. Accompanying Co‑pilot

Passive AI assistants that provide suggestions and help within the current context, typically displayed in sidebars. They rely on precise user prompts and are common in Office applications.

Example – Office Copilot

Office Copilot assists with content creation, information retrieval, and summarization. It cannot modify documents automatically; user confirmation is required, and actions are recorded in the sidebar. Accurate prompts are essential, so the system offers suggested prompts to guide users.

Design Reflection

The co‑pilot improves work efficiency by acting as a supportive role without disrupting the primary workflow.

3. Embedded AI (Embedding)

Embedded AI focuses on specific scenarios, activating only during important user actions. It follows a lightweight GUI (LGUI) approach, emphasizing seamless, efficient interaction.

Example – OneDrive

OneDrive’s embedded AI suggests smart file‑organization actions and recommends sharing targets based on file content and user history, dramatically reducing the time needed for these tasks.

Design Reflection

Efficient embedded AI should activate only when valuable, provide instant suggestions, and keep interactions simple (click > input). Designers must deeply understand user scenarios to avoid disrupting primary workflows.

Future AI Design

AI forms will continue to diversify, but the core principle remains: design should be user‑centered, efficiency‑first, and scenario‑appropriate. Successful AI integration balances proactive agents, supportive co‑pilots, and lightweight embeddings to deliver real value without unnecessary complexity.