The new Powers of AI Assistants Explored

2026-07-01 · Source: Department of Product · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

AI Assistants are demonstrating significant impact on core product metrics, as seen with DoorDash's Ask DoorDash Assistant, which boosted grocery basket sizes by over 35% and accelerated cart building by 5x. These assistants are emerging as a new paradigm for in-product search, capable of finding information, answering questions, and executing agentic actions. A comprehensive analysis explores over 35 new AI Assistants from companies like Instacart, Robinhood, Meta, Adobe, and Notion, categorizing their capabilities across B2C ecommerce, SaaS, finance, and productivity. Key "powers" include Agentic Execution, Knowledge Q&A, Memory and Context Awareness, Workflow and Task Automation, Shopping and Cart Building, and Customer Support/Issue Resolution. The analysis also examines the "ambient assistant" pattern and the evolving placement of these tools beyond traditional sidebars.

Key takeaway

For AI Product Managers evaluating new in-product experiences, recognize that AI Assistants are now critical for driving direct business outcomes. Your focus should shift beyond basic search to agentic capabilities that perform multi-step actions, like automated cart building or customer support resolution. Consider integrating memory and context awareness to enhance user flow and explore "ambient" patterns for proactive assistance, ensuring your assistant moves beyond a sidebar utility to a core product differentiator.

Key insights

AI Assistants are evolving beyond search to perform agentic actions, significantly impacting user experience and business metrics.

Principles

• AI Assistants significantly boost core business metrics.
• Agentic execution enables multi-step actions.
• Context awareness improves user interaction flow.

Method

The analysis categorizes 35+ AI Assistants by capabilities like Agentic Execution, Knowledge Q&A, Memory, Workflow Automation, Shopping, and Customer Support, providing examples and UI galleries for each.

In practice

• Implement agentic execution for multi-step tasks.
• Integrate memory systems for context retention.
• Explore ambient patterns for proactive assistance.

Topics

• AI Assistants
• In-product Search
• Agentic AI
• Product Metrics
• User Experience
• Workflow Automation
• Customer Support AI

Best for: Product Manager, Executive, Entrepreneur, AI Product Manager, Director of AI/ML, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Department of Product.