Amazon's AI-powered Alexa+ reaches over one million users in early access
Alexa+, Amazon's generative AI-powered digital assistant, is now available to over a million users during its early access phase. The service will be free for Prime members and cost $19.99 per month for non-Prime users after launch.
Amazon's upgraded digital assistant, Alexa+, powered by generative AI, has now reached over a million users during its early access phase. The service, first announced in February 2025, is not yet publicly available but has been rolling out invites to users who signed up for the waitlist.
Key Features of Alexa+
- Natural Language Interactions: Users can phrase requests conversationally (e.g., "It's too cold in here" to adjust a smart thermostat).
- Personalized Experience: Remembers preferences like favorite songs, recipes, and routines.
- Generative AI Capabilities: Can summarize emails, create bedtime stories, generate quizzes, and provide smart home activity summaries.
- Action-Oriented Tasks: Books reservations, buys tickets, and notifies users about sales via partners like OpenTable, Ticketmaster, and Uber Eats.
Pricing and Availability
- Early Access: Free for invited users.
- Post-Launch: Free for Amazon Prime members, $19.99/month for non-Prime users.
- Device Compatibility: Initially available on Echo Show 8, 10, 15, and 21 in the U.S., with plans to expand to Fire TV and Fire tablets.
User Feedback
Early adopters report mixed reactions:
- Some praise its advancements over competitors like Siri.
- Others note it’s still "rough around the edges," per early reviews.
Amazon's AI Ambitions
Alexa+ marks Amazon’s push to monetize its voice assistant after years of losses. The company aims to compete with modern AI services like ChatGPT, which made Alexa feel "clunky" by comparison.
Current Status
- 90% of announced features have shipped.
- Growth from 100,000 users in May 2025 to over a million highlights rapid adoption.
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About the Author
Dr. Sarah Chen
AI Research Expert
A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.