How AI Is Showing Up in Product Experiences

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by

Tara
in , ,

Keeping up with all the new AI can feel impossible, right? But if we can take a look at some of these developments through the lens of the products we might already be using use every day, it makes it easier to create some context on how to think about them.

In the following we’ll look at some familiar products and create a simple framework for categorizing AI features in order to better understand their use cases.

Five Categories

I’ve broken down the AIs into these 5 categories.

  1. Chatbots: AI-powered chatbots that enhance customer interactions.

2. UX Enhancements: AI features that improve the usability of an existing product.

3. Productivity Enhancements: AI features that help users work more efficiently by automating certain tasks.

4. Standalone Solutions: Independent AI tools that solve specific problems.

5. Analytics + Machine Learning Tools: Models that analyze data and provide deeper insights.

🤖 Chatbots

Chatbots have been around for a while but still hold immense potential for enhancing user interactions.

Especially now with chatbots appearing on an increasing number of sites and user fatigue on the rise (remember this Redditor’s encounter with Chevrolet’s chatbot?), it’s crucial to consider the changing landscape to make sure interactions are thoughtful and helpful to users.

Here are some examples:

Zoom AI Assistant: Generates meeting summaries, transcribes conversations, manages schedules, and offers insights based on histories.

AI Assistant can help you get caught up or give you a recap of action items (image via Zoom)

Shopify Sidekick: Navigates the Shopify platform, automates routine activities, and makes recommendations.

Shopify Sidekick is literally like an assistant that can take on tasks like setting up a sale or help you analyze your store data. Image via Shopify.

Notion Q&A: Provides instant answers based on workspace content, streamlining workflow.

Slack AI: Manages work more efficiently with personalized search, automated recaps, and thread summaries.

Get channel recaps, thread summaries and more personalized and contextual search results with Slack AI.

Yelp AI Assistant: Connects consumers with local service professionals.

Using Yelp’s AI assistant to find a masseuse.

🫡 Standalone AI Solutions

Standalone AI solutions go beyond simple enhancements to solve specific problems. Some examples include:

Spotify Synthetic DJ: AI mimicking a DJ to enhance music listening.

Kind of like an old skool top 40 DJ talking to you.

Dropbox Dash: Universal AI-powered search tool.

A single search bar to help you find anything, even across different connected services like Google Workspace, Slack, Asana, Trello, Outlook etc.

Docusign IAM: Transforms unstructured data in agreements into structured data.

Docusign’s Intelligent Agreement Management platform and suite of applications to help businesses transform agreement data into insights and actions.

YouTube Create: A standalone app with tools to help content creation.

Tools to help creators make better video content.

🎨 UX Enhancements

UX enhancements are AI features designed to improve product usability, making them easier and more enjoyable to use. Examples include:

Google Maps Updates: Enhances speed limit accuracy.

See speed limits on the Google maps interface (bottom left corner).

Shopify Generative AI: Writes product descriptions.

With just a few feature and keyword details, Shopify will write your product descriptions for you.

Amazon Product Image Generator: Creates high-quality product images.

Producing engaging and differentiated creative is now possible with Amazon’s AI-powered image generation.

Pinterest Body Types: Refines search results based on body types.

Body type ranges are part of a broader effort to develop AI-powered technology that is additive rather than addictive according to Pinterest.  (image via Pinterest)

Audible AI Narrated Audiobooks: Creates audio versions of books.

With already 40,000 titles with AI narration, AI narration is experiencing some backlash.

💪 Productivity Enhancements

Productivity enhancements help users work more efficiently by automating tasks. Some examples:

Google Docs Help Me Write: Assists with content creation.

Write with Gemini in Google Docs.

Spotify Voice Translation Tools: Translates podcast content.

Spotify AI voice is an AI generated voice that mimics the podcaster’s voice, maintaining distinctive speech characteristics in other languages. Listen to Lex Fridman in Spanish.

Grammarly: Adapts to your writing style.

Grammarly’s new voice profile feature ises generative AI to match the style of your writing.

YouTube AI Features: Includes insights and dubbing videos.

YouTube’s Dream Screen tool allows users to create AI-generated video or image backgrounds by typing an idea into a prompt.

Canva Magic Design – Content creation from a single prompt. (and if you didn’t catch their most Canva-esque keynote in May here’s a link.)

From a single prompt, Magic Design helps identify what you need and quickly creates designs.

⚙️ Analytical/Machine Learning Tools

Analytical and machine learning tools provide data analysis and insights. Some examples:

Amazon Transcribe Call Analytics: Generates call transcripts and insights.

Transcribe Call Analytics will improving customer service by unlocking the insights trapped in customer conversations.

Stripe Smart Retries: Optimizes payment retries.

Smart Retries chooses the optimal times to retry failed payments attempts in order to increase the chance of successful payment. (image via Stripe)

Building AI capabilities Into Your Product

AI offers transformative potential across various business functions. If you’re thinking about how you might integrate AI into your product, asking yourself these three (very familiar) questions is a good place to start.

  1. What are our users’ biggest pain points? Identify areas where AI can genuinely enhance the user experience by solving specific problems. Talk to your users to understand their workflows and frustrations.
  2. What can we do to address those pain points? Consider specific AI capabilities that align with your product goals. Is it automating tasks? providing insights? making contextual suggestions? etc.
  3. How will we measure success? Define clear objectives and success metrics, such as increased productivity, user satisfaction, or reduced response times.

This said, we still have to do some of the hard work but perhaps this might be somewhat of a relief! 😮‍💨

I hope this leaves you with some examples of how some familiar products are leveraging AI and perhaps some ideas on using AI in your own.