DoP Deep: What AI features are product teams building? Part 2
A closer look at how top tech companies are integrating AI into their products
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Hi product people 👋,
Eventually, saying ‘AI powered features’ will sound just as strange as someone who says ‘internet powered features’ today. But, given the rapid speed at which AI is evolving and the sheer number of new opportunities created by the AI explosion, we’re not quite there yet.
In this DoP Deep, we’re going to explore the new ways top tech companies are integrating AI into their products so that you can stay in the loop - and more importantly - consider how these new features and developments might help you craft your own product’s AI strategy.
If you missed the first edition of this DoP Deep series, you can check that out here. In that edition, we looked at how companies like Spotify, Snapchat, Zoom and Arc were deploying new AI features.
In Part 2, we’ll continue to explore what new features top tech companies are building with a fresh batch of companies including Stripe, Notion, Microsoft, Amazon, Roblox, Quora and more. Plus we’ll take a look at some recent failures, too. Since the last DoP Deep on AI, some companies released - and retired - some AI features, so it’s also helpful to understand why some features failed.
Coming up:
The top categories of AI features: from UX enhancers and AI Assistants
A snapshot of new AI features recently shipped by Stripe, Roblox, Google Maps, LinkedIn and more
How to use these new features to inform your own product’s AI strategy
Notes on AI features that failed
The full list of AI features recently released - with links to each one
Categorising AI features
After exploring how companies are using AI, the features product teams are building right now tend to fall into 5 distinct categories:
Embedded assistants - an AI powered assistant that is embedded inside the core product and is designed to complement the value proposition in some way
New standalone products - AI powered, standalone products that are separate to the core product offering
UX enhancers - AI powered features designed to make it easier to use an existing product or improve the overall user experience in some way
Productivity boosters / time savers - AI-powered features designed to boost the productivity of users
ML intelligence / data analysis - AI powered machine learning models deployed to add value or uncover insights
We’ll use these categories to help us explore what AI features product teams are building as we did in Part 1 of this. And this time, we’ll also use this to help you generate ideas of your own. But first, let’s take a look at each of the companies we’ve included this time.
How top tier tech companies are integrating new AI features
Here’s a snapshot of some of the new features implementing by the top tech companies we’ve featured in this edition using the 5 distinct categories: