AI applications are evolving rapidly. For companies to make money off of the new technology, they need consumers to accept using AI as part of their daily lives. Meta Platforms (META) took a big step toward making AI user friendly this week, making the AI interaction seem like a chat with a popular celebrity, or just another member of your friend group.

Don’t get me wrong, ChatGPT and Claude are great applications, but most people aren’t willing to become “Prompt Engineers” just to find out where the best pizza is near them. To capture the large consumer market, companies like Meta have to dumb down (yes, ironic when speaking of AI) the interface so it’s very simple to use.

Introducing AI bots based on popular media and historic characters to provide both search results, and an AI “buddy” to chat with on Instagram, or via WhatsApp, is a big step in the right direction. As Ahmad Al-Dahle, METAs VP of Generative AI put it, “You don’t have to pull yourself out of context to interact or engage or get the assistant to help you.” It’s what the social media and marketing geeks like to call being “native” to the platform.

Meta and Zuckerberg have been chastised in the business press as being behind in the AI game. But with this latest announcement it appears they were just taking some time to get it right…making sure they weren’t just blathering about AI for the sake of getting positive press.

Meta currently has operating margins of almost 29%, and trades at 2.79 times sales. In the latest quarter, revenue increased 11% YoY, and free cash flow was a tick under $11 billion.

The company is rated a B overall in our POWR Ratings, where it is ranked higher than 81% of the stocks in our database. Not surprisingly it rates an A for Quality.

As the AI race developed this year, a lot of investors were asking why only the large companies were “winning” while there seemed to be a dearth of small AI companies. Here’s why. Companies like Alphabet (GOOGL)…which I still call Google…have what it takes to bring profitable AI products to market. Cash…AI is EXPENSIVE. Large data sets…training AI takes a LOT of information. And, always helpful, a built-in user base.

Google, while weaving AI into its products, from Gmail to Google Docs, is also focusing heavily on allowing developers to make new AI products (which inevitably will interact with Google products) by putting a large effort into AI development tools, like its LaMDA, or Language Model for Dialogue Applications.

Thus, a large part of the Alphabet AI strategy is to provide the picks and shovels that build AI. Which, again, it is very good at because it possesses massive databases and the wherewithal to train AI on those databases.

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