Big-tech is leading the artificial intelligence race, but there are plenty of smaller companies well placed for what's to come. 

That's the view of Franklin Templeton portfolio manager Francyne Mu, identifying Synopsys (SNPS) and MongoDB (MDB) as two smaller players set to benefit from the AI boom. 

Since 2007, MongoDB has amassed millions of users of its document-based database, and currently screens as 3-star, or fairly valued, according to Morningstar.

Narrow-moat Synopsys provides electronic design automation, or EDA, software, intellectual property, and software integrity products that are critical to the semiconductor chip design process. Morningstar believes the company has a long growth runway ahead, although at its current share price, looks overvalued. 

 

Ms Mu discussed why she likes the companies during a panel discussion with Morningstar's Michael Malseed and Antipodes founder Jacob Mitchell, at the 2023 Morningstar Investment Conference in May. 

Transcript: 


Jacob Mitchell: Yeah, AI, probably 3 buckets of opportunity. They are the business cases or use cases that we haven't even, we can't really imagine at this point. We're trying to work them out. The second bucket would be the deployment of AI within existing software platforms and. That favors companies like Microsoft (MSFT), Oracle (ORCL), SAP (SAP), many of the large, the mega caps, are going to be able to do that because they have really, they've got the internal software hardware skills. And they have relatively unique data sets and the ability to monetize and upsell is really easy for a company like Microsoft or Oracle, SAP. And we own those stocks, we think they're still reasonable valuations relative to their underlying quality of their businesses. Clearly you can do it in consumer facing companies like Meta (META), Google or Alphabet (GOOG).

But I think the range of outcomes in some of the consumer facing stocks are a lot wider and are harder to predict and arguably they are more mature. I mean Alphabet and Meta do dominate digital advertising and I'm not sure, that market is now becoming, I suspect you're getting close to the growth trap point in their cycle where they start to mature rapidly and they become very, more cyclical. Even if they do have pricing power, they're very high quality businesses. I think their top line will become, more like GDP type growth. And in Alphabet in particular, you have to think that ChatGPT Microsoft, OpenAI, Microsoft collaboration is taking 200 million monthly average users on that, on ChatGPT. The number of queries is averaging around 8% of desktop search queries. So it's already grown to being roughly 8% of Google's desktop search query market.

So you've got a competitor who's arguably taking away eyeballs from standard search and then clearly Alphabet responds with Bard, but Bard could actually be cannibalizing their existing profit pool. And as of yet, these companies haven't really worked out how to monetize that. And so it's I think the range of outcomes around Alphabet is broadening and hence we don't own that stock. But that's I think a more healthy environment, if we start to see more dispersion amongst the mega caps, which I think will come back, we've had this little episode of bond proxy, but I think we go back to the market being a lot more discriminating between the winners and losers in that bucket.

Michael Malseed: So yesterday online, Rajiv Jain talked about it's very hard to pick a winner in AI because there's about 400 startups in the U.S. and it's like the 90s with Amazon, you wouldn't pick them as a winner necessarily back then. So in terms of looking at AI startups smaller companies, what are you saying out there is the opportunities or is it a case that Microsoft has this big first mover advantage with OpenAI and they can potentially just dominate because it's a scale game, but maybe Francyne you look at smaller stocks, what do you think?

Francyne Mu: Yeah, I mean, I think he's probably right in that it's still very early in the piece. And it's difficult to pick the winners and see how the market develops. You know, there's a range of outcomes as Jacob has said. But I think what is clear to us is that, AI these large language models will require huge computational power. So if you strip it back to that you need semiconductor chips that can actually process that, right. And so for us, we're taking a position in, Synopsys (SNPS) which provides the software in electronic design automation to help these semiconductor companies design better chips in order to enable this generative AI and to sort of move forward in this space.

Another company that we like also to sort of play AI is through MongoDB (MDB). You know more and more the information that's coming in, the data that's coming in is unstructured, you've got video files, you've got text messages, you've got all that kind of stuff and these models have to sort of try and work with that data in order to generate and predict what the next word is or what have you. And so MongoDB provides software, document based database management which will help to be able to pick up on these data pieces much more efficiently over time. And so those two, I think names, they're not the mega caps, but we think that there's very clear positives for these two companies to benefit from what is to come.