Accelerating the Shift from AI Enablers to AI Adopters

Our Head of Thematic Research in Europe previews the possible next phase of the AI revolution, and what investors should be monitoring as the technology gains adoption.

----- Transcript -----

Welcome to Thoughts on the Market. I’m Edward Stanley, Morgan Stanley’s Head of Thematic Research in Europe. Along with my colleagues bringing you a variety of perspectives, today I’ll discuss the latest developments around AI Adopters. It’s Tuesday, February the 20th, at 2pm in London.

The current technology shift driven by AI is progressing faster than any tech shift that came before it.

I came on the show at the beginning of the year to present our thesis – while 2023 was the “Year of the Enablers,” those first line hardware and software companies; 2024 is going to be the “Year of the Adopters,” companies leveraging the Enablers’ hardware and software to better use and monetize their own data for this generative AI world.

And the market is still sort of treating this as a “show me” story. Enablers are still driving returns. Around half of the S&P’s performance this year can be attributed to three Enabler stocks. Yet, be it Consumer or – more importantly – Enterprise adoption, monthly data we’re tracking suggests AI adoption is continuing at a rapid pace.

So let me paint a picture of what we’re actually seeing so far this year.

There has been a widening array of consumer-facing chatbots. Some better for general purpose questions; some better at dealing with maths or travel itineraries; others specialized for creating images or videos for influencers or content creators. But those proving to be the stickiest, or more importantly leading to major behavioral day-to-day changes, are coding assistants, where the productivity upside is now a well-documented greater than 50 per cent efficiency gain.

From a more enterprise perspective, open-source models are interesting to track. And we do, almost daily, to see what’s going on. The people and companies downloading these models are likely to be using them as a starting point – for fine-tuning their own models.

Within that, text models which form the backbone of most chatbots you will have interacted with, now account for less than 50 per cent of all models openly available for download. What’s gaining popularity in its place is multi-modal models. This is: models capable of ingesting and outputting a combination of text, image, audio or video.

Their applications can range from disruption within the music industry, personalized beauty advice, applications in autonomous driving, or machine vision in healthcare. The list goes on and on. The speed of AI diffusion into non-tech sectors is really bewildering.

Despite all these data points, suggesting consumer and enterprise adoption is progressing at a rapid clip, Adopter stocks continue to underperform those picks-and-shovels Enablers I mentioned. The Adopters have re-rated modestly in the first month and a half of the year – but not the whole group.

Of course, this is a rapidly changing landscape. And many companies have yet to report their outlook for the year ahead. We’ll continue to keep you informed of the newest developments as the years progress.

Thanks for listening. If you enjoy the show, please leave a review on Apple Podcasts and share Thoughts on the Market with a friend or a colleague today.