Key points
- The Long Term Global Growth Team looks beyond the hype to find companies with the ambition, vision and culture to become AI outliers
- Roblox and AppLovin are using the technology to create transformational products and become more efficient
- Promising future applications include robotics, which could spur further demand for NVIDIA’s chips
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Generative AI has given the tech crowd a lot to chew over. The rush of new models, capabilities and research papers is relentless, not to mention related developments in semiconductors, geopolitics and boardroom intrigue.
Long-term growth investors, however, can afford to ignore much of the chatter. Their challenge is singular: discerning which of the companies involved have the culture, ambition and leadership to grow to many multiples of their current size."
“Change is one of the most interesting things that can happen to a growth investor because it suggests new opportunities,” Kyle McEnery, investment manager with Baillie Gifford’s Long Term Global Growth (LTGG) Team, tells the Short Briefings on Long Term Thinking podcast.
“But it’s easy to get caught in the feeling that you need to understand the whole field. Often, I just slow myself down and consider: what am I really looking for? It’s a few exceptional companies that, because of this change, could achieve enormous growth over the next 10 or 15 years.”
AI’s frontier companies
Could Anthropic stand among them? The four-year-old research lab develops the Claude family of large language models (LLMs). They power its own chatbot and AI-assisted coding tool, as well as a growing number of third-party services, including many organisations’ internal AI software.
“Anthropic’s founding principles were very much about AI safety – creating AI that’s understandable and trustworthy, and that’s made them very well suited to enterprise,” McEnery says.
The private company’s annualised revenue run rate (a 12‑month projection calculated by extrapolating a recent month’s sales) has grown from $1bn in late 2024 to a projected $8-10bn at the end of 2025. Despite rising computation costs, it sees a route to profitability.
LTGG invested in August, alongside other Baillie Gifford strategies, and McEnery last visited its San Francisco headquarters at the end of the year.
“They’re winning customers right across the economy – financials, banks, healthcare companies and cybersecurity. And what’s really striking is that the use cases they talked about weren’t just generic tasks, each one was specialised to a relevant industry. For example, know-your-customer checks for [US finance and insurance provider] AIG.”
McEnery’s efforts are not limited to building conviction in new AI-related holdings but also stress-testing the case to retain existing ones. NVIDIA is a case in point. The company became the first to achieve a $5tn valuation thanks to its accelerator chips underpinning much of the field’s progress.
NVIDIA’s chief executive Jensen Huang revealed at the CES tech event that chips and other hardware for its Rubin AI platform are in “full production” for release in 2026. © NVIDIA
Baillie Gifford first invested in 2016, when the firm was better known for selling graphics cards to video gamers than to machine-learning customers. Despite increasing its workforce fourfold and its revenue 26-fold since then, the firm remains future-focused.
“Jensen has a knack for positioning NVIDIA into places that might work out well for it and ensuring that execution is strong,” says McEnery, referring to chief executive, Jensen Huang.
“Over the past six years, it’s improved energy efficiency for LLMs – in terms of the amount of AI tokens1 per joule – by something like 42,500 times, which is crucial as that’s a big bottleneck. Looking ahead, it’s developing ways to simulate the laws of physics to create ‘synthetic data’ for training robots – which is computationally intensive – and Jensen’s also talking about quantum computing. So, while competition is heating up, there are still compelling reasons to hold.”
Transformational products, efficient processes
McEnery’s focus also extends to companies putting AI to use, whether to delight customers or improve internal processes.
He gives Roblox as an example of the former. The firm operates the world’s most popular platform for user-made video games, attracting more than 151 million people daily. Its new Cube 3D generative AI tool lets developers create 3D objects and scenes for their games via text-based descriptions.
Roblox users can now create in-game objects by using its Cube 3D AI tools. © Roblox
“It’s still early days – but the founder, David Baszucki, has told us that the idea is eventually AI allows ‘lucid gameplay’, letting worlds be created in real-time, on-the-fly as people play with them,” McEnery explains – an innovation that should help small teams provide better looking, more ambitious experiences with a greater degree of personalisation.
“It’s an example of a company with a vision it’s been working towards for decades, and this technology could unlock the next stage.”
AppLovin exemplifies AI-driven operational efficiency gains. The advertising platform helps app publishers reach new audiences and track user engagement. Co-founder Adam Foroughi has a policy that if AI can do a task, it should. The has restructured the company to keep layers of management as lean as possible, without compromising service.
“AppLovin’s economics are amazing,” McEnery comments. “Adam is focused on trying to scale up every single one of his employees with AI to be the best they can be. His vision is for everyone to perform at the peak of their level, keeping the company hungry and nimble.”
Human communities
In hunting for big winners, McEnery also thinks about AI’s second-order effects – including people’s hunger for ‘authentic’ human content. It’s a topic he’s raised with portfolio company Reddit. The platform hosts more than 100,000 active discussion groups, conversing about everything from the news headlines to defunct shopping malls.
“It’s about what becomes valuable as AI permeates,” McEnery says. “Steve Huffman, Reddit’s founder, has talked about it being the most human place on the internet – real communities having proper conversations. That’s likely to become increasingly valuable purely because of what’s happening elsewhere.”
It doesn’t mean Reddit shuns the technology. It has increased engagement by using generative AI to auto-translate comments between languages, thereby expanding each post’s potential audience, and has enhanced its search tool to let users ask complex, natural-language questions to discover relevant discussion threads.
But if it is to capitalise on AI’s opportunity fully, Reddit still has further challenges to tackle. For example, Google and OpenAI pay to reference its content within their AI tools, but currently do little to encourage users to go back to the source.
“When we last spoke, one of the main things Steve wanted to talk about was how to nudge anyone who passively interacts with Reddit to get involved,” McEnery says. “He’s obsessed with the product, really cares about onboarding new users and thinks getting AI partnerships right could be a crucial lever for the business.”
This aligns with Baillie Gifford’s own view that companies must think beyond immediate profits to achieve enduring growth.
Other areas where generative AI could have a huge impact include agentic workflows (where LLMs determine their own processes rather than relying on a series of human prompts), as well as healthcare and education. With so much disruption and such rapidity of change, McEnery recognises that some of the outliers he’s chasing may not have even been founded yet.
But, he concludes, these circumstances favour his team’s style of investing: a willingness to take risks in the pursuit of outperformance, an emphasis on finding companies with visionary management, and then the discipline to remain a shareholder during periods of significant volatility – so long as the investment thesis holds.
“This feels like an incredibly noisy time, but I remain pragmatically optimistic,” he concludes. “I try to bias myself to what can go right and be very open-minded. People are going to come up with compelling ways to use this technology – they’re already doing so – so, we just have to be humble as to how it actually plays out.”
Kyle McEnery
Investment Manager
Kyle is an investment manager in the Long Term Global Growth Team. He joined Baillie Gifford's Investment Graduate Programme in 2014. Before joining the team, he led Baillie Gifford’s Artificial Intelligence Research project. Kyle graduated BSc (Hons) in Physics and Astrophysics from University College Cork (UCC) and attained a PhD in Physics from Imperial College, London.
1 Tokens are the fundamental units that large language models process when handling text. They can represent a complete word, partial word, character or punctuation mark. When you type a message into a chatbot, it breaks it into tokens, analyses them, and responds with its own token sequence. Training today’s frontier models typically involves tens of trillions of tokens.
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