Two market-leading AI stocks yet to attract market-leading multiples

Alison Savas | Antipodes

Despite being one of 2023’s best performing global stocks, up almost 240%, at the time of writing, Nvidia’s share price has continued to rise by around another 150% this calendar year. It's also in the elite club of stocks that have a market cap over more than $3 trillion (USD), along with Microsoft and Apple. 

It's been a phenomenal run thanks to a near monopoly over AI chips and pricing power. 

The commercial implementation of large language models has been percolating for a number of years and the release of Chat GPT in November 2022 catalysed an unprecedented acceleration in investment . 

Nvidia has been the primary beneficiary of this investment cycle. 

Building and operating AI models is both power and hardware intensive. This has resulted in huge demand for Nvidia’s GPUs, or graphic processing units (a powerful chip that can quickly process large quantities of simple operations but run them in parallel). 

Further to this, Nvidia’s share price performance has been underwritten by a significant increase in revenue and profit - NPAT increased from $4.4 billion in FY Jan 2023 to $29.8 billion in 2024, with consensus expecting $63.7 billion in 2025 (per Factset). 

The market has blessed the stock as the ultimate AI winner.

The landscape will shift

However, we know that with any non-linear change, the business and market landscape shifts over time.

We are currently in an arms race to build more capacity and train increasingly sophisticated models. The question is, how sustainable is the current level of spending? 

AMD estimates that spending will continue to grow at 70% p.a. from $45 billion in 2023 to more than $400 billion by 2027. To support this level of AI hardware, surrounding infrastructure also needs to be upgraded – Antipodes estimates an additional $350 billion will be required alongside the $400 billion. 

This will take total data centre investment to $750 billion by 2027. These numbers are staggering - and to justify this level of spend, companies will need to find ways to monetise models.

As companies look to scale their AI models, the spotlight is squarely shifting to reducing the total cost of compute.

Competition is building from Nvidia’s traditional semiconductor rivals, as well as the cloud giants that are developing in-house accelerator chips (an alternative to GPUs) to support both training and inferencing workloads (the workloads from deploying, or using, the AI model).

Further, researchers are working on ways to increase the algorithmic efficiency of the AI models to get better use out of existing chips - startups are contemplating using alternative GPUs to run AI models once they are deployed into the real world, and smaller models are being deployed to run locally on devices without the need to use GPUs in data centres.

What does this mean for Nvidia's market dominance?

All these methods aim to reduce the cost of compute.

The point is, the phenomenal growth that Nvidia has experienced is not guaranteed into the future.

The capability of these large language models is transformational, and there will be more than one winner from this cycle of innovation despite the way the market is behaving today. 

Exposure to AI without extraordinary market multiples

AI has the potential to transform the traditional parts of the economy – those businesses that can adopt AI to either drive revenue or significantly reduce costs – as well as change the way consumers interact with the digital and physical world.

At Antipodes, we’re looking for Pragmatic Value exposure to AI. Stocks that can benefit from the AI investment cycle but are mis-priced relative to their business resilience and growth profile. 

Two such companies are Taiwan Semiconductor Manufacturing (TSMC) (TPE: TPE: 2330) and Qualcomm (NASDAQ: QCOM).

TSMC

TSMC is the picks and shovels play of AI given its critical role in the supply chain. It is the largest and most sophisticated foundry in the world with a near monopoly over the manufacture of the most advanced semiconductor chips. 

The GPU or accelerator chips that are currently deployed in data centres are more than likely manufactured by TSMC. 

TSMC's competitive strength is evidenced by Intel’s challenges in attempting to scale its foundry business, and Samsung Electronics’ inability to mass produce leading edge chips at the same volume, quality and cost as TSMC.

The company has made the investments required to participate in this cycle of innovation including building leading-edge fabs in the US and Japan.

Explosive demand for AI chips places TSMC in pole position to harvest those investments for growth and profitability. We see the company growing earnings 15-20% p.a. and it’s priced at only 14x our 2026 earnings forecasts. 

Geopolitical risks do exist but given TSMC’s critical role, both superpowers are still very dependent on the company.

QCOM

Beyond first order beneficiaries, we are also thinking about edge applications. Qualcomm is a global leader in low power compute and connectivity chips. Its expertise allows it to flex its creative muscle by designing AI chips for devices like phones and laptops. 

For example, some of Microsoft’s new Surface tablets and laptops will be able to run certain AI tasks locally on the device, powered by chips from Qualcomm. Running AI models locally results in lower cost (no data centre required), better security (sensitive information is not being sent to the cloud) and a better user experience from lower latency (avoids internet lag).

Unlike downloading a new app, users need to upgrade their hardware to access these new AI features. 

By bringing AI from the cloud to the device, Qualcomm benefits from this refresh cycle as well as via delivering more semiconductor content to the device. The company is also gaining share in new markets like smart glasses and connected cars.

We can buy Qualcomm today on 18x our forward earnings forecasts, an attractive multiple relative to its business resilience and growth profile.

Pragmatism matters in the long term

Nvidia is today’s undisputed AI leader, but as with previous episodes of innovation the landscape will shift. 

There are obvious parallels to the dotcom bubble. The fibre optics communications boom in the late 90s led to game changing technology that ultimately enabled all the things we take for granted today.  But capacity was overbuilt in the short term which led to a period of digestion as investment receded and stock valuations came back down to earth.

With TSMC and Qualcomm we’re able to take exposure to AI at mid to high teens multiples versus 30x for the broader semiconductor complex. 

This is Pragmatic Value exposure to AI.

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All prices and analysis at 7 June 2024.  This document was originally published in Livewire Markets on 7 June 2024. This information has been prepared by Antipodes (ABN 29 602 042 035)(AFSL 481580). The content is distributed by WealthHub Securities Limited (WSL) (ABN 83 089 718 249)(AFSL No. 230704). WSL is a Market Participant under the ASIC Market Integrity Rules and a wholly owned subsidiary of National Australia Bank Limited (ABN 12 004 044 937)(AFSL No. 230686) (NAB). NAB doesn’t guarantee its subsidiaries’ obligations or performance, or the products or services its subsidiaries offer.  This material is intended to provide general advice only. It has been prepared without having regard to or taking into account any particular investor’s objectives, financial situation and/or needs. All investors should therefore consider the appropriateness of the advice, in light of their own objectives, financial situation and/or needs, before acting on the advice.  Past performance is not a reliable indicator of future performance.  Any comments, suggestions or views presented do not reflect the views of WSL and/or NAB.  Subject to any terms implied by law and which cannot be excluded, neither WSL nor NAB shall be liable for any errors, omissions, defects or misrepresentations in the information or general advice including any third party sourced data (including by reasons of negligence, negligent misstatement or otherwise) or for any loss or damage (whether direct or indirect) suffered by persons who use or rely on the general advice or information. If any law prohibits the exclusion of such liability, WSL and NAB limit its liability to the re-supply of the information, provided that such limitation is permitted by law and is fair and reasonable. For more information, please click here.