Some of the largest companies in the world are all tech juggernauts.
Seven of these have been dubbed the ‘Magnificent Seven’. Microsoft, Amazon, Google parent Alphabet, Tesla, Facebook (aka Meta), Nvidia and Apple are valued at an eye-watering total of around $14tn.
They make up so much of the S&P 500’s total value that their rise or fall holds a heavy influence over investors.
All of them claim to be gearing up to be big players in artificial intelligence (AI), and the potential growth is being priced in.
However, there are concerns about bottlenecks on the road to AI adoption.
Demand for generative AI solutions, which harness the power of large language models, require a huge well of data and that’s got to be stored somewhere.
This presents a huge opportunity for the big tech giants providing the infrastructure. But these power-hungry data centres could put a big strain on electricity grids that could struggle with demand.
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The key takeaways from the magnificent seven’s latest results
Each of the magnificent seven have specific challenges of their own to consider.
Tesla’s share price has had a bumpy ride. This is partly due to how competitive it‘s been in the electric vehicle space, and because investors have raised questions about its AI credentials.
On the latest episode of the Switch Your Money On podcast, Sophie Lund-Yates, Lead Equity Researcher, explained:
“Tesla has lagged some of the other big names. This is partly because the wider excitement is largely linked to AI, and … Tesla’s exposure to this tech is less cut and dry than it is for others. It’s also a lot more exposed to the consumer mood than others, selling cars at a time of economic uncertainty is a tough ask.”
Apple is seen as lagging behind the AI revolution, and has been tight lipped about its plans. This is despite speculation that it’s working on its own chips for data centres.
Some frustration has been reversed recently, following a record share buyback plan. But questions have been raised about whether Tesla and Apple deserve their place in the magnificent seven after all.
Meta, Facebook’s parent company, raised eyebrows in its latest set of results in April, by changing its spending plans and boosting its budget to fund AI.
Sophie Lund-Yates explained: “The reason this initially spooked the market is because Meta had recently reined in its spending to refocus on the core advertising business. Not because there’s anything wrong with spending on AI, but because there wasn’t an iron-clad plan.”
Overall, the latest results – and expectations for Nvidia who’s still yet to report – largely show strength. But there are no guarantees this will continue. Hopes are high for US interest rate cuts this year, which could buoy the wider index, rather than the slim, but mighty, group of seven.
What are the challenges facing big tech and AI?
Being a big fish has its downsides too, and regulators have been getting increasingly nervous about the giant seven tech firms, so there’s a chance that regulation could clip their wings.
Our guest on the latest Switch Your Money On Podcast, Leslie Canavera, Founder of Pol Arctic welcomed regulation. Her data science company uses AI models to help companies in the shipping and fishing industries operate in the Arctic. She said clearer rules would help build trust and fuel AI adoption.
She’s also concerned that without it, gaps in data and bias within models could present risks. And it could mean that “the way people are building them and the decisions people are making with them are not going to be accurate or reliable.”
Of course, the rise of these companies brings its own risk.
Also on the podcast was Lauren Romeo from Franklin Templeton. She spoke to Emma Wall, our Head of Investment Research and Analysis, and pointed out that the top ten companies now make up a third of the S&P 500.
She explained: “That’s a new peak level that surpasses the level of concentration we saw at the height of the tech bubble in 2000.”
She added that there have been four times historically when the concentration was that high in the S&P “and in each case it really represented the peak of large caps’ outperformance over small caps.”
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