Big tech companies are still financially strong, but their enormous investments in artificial intelligence are weakening them and changing their business models in ways that should alter investors’ perceptions of them.
Over the past three years, Microsoft, Alphabet’s Google, and Amazon.com have gone on unprecedented spending binges because they believe AI will revolutionize the tech industry and the world economy. They will have spent more than $600 billion between 2023 and the end of this year if analyst and company forecasts come to pass.
AI is weakening big tech
These businesses were able to maintain that spending early on thanks to their strong balance sheets, low debt, and consistent revenue growth. Their combined net income—mostly unrelated to AI—is projected to surpass $750 billion between 2023 and 2025, which will make their investment choices easier to justify. However, the cash drain is now clearly affecting their financial situations, providing a sneak peek at how drastically their businesses might change if AI costs keep going up.
At the end of the third quarter, Microsoft’s cash and short-term investments made up about 16% of its total assets, a decrease from roughly 43% in 2020. Due to increased investments in AI infrastructure, Alphabet and Amazon also saw a decline in their cash positions in comparison to assets that increased. Additionally, cash flow is becoming more constrained. Analysts expect Amazon and Alphabet to end the year with less free cash flow than they generated last year. Microsoft reports higher free cash flow, but that figure excludes long-term data-center and hardware leases; including those leases would push its free cash flow into negative territory.
According to analysts, rather than focusing on software operations that are infinitely scalable, investors may need to view tech companies as capital-intensive enterprises whose success depends on disciplined spending. According to Josh Beck, a tech analyst at Raymond James, investors will value these companies more based on metrics like the number of AI users and remaining performance obligations.
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