My 3 AI Stocks to Buy in August: 1 Software Winner, 2 Infrastructure Powerhouses

August is becoming the showdown month for AI spending

August is shaping up to be a key test for AI investing.

After a huge run in AI names, the Morningstar Global Next Generation Artificial Intelligence Index was up about 45% this spring and more than 20% for the year to date. But investors are no longer paying up for ambition alone. With hyperscalers on track to spend upward of $650 billion on AI investments this year, the market is asking a harder question: who can turn that buildout into measurable revenue and sustainable margins?

My rule of thumb is simple: favor AI landlords and software operators with visible monetization rather than buying every company with a big AI spending plan.

That tension is not theoretical. At the current pace, hyperscalers could spend more combined on capital expenditures than they generate in free cash flow by 2027. For August, that argues for picking winners more carefully.

Microsoft: a software leader still weighed down by capex fears

Microsoft still looks like a software cash engine that the market is judging mostly through the lens of future spending.

The stock is near a one-year low even though the company has topped earnings expectations consistently in recent years. That mismatch is the setup. Wall Street does not seem to be questioning Microsoft's past execution so much as its patience with the size of the AI capex bill.

The numbers still look healthy

Wall Street expects about $87.7 billion in revenue and $4.24 in EPS for the quarter. Those are strong numbers, and they sit near the top of the company's own guidance range. By that measure, the business is still producing meaningful growth.

The bigger issue is optics. Microsoft expects more than $40 billion in capital spending for the quarter, with about two-thirds going to GPUs and other short-lived hardware. Investors are fixated on that spending curve even if the underlying business remains solid.

Why Microsoft still has rerating potential

Microsoft has the advantage of selling AI through products customers already use and pay for. Even if returns are still unfolding, that is different from funding a distant experiment with no revenue path. If investors start focusing again on software monetization rather than just the buildout, the stock could respond.

What to watch in the report

• Whether guidance shows the revenue engine is still strong enough to justify the spending plan.
• Whether management can show AI demand remains durable rather than cyclical.
• Whether capex expectations start to look manageable relative to cash generation.

Alphabet: AI spending that reinforces the core cash engine

Alphabet's case is different because its AI spending is being plugged into businesses that already generate massive cash.

Search is still generating 19% year-over-year growth in revenue, while Google Cloud posted 63% year-over-year revenue growth. That matters because Alphabet is not asking investors to fund a far-off AI dream. It is funding tools that are already strengthening its core monetization engines.

Why Alphabet's AI spend looks more defensible

Alphabet can use AI to reinforce Search, improve ad products, lift cloud demand, and support internal efficiency at the same time. That diversification makes the spending case look sturdier than a pure infrastructure bet.

That is likely why Morningstar gave Alphabet a 4- or 5-star rating as of July 24. The stock is being treated less like a speculative AI story and more like a profitable platform whose AI buildout could strengthen, not weaken, its position.

Bulls see a high-margin ad and software platform using AI to reinforce the cash engine. Bears still worry about cyclical ad spending and whether the full AI payoff will arrive fast enough. For August, though, the fact that monetization is already showing up in growth data makes the bull case more credible.

What to watch

• Whether Search momentum remains intact as AI features expand.
• Whether cloud growth continues to accelerate.
• Whether management can show AI investment is supporting margins rather than just expanding the spending plan.

TSMC: the foundry layer that benefits no matter which platform wins

If Microsoft and Alphabet are the software and platform layers, TSMC is the manufacturing bottleneck underneath them.

Morningstar still rates it 4 stars and says it is undervalued as of July 24, 2026. In practical terms, that means investors are not being asked to buy a faded dream; they are buying a scarce manufacturing asset at what Morningstar considers a discount.

Why TSMC is the cleanest scarce-resource bet

TSMC sits in the infrastructure and foundry layer of the AI stack. That matters because AI demand does not become useful capacity until design interest turns into real silicon.

Advanced packaging and leading-edge manufacturing are not easy to copy. Many chip designers and cloud buyers ultimately depend on a small set of manufacturers that can build the hardest chips at scale. When demand is broad-based, that kind of choke point can be more durable than betting on any one software winner.

TSMC also complements Microsoft and Alphabet. Microsoft and Alphabet rent AI compute and embed AI into software; TSMC helps build the chips that make that compute possible. If AI demand stays strong, all three can win. If demand narrows, TSMC still has an argument because its exposure is spread across many customers rather than tied to one platform's product cycle.

What to watch

• Whether demand remains broad across customers and end markets.
• Whether the company's leadership continues to reflect strong utilization in advanced nodes.
• Whether investors keep rewarding the scarcity value of leading-edge capacity.

Why these three make more sense together than a broad AI spend trade

The common thread here is monetization visibility. Microsoft offers software revenue already attached to existing products. Alphabet has core ad and cloud businesses that AI is already helping. TSMC sits at the manufacturing layer that benefits even if platform leadership shifts over time.

In a month when investors are scrutinizing whether AI spending is turning into real returns, those are stronger positions than simply owning every company with a large AI budget.