The Best Stocks to Invest $1,000 in Right Now

The U.S. equity market in mid-April 2026 is being driven by a powerful surge in spending on artificial intelligence (AI) infrastructure. Fresh results this week show that demand for advanced chips remains exceptionally robust. At the same time, major cloud providers are also scaling rapidly and increasing their capital spending on AI-related services.

If you have $1,000 that is not required to pay bills or save for contingencies, consider at least a small stake in one of these three stocks below.

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Nvidia

Shares of Nvidia(NASDAQ: NVDA) have been gradually rising in April, even as investors continue to debate whether AI spending is nearing a peak. The company has visibility into at least $1 trillion in demand for its Blackwell and Rubin AI systems through 2027, highlighting the massive scale of ongoing infrastructure investments.

Some analysts believe this figure could prove conservative. Wells Fargo analyst Aaron Rakers is projecting 15% to 20% upside to Nvidia's consensus earnings estimates for calendar years 2026 and 2027. Hence, the company appears well-positioned to achieve exceptional financial growth over the next few years.

CEO Jensen Huang has described Nvidia as an "AI factory" that converts electricity to tokens, the core unit of AI output. As customers increasingly focus on optimizing tokens used per second rather than hardware costs and upfront pricing, the company's full-stack platform, comprising advanced chips, networking technologies, and software, is emerging as a key advantage. This allows customers to build complete AI systems rather than assemble fragmented components, improving performance while lowering the effective cost of AI output.

Nvidia is also benefiting from a more diversified demand. While hyperscalers remain key customers, AI adoption is rapidly expanding across enterprises, regional cloud providers, and emerging use cases. Governments are increasingly investing in "sovereign AI" infrastructure, while early developments in robotics and industrial automation are opening additional long-term opportunities. This shows that Nvidia's total addressable market is far from saturated.

Despite these strengths, the company trades at a reasonable 17.8 times forward earnings. For investors who can ignore short-term noise, Nvidia appears to be a clear way to participate in the long-term expansion of the AI economy.

Taiwan Semiconductor Manufacturing

Advanced chip manufacturing has emerged as a key constraint in the global race to build AI infrastructure. That dynamic has placed Taiwan Semiconductor Manufacturing(NYSE: TSM), the world's largest foundry, at the center of the global AI supply chain.

In this year's first quarter, the company reported revenue of $35.9 billion, up over 39% year over year. Advanced nodes, defined as 7-nanometer and below, accounted for 74% of wafer revenue, highlighting strong demand from high-performance computing and AI workloads. Gross margin rose 3.9 percentage points sequentially to 66.2%, while operating margin improved 4.1 percentage points sequentially to 58.1%.

TSMC is also benefiting from the shift from generative AI to more compute-intensive agentic AI workloads. As AI models process more tokens and require higher performance, the need for cutting-edge silicon is increasing, directly benefiting TSMC's advanced manufacturing capabilities.

However, the supply of advanced chip manufacturing capabilities remains constrained. TSMC is also strengthening its technological lead, with 3-nanometer capacity expanding globally and 2-nanometer already ramping with strong customer interest. While the company is guiding for 2026 capital expenditures toward the high end of its $52 billion to $56 billion range, capacity is expected to remain tight for the foreseeable future.

This combination of constrained supply, strong demand, and technology leadership positions TSMC to sustain both pricing power and long-term growth.

Datadog

Rising spending on AI infrastructure is also driving demand for software that can monitor, manage, and optimize increasingly complex AI systems. As AI adoption accelerates, organizations are dealing with an explosion of complexity across infrastructure, applications, and data. AI is also making systems harder to manage, as faster development cycles and the rise of AI agents increase interdependencies. Subsequently, the growing need for visibility is placing Datadog (NASDAQ: DDOG) in a strong position within the AI ecosystem.

The company has expanded beyond traditional cloud monitoring into a broader observability platform covering infrastructure, applications, logs, and security. This unified approach helps break down silos across teams and data. Datadog now generates over $1.5 billion in annual recurring revenue (ARR) from infrastructure monitoring, along with more than $1 billion each from log management and application performance monitoring (APM).

Datadog already has a strong presence in the AI ecosystem. The company serves around 14 of the top 20 AI-powered companies. Of its roughly 650 AI customers, 19 spend more than $1 million annually on the company's products.. At the same time, the company is investing heavily in its platform, spending over $1 billion annually on research and development in 2025. The company also has roughly half of its 4,000 engineers focused on core platform capabilities.

The company expects to benefit from increasing cross-selling within its customer base. With Gartner expecting public cloud spending to exceed $1 trillion by 2027 while still representing only about 16% of total global tech spend, the long-term opportunity for observability and monitoring tools remains significant. Datadog can offer a differentiated way to invest in the ongoing AI boom.

Manali Pradhan, CFA has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Datadog, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Gartner. The Motley Fool has a disclosure policy.