The term "artificial intelligence (AI) stocks" has become about as precise as saying "internet companies" in 1999. Is it the chip makers powering machine learning? The tech giants deploying algorithms? The startups promising to revolutionize everything?

This Datalign guide is all about investing in AI stocks. It lists terms, questions, and insights to help you evaluate AI companies in ways that align with your life and goals. 

Let’s dive in!

What Are Useful Terms In Understanding AI Companies?

Yes, we're seeing exciting headlines about investing in AI stocks – like OpenAI potentially generating more than $125 billion by 2030. Tech companies are adjusting their AI expansion timelines and everyone's still figuring out how these amazing technologies will actually make money consistently. This is actually good news if you're thinking long-term. But what exactly are AI companies?

Think of AI companies as being organized into different, connected categories. Each category presents distinct possibilities for growth, but also its own set of potential downsides that investors need to consider.

• Foundations: Hardware providers (chips, data centers) offering stability with established revenue streams

• Intelligence: Core AI model developers with higher risk/reward profiles but longer paths to profitability

• Applications: Companies applying AI to solve specific industry problems, often with clearer revenue models

• Integrations: Established businesses enhancing existing products with AI capabilities

AI isn't just one category; it's more like an ecosystem with different interconnecting layers. Understanding these layers is useful because it helps you see the kinds of opportunities and risks involved. This can help you can make smarter choices about where to put your money based on what you're comfortable with and what you're trying to achieve.

What Five Questions Should I Be Asking About AI Stocks?

When researching AI companies or talking with your financial advisor, these questions help you move beyond headlines to find opportunities that align with your situation. Each question includes practical ways you can start finding answers, even without specialized technical knowledge.

1. Which part of the AI landscape fits my risk tolerance?

Why this matters: Different AI categories carry different levels of volatility and potential reward.

How to find answers: Established chip makers and cloud computing companies typically offer more stability than early-stage AI startups. Consider how you've reacted to previous market downturns - did you panic sell or stay the course? Your comfort with volatility helps determine whether to focus on established AI stocks or newer ventures.

2. How does the development timeline of AI technologies match my investment horizon?

Why this matters: Some AI stock investments may take years to deliver returns while others generate revenue today.

How to find answers: Review company updates for mentions of current revenue versus future potential. If you need your investment returns within 5 years, focus on companies already generating AI-related revenue rather than those promising breakthroughs "eventually."

3. How can I evaluate AI claims in company reports and press releases?

Why this matters: Nearly every company claims AI capabilities, but implementation quality varies dramatically.

How to find answers: Look for specific examples and measurable results rather than vague statements. When a company announces an AI initiative, do they explain exactly how it improved their business with numbers? If not, healthy skepticism is warranted.

4. Which established companies in my portfolio are successfully implementing AI?

Why this matters: You may already own companies benefiting from AI without realizing it.

How to find answers: Review recent investor presentations from companies you own. Many non-tech businesses now highlight AI initiatives in their quarterly reports. Look for specific examples of how they're using the technology to improve operations or products.

5. How should AI investments be weighted in my portfolio relative to other technologies and sectors?

Why this matters: Even promising technologies require appropriate allocation within a diversified portfolio.

How to find answers: A common approach is to limit any single technology theme to 5–10% of your total investments, as recommended by Finimize, a financial education platform. Portfolio diversification is intended to provide meaningful exposure while protecting from sector-specific downturns. Your advisor can help determine the right percentage based on your complete financial picture.

The Aligned Perspective: Investing in AI Stocks

When it comes to investing in companies using or developing AI, there's no universal recommendation that works for everyone. The real advantage comes from treating AI as one part of your broader investment strategy, approaching it with thoughtful questions rather than getting caught up in the latest hype.

Think about it: your investment goals, timeline, and comfort with market swings are uniquely yours. The questions we've explored help you and your advisor have more productive conversations about where AI fits within your complete financial picture. For additional information on the topic of AI stocks of 2025, read our guide.

At Datalign, we see this kind of personalized approach as essential. These questions are a starting point for discussions that go beyond headlines to focus on what actually makes sense for you.