Fundamental Analysis
The 10 Numbers That Tell You Everything About an AI Stock
You don't need a 50-page analyst report. These 10 metrics tell you whether an AI company is building real value or burning cash on hype. All of them are free to look up. Most take 30 seconds to find.
The Quick Screen
Why These 10 and Not Others
There are hundreds of financial metrics. Most are noise for AI stock evaluation. Revenue growth matters. Return on invested capital matters. Accounts receivable aging does not tell you whether an AI company will win or lose its market.
These 10 metrics were selected for three reasons. They capture the economics specific to AI businesses. They are available for free on Yahoo Finance, FactSet, or in company earnings releases. And together, they tell a complete story in under five minutes.
The metrics are organized into three groups: growth, profitability, and valuation. Growth tells you if the business is expanding. Profitability tells you if the expansion creates value. Valuation tells you if the stock price already reflects both.
No single number tells the whole story. A company with 50% revenue growth and negative gross marginsThe percentage of revenue left after subtracting the direct costs of producing the product. Higher is better. is a different animal from one with 20% growth and 70% margins. The power is in the combination.
Group 1: Growth
Is the Business Expanding?
#1
Revenue Growth Rate (YoY)
Year-over-year percentage change in total revenue. Find it on the income statement in any earnings release. Tells you how fast the company is adding new business.
AI benchmark: 25%+ is strong. 50%+ is exceptional. Under 15% means the AI tailwind isn't hitting this company.
#2
Revenue Acceleration or Deceleration
Is the growth rate speeding up or slowing down? Compare the last four quarters of YoY growth. If Q1 was 40%, Q2 was 35%, Q3 was 28%, growth is decelerating. That pattern matters more than any single quarter.
Green flag: accelerating growth. Red flag: three consecutive quarters of deceleration.
#3
Revenue Per Employee
Total revenue divided by headcount. Shows how efficiently the company generates income. AI companies should have high revenue per employee because software scales without proportional hiring. Find headcount in the annual report.
AI benchmark: $500K+ per employee is solid. $1M+ is excellent. Below $300K suggests the business isn't leveraging AI's scaling advantage.
NVIDIA generates roughly $5 million in revenue per employee. Microsoft generates about $1 million. Most early-stage AI startups generate under $200K. Revenue per employee separates companies that have found product-market fit from those still searching.
Group 2: Profitability
Does the Expansion Create Value?
#4
Gross Margin
Revenue minus cost of goods sold, divided by revenue. For AI companies, COGS includes compute costs (cloud or GPU), model training, and infrastructure. Gross margin tells you how much money the company keeps from each dollar of revenue before operating expenses.
AI benchmark: 60%+ for software. 50%+ for infrastructure. Below 40% is a red flag for margin sustainability.
#5
Gross Margin Trend
Is gross margin expanding or compressing over the last four quarters? This matters more than the level. A company at 55% and improving is in better shape than one at 65% and declining. Improving margins mean the business model is working at scale.
Green flag: 2+ percentage points of expansion over 4 quarters. Red flag: compression for 2+ consecutive quarters.
#6
Free Cash Flow Margin
Free cash flow divided by revenue. Free cash flow is operating cash flow minus capital expenditures. This is the ultimate profitability metric. It tells you how much actual cash the business generates relative to revenue. Accounting earnings can be manipulated. Cash flow cannot.
AI benchmark: 15%+ is strong. Negative is acceptable only for companies under $5B revenue that are investing heavily. Above $10B revenue and still negative? Problem.
#7
Capex Intensity (Capex / Revenue)
Capital expenditures as a percentage of revenue. AI companies spend heavily on GPUs, data centers, and infrastructure. High capex isn't automatically bad, but it reduces free cash flow. The question is whether the capex generates future revenue or just maintains the current level.
AI benchmark: Under 15% for software companies. 20-40% for infrastructure companies. Above 50% means the company is spending more on infrastructure than it earns in profit.
Profitability Snapshot: Major AI Companies
Gross margin and free cash flow margin, latest fiscal year
Data visualization showing profitability metrics for five major AI companies: NVIDIA with 75% gross margin and 52% free cash flow margin, Microsoft with 69% and 34%, Alphabet with 57% and 25%, Palantir with 80% and 28%, and OpenAI estimates at 45% and negative respectively.
| Company |
Gross Margin |
FCF Margin |
Capex/Rev |
Assessment |
| NVIDIA |
75% |
52% |
5% |
Cash machine. Low capex, high margins. |
| Microsoft |
69% |
34% |
25% |
Strong margins. Capex rising for AI infrastructure. |
| Alphabet |
57% |
25% |
22% |
Solid. Capex increasing for cloud and AI. |
| Palantir |
80% |
28% |
3% |
High margins. Low capex. Software model working. |
| OpenAI (est.) |
~45% |
Negative |
High |
Compute costs dominate. Revenue growing but margins thin. |
Group 3: Valuation
Is the Price Right?
#8
Forward P/E Ratio
Stock price divided by next 12 months of expected earnings per share. This is the market's price tag on future earnings. A forward P/E of 30x means investors pay $30 for each $1 of expected earnings. Higher means more growth is already priced in.
AI benchmark: 20-35x is fair for high-growth. 35-60x is expensive but defensible if growth exceeds 30%. Above 60x requires exceptional conviction.
#9
PEG Ratio
Forward P/E divided by expected earnings growth rate. Normalizes the P/E for growth speed. A company at 40x P/E growing 40% has a PEG of 1.0. The same P/E at 20% growth has a PEG of 2.0 and is twice as expensive relative to its growth.
AI benchmark: Below 1.0 is cheap. 1.0-1.5 is fair. 1.5-2.0 is premium. Above 2.0 means you need the company to beat analyst expectations.
#10
Price-to-Free-Cash-Flow
Market capitalization divided by trailing 12-month free cash flow. Similar to P/E but uses cash flow instead of earnings. Harder to manipulate. Tells you how many years of current cash generation you're paying for at today's stock price.
AI benchmark: Under 30x is reasonable. 30-50x is growth premium. Above 50x assumes massive cash flow expansion ahead.
Putting It Together
The Five-Minute Screen
Here is how to use all 10 numbers on any AI stock. Open Yahoo Finance. Pull the numbers. Fill in the mental scorecard. Takes five minutes, tells you 80% of what you need to know.
Green Lights
Revenue growth above 25% and accelerating. Gross margins above 60% and expanding. Positive free cash flow. Capex below 20% of revenue. Forward P/E under 35x. PEG below 1.5. A company with all six is rare and worth deep research.
Red Flags
Revenue decelerating for three quarters. Gross margins below 50% and compressing. Negative free cash flow above $10B revenue. Revenue per employee under $300K. PEG above 3.0. Any one of these should make you ask harder questions. Three or more together is a sell signal.
These 10 numbers are a screen, not a verdict. They tell you which companies deserve deeper research and which ones you can skip. The numbers don't replace judgment, but they focus your judgment on the companies that matter.
10
Ten numbers. Five minutes. Growth, profitability, valuation. If you can't find these numbers for a company, the company doesn't want you to find them. That tells you something too.
How I Built This
Metrics selected based on relevance to AI business models. Benchmarks derived from analysis of 30+ public AI and tech companies.
Benchmark Ranges
Derived from current AI company financials
The "good" and "bad" ranges are calibrated to today's AI market, not historical norms. A 60% gross margin would be exceptional in manufacturing but ordinary in software. These benchmarks are specific to AI companies as of 2026. They may shift as the industry matures and competition compresses margins.
Data Sources
Yahoo Finance, FactSet, company earnings releases
All 10 metrics can be found on free platforms. Yahoo Finance has revenue, margins, and P/E ratios. Earnings releases have capex and cash flow. Revenue per employee requires headcount from annual reports. The numbers are as current as the last reported quarter. Forward estimates change daily.
OpenAI Estimates
Based on press reporting, not audited financials
OpenAI is not publicly traded and does not file with the SEC. The gross margin and revenue estimates are based on media reporting and industry analysis. Treat them as directional, not precise. When OpenAI goes public, actual audited numbers may differ significantly.
Jesse Walker has been an individual investor for 30 years. Before that, he was a poker professional, which is where he learned that the best decision and the best outcome aren't always the same thing. He writes about financially navigating the uncertainties of AI.