Why Unity fell, but utility is rising.
In partnership with Rad Intel | $10K Investment in Nvidia Could've Made $2.5M | Imagine investing $10K into Nvidia a decade ago—today that's $1.25M. That's the power of getting in early on the right startup. We think RAD Intel is next. They're applying AI to solve a problem every marketer faces: how to reach the right audience with the right message. Backed by Adobe, Fidelity Ventures, and already in use by Fortune 1000s - this company's valuation has soared 4900% in just 4 years*. | RAD Intel's software is built for AI 2.0: intelligent targeting that powers real ROI. They've already reserved a Nasdaq ticker symbol, $RADI and this is a rare opportunity to get in on a high-growth | | | | AI software company at the ground floor. | The company is offering shares at just $0.85 right now. | Don't let this be another "I wish I had…" moment. The opportunity is now. | 👉 Lock in $0.85 shares today | |
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| | The AI Market Is Splitting in Two | January's market action delivered a quiet but important signal. | AI is no longer moving as one trade. | Over the past two weeks, several AI-linked stocks tied to gaming and speculative use cases fell sharply after Google unveiled new generative tools. Unity, Roblox, and other names sold off hard as investors reassessed where AI actually creates durable value. | At the same time, companies with clear monetization paths held up — or rallied. | Meta's latest earnings reinforced the point: AI spending is being rewarded only when it improves measurable business outcomes, particularly advertising efficiency and targeting. That divergence matters. | It tells us the market is moving past novelty and toward return on investment. | From "Can It Do This?" to "Does It Pay?" | For most of the last decade, AI was evaluated on capability. | How big is the model?
How fast is the chip?
How impressive is the demo? | In 2026, the question has changed. | Does it work — commercially? | Executives are under pressure to justify AI budgets. Boards want to see efficiency, not experiments. That's why capital is rotating away from generalized tools and toward application-specific systems that directly affect revenue. | Marketing sits squarely in that category. | It is one of the largest line items on corporate budgets — and one of the least efficient. AI that improves targeting, timing, and message alignment doesn't need to be revolutionary. It needs to be reliable. | Why Smaller AI Companies Matter Again | Another lesson from January's tape: size is no longer a guarantee. | Large AI platforms dominate headlines, but they also face rising costs, regulatory scrutiny, and expectations that are hard to satisfy. Smaller, focused companies operate differently. | They: | solve a narrow, expensive problem integrate into existing workflows scale alongside adoption, not hype
| Historically, that's where many of the best risk-adjusted returns emerge — especially after the market has already priced in the obvious winners. This is how earlier tech cycles played out. | The infrastructure giants came first.
The specialized applications followed. | A Measured View | Not every early-stage AI company becomes a breakout success. And skepticism is healthy. | But dismissing all smaller opportunities because Nvidia already ran misunderstands how technology diffusion works. | The first wave builds the platform.
The second wave makes it useful. | Markets are now paying attention to that second wave. | | | | A Calm Close | The past month made one thing clear: AI is no longer being valued for what it might do. It's being valued for what it delivers. | As capital becomes more selective, companies that turn intelligence into practical results quietly move to the front of the line. | That shift rarely makes headlines at first.
But it's often where the next chapter begins. |
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| | | How did you find today's briefing? | |
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| | Written by Deniss Slinkins
Global Financial Journal |
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