AI Software Is Creating the Next Billion-Dollar Giants
RAD Intel Is One of Them |
Just like Microsoft and Adobe rode the software wave in Web 1.0, RAD Intel is riding the AI software wave in 2025. Their product helps brands instantly find the right audience and message using AI – solving the #1 waste in marketing: misfired ad spend. |
Already trusted by a who's-who of Fortune 1000 brands and leading global agencies – with recurring seven-figure partnerships in place. |
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With a Nasdaq ticker reserved, $RADI, it's early – but very real. Investors can still buy shares at just $0.85 through a Regulation A+ round. |
AI software will create the next set of billion-dollar winners – RAD Intel may be your shot at being part of that now. |
$0.85 Won't Last – Secure Your Shares Today |
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*This valuation has been set by RAD Intel. |
DISCLOSURE: This is a paid advertisement for RAD Intel's Reg A+ offering and involves risk, including the possible loss of principal. Please read the offering circular and related risks at invest.radintel.ai. |
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BONUS CONTENT |
Big Tech is on pace for historic AI capex |
Reuters reported that Microsoft, Meta, Alphabet and Amazon are expected to lift AI spending by ~30% to more than $500 billion this year—an unprecedented outlay that's putting investor scrutiny on payoffs. |
Bloomberg's compilation puts a similar stake in the ground: combined capex for the "big four" is expected around $505B, up from roughly $366B estimated for 2025. |
That's not "incremental spending." That's an infrastructure cycle. |
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The new shocker: Meta just told you how big this is |
Meta's latest update was the clearest "arms race" number we've seen: |
2026 capex forecast: $115B to $135B 2025 capex: about $72B (as referenced in multiple reports) Q4 revenue: roughly $58.14B (+24% YoY, per Reuters) Total 2026 expenses: $162B to $169B
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Meta is essentially saying: "Ad cash is funding the superintelligence buildout." And the market rewarded the clarity (shares popped after-hours in coverage). |
What investors should notice |
Meta is not pretending this is cheap. It's telling you the spend is going vertical and daring the market to stay invested. |
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Microsoft: the spending is massive — and the market is demanding proof |
Microsoft's quarter told the other half of the story: spending can be so large that it becomes the narrative. |
Multiple reports highlighted: |
Quarterly capex: $37.5B (about +66% YoY) Two-thirds of that capex tied to "short-lived assets" like GPUs/CPUs (i.e., the AI iron). Cash flow from operations: $35.8B (+60% YoY, per earnings highlights coverage). Microsoft's demand signals include a referenced backlog around $625B in recent write-ups.
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This is the key tension: |
Microsoft is building the factory, but investors want to see the factory sell product, not just buy equipment. |
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So… what opportunities does this spending unleash? |
When a spend cycle is this large, the best "cheap investor" move isn't always chasing the biggest AI brand. It's finding the second-order winners — the companies that monetize the buildout regardless of which model wins. |
Here are the most investable "where the money flows" buckets, with concrete evidence from the last few days. |
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1) GPU/accelerator supply chain — the obvious toll collectors |
If Microsoft is spending $37.5B in a quarter and Meta is telegraphing up to $135B in a year, a big portion lands in: |
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That's why the "AI hardware stack" remains central: it's where budgets convert to invoices fastest. |
What to watch in this bucket |
delivery cadence (supply constraints easing or worsening) pricing power (are vendors still able to hold premium pricing?) lead times (still long = demand pressure remains)
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2) Data center power + cooling — the "keep it running" economy |
This is the quietly explosive part of AI: models don't just need chips. They need electricity and thermal management at scale. |
Meta explicitly framed its AI capex push around building massive infrastructure (data centers, capacity expansion, partnerships). |
Why this is investable
Even if the "best model" changes, the physical requirements don't: |
higher rack density better cooling (liquid cooling, thermal systems) UPS, switchgear, transformers, backup electrical distribution + reliability
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This is the picks-and-shovels layer where "AI enthusiasm" turns into purchase orders. |
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3) AI infrastructure services — the "rent the shovels" trade |
One detail in Reuters' Meta coverage jumped out: Meta is leaning on third-party providers (cloud partners) as internal capacity is built out. |
When the demand for compute outpaces the ability to build instantly, the market tends to reward: |
specialized GPU cloud providers infrastructure hosting and build partners deployment and data center services
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That's a bridge phase of the cycle — and it can be lucrative while it lasts. |
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4) Software that reduces AI cost — the underrated winner |
When companies start spending hundreds of billions, CFOs show up. |
The first question shifts from "Can we build it?" to: |
"Can we run it cheaper?" "Can we optimize inference?" "Can we cut training waste?" "Can we allocate compute more efficiently?"
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In a world where cloud margins get pressured by AI infra, optimization software becomes a real lever — and can be a stealth winner as companies chase efficiency. |
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5) The "AI payoff" companies — the market now rewards proof, not promises |
Reuters summed up the mood: investors are increasingly demanding payoffs from heavy AI spending, and punishing companies when spending rises faster than growth signals. |
So the opportunity isn't just in the shovels. It's also in identifying which platforms can show: |
backlog / consumption acceleration margin stabilization clear monetization pathways (subscriptions, usage-based revenue, enterprise expansion)
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Meta can fund its buildout through ads — that's why its spend plan can be "absorbed" psychologically by investors. Microsoft can too, but the margin and growth optics matter more when capex prints keep surprising. |
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The Cheap Investor playbook for this moment |
If you're trying to invest around this cycle (without getting wrecked by hype), here's the approach: |
1) Don't fight the spending — map it |
The numbers are telling you the trend is real: $115B–$135B at Meta, $37.5B quarterly at Microsoft, and $500B+ spending scale for the big cohort. |
2) Prefer "paid first" businesses |
In every infrastructure cycle, the earliest winners are: |
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3) Use valuation discipline inside AI |
The market is now separating: |
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The best bargains often hide in the second bucket. |
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What could happen next (and what could go wrong) |
What could go right in 2026 |
AI demand stays strong, supply constraints ease, and "capex → revenue" conversion improves. Infrastructure buildout unlocks a second wave: lower costs, wider adoption, more enterprise deployments.
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What could go wrong |
The buildout overshoots near-term demand. Margins stay under pressure longer than investors expect. Spending keeps rising, but monetization lags—leading to multiple compression even if revenues grow.
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That's why this cycle rewards discipline: don't just own AI. Own the parts of AI that get paid first. |
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Disclaimer: This article is for informational purposes only and does not constitute investment advice. Investing involves risk, including the potential loss of principal. Always do your own research before making investment decisions. |
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