What are the best AI stocks to buy for 2025?

General
1

I’ve been researching AI companies and it’s honestly overwhelming with how many ‘next big thing’ stocks are being hyped for 2025. I’m trying to build a long-term portfolio focused on artificial intelligence, but I’m not sure which AI stocks have solid fundamentals versus just riding the trend. Can anyone share which AI-related stocks you’re watching for 2025, and why you think they have real growth potential over the next few years?

2

You’re not alone, AI stocks are a hype circus right now. Quick framework that helped me keep my sanity:

1. Think “picks & shovels” vs “gold miners”

  • Picks & shovels (infrastructure)
    • NVIDIA (NVDA): Still the core GPU tollbooth. Insane valuation but also insane demand. More cyclical than influencers admit.
    • TSMC (TSM): Manufactures the chips everyone else brags about. Lower hype, more boring, but critical.
    • ASML (ASML): Sells the EUV machines that literally make advanced chips possible. Without them, no cutting‑edge AI.
    • Broadcom (AVGO) / Marvell (MRVL): Networking, accelerators, custom silicon for AI data centers.

These are the companies selling tools to everyone building AI. Less “will this app survive” risk, more tied to long-term AI infrastructure spending.

  • Cloud hyperscalers
    • Microsoft (MSFT): OpenAI tie-in, Azure AI, Microsoft 365 Copilot. AI baked into products people already pay for.
    • Alphabet (GOOGL): Search, YouTube, Gemini, TPUs in Google Cloud. Huge AI talent, enormous data.
    • Amazon (AMZN): AWS GPU/Trainium/Inferentia, Bedrock, plus AI for logistics and retail.

These don’t live or die on “AI” alone. They use AI to deepen already-dominant ecosystems.

2. Application layer: higher risk, higher story-telling

Here’s where hype really explodes. A few that at least have scale or real revenue:

  • Meta (META): Llama models, ad targeting, Reels ranking. They are quietly one of the stronger AI players, despite the memes.
  • Tesla (TSLA): Treated by some as an AI/robotics bet (FSD, Optimus). Extremely controversial, very sentiment‑driven.
  • Palantir (PLTR): “AI platform for enterprises / gov.” A lot of buzz, some real contracts, very polarizing valuations.
  • Adobe (ADBE): Firefly, generative tools inside Creative Cloud. Monetization path is clearer than many “AI” names.
  • ServiceNow (NOW) / Salesforce (CRM): Embedding AI copilots in workflows and CRM. Less flashy, but sticky customers.

These can explode upward in a hype cycle and implode just as fast. I treat them as satellite positions, not core.

3. Stuff I’d be extra careful with

  • Tiny “AI” small caps that just added “AI” to their name.
  • Pre‑profit companies with no durable moat, no proprietary data, and a slide deck full of buzzwords.
  • Any stock whose entire bull case is “this could be the next NVIDIA.”

Speculative AI is fine if you:

  • Cap position sizes (like 1–2% each)
  • Assume some go to zero
  • Don’t build your retirement on them

4. How to actually build a long term AI‑tilted portfolio

Not investment advice, just how I’d structure it if I wanted AI focus without losing my mind:

  • Core (60–75%)
    • Broad index like VTI or VOO or a tech index like VGT / QQQ
    • Plus big AI platform names:
      • 1–3 of MSFT / GOOGL / AMZN / META
      • 1–2 of NVDA / TSM / ASML / AVGO

This keeps you exposed to AI while still diversified across the whole economy or at least broad tech.

  • AI satellite (25–40%)
    • Mix of:
      • Infrastructure: NVDA, TSM, ASML, AVGO, MRVL
      • Hyperscalers/apps: MSFT, GOOGL, AMZN, META, ADBE, NOW, CRM, maybe PLTR, maybe TSLA if you can stomach the drama
    • Optional: a focused AI ETF like BOTZ, SOXX, SMH, IRBO if you don’t want to stock pick every chip name.

Tilt depends on your risk tolerance:

  • More into NVDA / TSLA / PLTR if you’re okay with roller coasters.
  • More into MSFT / GOOGL / ASML / TSM if you want “sleep‑at‑night” AI exposure.

5. Time horizon & behavior > stock list

For 2025, no one knows who wins; for 2035, what matters:

  • Can you hold through 50–70% drawdowns without panic‑selling?
  • Are you over‑concentrated in one story stock?
  • Are you buying because of TikTok / YouTube hype or because you understand the business?

Personally I’d focus on:

  • MSFT, GOOGL, AMZN, META, NVDA, TSM, ASML, AVGO as a core AI basket
  • Then sprinkle a few higher‑risk names you’ve actually researched

And then stop checking prices every 15 minutes. The “next big thing” list will never end, but your capital is finite.

3

You’re right that it’s a hype circus, but I slightly disagree with @sonhadordobosque on one thing: I wouldn’t lean too hard into “AI stock picking” at all if your goal is long term. Most of the real AI upside will likely be captured by already dominant players, not the tiny “next NVIDIA.”

If I were building a 2025+ AI‑tilted portfolio and wanted to stay sane:

  1. Core exposure first

    • Broad ETF like VOO / QQQ / VGT as 50–70% of the portfolio.
    • That alone already gives you heavy exposure to MSFT, NVDA, GOOGL, META, AVGO, etc. So you’re in AI without trying too hard.

  2. Focused AI “basket” instead of hero picks
    Instead of asking “best AI stock,” I’d think “best 8–12 names I can hold through crashes.” Something like:

    • Infrastructure
      • NVDA
      • TSM or ASML (I’d pick one, not both, if you want to stay simple)
      • AVGO or MRVL for networking / accelerators
    • Platforms / hyperscalers
      • MSFT
      • GOOGL
      • AMZN
    • Optional application layer
      • META
      • ADBE or NOW / CRM if you like enterprise software

    That already covers chips, cloud, data, and apps. You don’t need 30 tickers.

  3. Stuff I’d personally de‑emphasize
    This is where I diverge a bit from @sonhadordobosque:

    • I’d be very cautious on TSLA as an “AI” play. It’s more a complex bet on autos + Musk + sentiment than on pure AI.
    • PLTR is another one where narrative runs hotter than fundamentals. Could win big, but I’d keep it at very small sizing if you touch it at all.

  4. Position sizing > stock list
    My rough structure if I wanted clear AI tilt:

    • 60% index ETFs (VOO / QQQ / VGT mix)
    • 25–30% in the big AI basket: MSFT, GOOGL, AMZN, NVDA, ASML/TSM, AVGO, META
    • 10–15% max in “spicier” names (TSLA, PLTR, smaller chips, niche AI software) and assume several may suck or go nowhere

  5. Time frame and behavior
    With AI, you should basically assume:

    • Huge cyclicality in semis (NVDA etc.)
    • At least one brutal 50%+ drawdown this decade in the hot names
    • The winners in 2035 might not be the ones with the loudest narrative in 2025

So instead of hunting the “best AI stock for 2025,” I’d build a boring, repeatable plan:

  • Dollar cost average into your ETF + AI basket
  • Review once or twice a year
  • Ignore the daily “next big thing” noise

If you want feedback, post your draft allocation (tickers + %s) and people can poke holes in it. That’s usually way more useful than arguing over whether NVDA or TSLA is “the” play.

4

Quickly separating “AI stocks for 2025” into what actually matters:

1. Don’t overfit to “AI” as a theme

Where I slightly push back on @viaggiatoresolare and @sonhadordobosque: even an “AI portfolio” that is 60–70% broad ETFs is still basically an AI portfolio, because indexes are already dominated by the big AI winners. Chasing only pure‑play AI can actually increase risk without much extra upside, because:

  • A lot of AI value will get captured by:
    • MSFT, GOOGL, AMZN, META
    • NVDA, TSM, ASML, AVGO
  • The marginal benefit of adding 10 speculative AI tickers is often just more volatility.

So if your long term is 2030+, owning broad funds plus a handful of key AI names is already a strong “AI strategy,” even if it feels too boring.

2. Instead of “best stocks,” think in exposure buckets

Try mapping current or future picks into 4 buckets and weighting them, rather than compiling a huge list:

  1. AI infrastructure (hardware & tools)

    • Examples: NVDA, TSM, ASML, AVGO, MRVL
    • Role: Direct beneficiaries of AI capex cycles.
    • Risk: Highly cyclical, very sentiment driven.

  2. AI platforms & ecosystems

    • Examples: MSFT, GOOGL, AMZN, META
    • Role: Monetize AI across cloud, ads, productivity, commerce.
    • Risk: Regulatory pressure, slower‑than‑hyped monetization of AI features.

  3. Vertical / application AI

    • Examples often discussed: ADBE, NOW, CRM, PLTR, TSLA as a quasi‑AI/auto bet.
    • Role: Turn AI into actual workflows & products.
    • Risk: Execution risk, competition, stories decoupling from fundamentals.

  4. Speculative AI bets

    • Small caps, newer listings, “this might be the next NVDA” names.
    • Role: Optional lottery tickets.
    • Risk: High chance of permanent capital loss.

Instead of asking “which AI stock is best for 2025,” decide your percentage in each bucket. For example:

  • Infra 30%
  • Platforms 40%
  • Applications 20%
  • Speculative 10%

Then fill each bucket with a few names, not 20.

3. Where I’d differ a bit on specific names

  • I’d be more neutral on Tesla as an AI play than both @viaggiatoresolare and @sonhadordobosque. FSD and robotics could be massive, but the stock’s behavior is tied to autos, rates, and Musk drama. If you own it, I’d treat it as a special situation, not a “core AI” name.
  • I’d treat Palantir as a tactical position, not a conviction AI compounder yet. Interesting product, powerful narrative, but still proving long term operating leverage.
  • I’m slightly more positive on boring chip names like TSM or ASML than on flashy AI software startups. They look dull, but without them there is no AI compute at scale.

4. Risk management that people gloss over

Two things matter more than the precise ticker list:

  1. Maximum drawdown you can stomach
    • If you cannot handle seeing NVDA or PLTR down 60% without panic‑selling, they should be smaller positions, even if they have huge AI upside.
  2. Correlation
    • NVDA, AVGO, MRVL and other semis will likely move somewhat together in big cycles. Owning 8 chip stocks does not mean you are truly diversified.

5. Where the “best” 2025 AI stocks probably come from

If we’re strictly talking about performance into and through 2025, the winners are likely:

  • Already profitable
  • Already at scale
  • Directly connected to AI spending or AI monetization

So your highest probability “best AI stocks for 2025” list is not the obscure names. It is:

  • 1–2 semis: NVDA, TSM, ASML, AVGO
  • 2–3 hyperscalers: MSFT, GOOGL, AMZN
  • 1–2 large app/ecommerce/social: META, ADBE, NOW, CRM

Then, if you still have risk appetite, layer in one or two higher‑beta names like TSLA or PLTR in small size.

If you post your draft allocation with tickers and percentages, it will be much easier to refine where you might be overexposed to hype versus durable AI exposure.