🔥 2026 AI List Deep Dive: Do You Agree with Wedbush’s Picks?

Dan Ives just refreshed his AI-30 winners list for 2026 — and the reshuffle says a lot about where the next wave of AI gains may come from.

He expects Big Tech to push another ~20% climb in 2026 as AI shifts from hype to real commercial scale.

Here’s the in-depth breakdown with added context, signals, and risks. ⚡️

⸻

1) What Wedbush Actually Changed — and Why It Matters 🧭

Ives’ latest update moved the list away from classic SaaS giants and toward GPU infra, data infrastructure, and commercial-ready platforms.

Adds ➕: CoreWeave, IREN, Shopify

Removals ➖: ServiceNow, Salesforce, SoundHound

Why this is meaningful:

• ⚙️ Compute capacity becomes the bottleneck → GPU clouds gain pricing power

• 🧠 Data infrastructure becomes the monetization layer → AI is useless without clean, integrated data

• 🏭 Vertical/embedded AI wins → companies who can convert pilots into ARR will outperform

Ives is signaling that the money in 2026 comes from infra + data, not just software front-ends.

⸻

2) SaaS Earnings Backdrop — Mixed but Improving 📊

Recent SaaS earnings show a split:

• 📈 Salesforce raised FY2026 guidance, citing AI product traction (Agentforce, Data360)

• ⚠️ But many SaaS names still trade on hope rather than AI ARR

What the market is rewarding now:

• ✔️ Clear disclosure of AI-driven ARR

• ✔️ Strong net retention

• ✔️ Demonstrated AI upsell into existing enterprise customers

What the market is punishing:

• ❌ Weak AI monetization clarity

• ❌ Slowing revenue guidance

• ❌ High valuations without ARR proof

SaaS isn’t dead — but the bar is higher.

⸻

3) Snowflake — Buy the Dip or Value Trap? ❄️🤔

Snowflake’s recent pullback triggered two opposite camps:

Bull Case 🟢

• AI needs structured, accessible data → Snowflake is at the center of that

• More production AI = more compute + more Snowflake usage

• Long-term runway remains massive

Bear Case 🔴

• Valuation still rich based on several DCF models

• Cloud provider competition could squeeze margins

• Growth premium already priced in

Balanced Take 🎯

The dip is interesting — but requires discipline.

Start small (2–4% initial allocation), scale only if:

• ARR accelerates

• Retention trends hold

• AI-specific revenue disclosures strengthen

Snowflake remains a high-beta AI infrastructure play, not a safe bargain.

⸻

4) Best AI Picks for 2026 — Category Breakdown 🧩

A. Hyperscalers / AI Platforms 👑

• Microsoft — Azure AI + enterprise bundling

• Nvidia — datacenter GPU dominance

B. GPU / Specialized Compute Providers ⚡️

• CoreWeave — GPU cloud capacity play

(One of the biggest beneficiaries of model training demand)

C. Data & Analytics Infrastructure 🧠

• Snowflake (SNOW)

• MongoDB / Confluent (data pipeline ecosystems)

D. Vertical/Enterprise AI SaaS 🏢

• Salesforce — strong AI ARR, though removed from Ives list

• Shopify — embedded AI commerce workflows (added to Ives list)

E. Cybersecurity Beneficiaries 🔐

• Palo Alto Networks, CrowdStrike, Zscaler

(AI models = new attack surfaces → security demand rises)

⸻

5) ETF vs Stock-Picking — Which Is Better? 💼

ETF Route (IGV) — Safe & Lazy 👍

Broad SaaS exposure, reduced single-stock risk.

Great if you want AI exposure without daily monitoring.

But… it may underperform concentrated winners.

Stock Picking — Higher Alpha, Higher Risk 🚀

You can overweight the actual mega-winners (NVDA, SNOW).

But requires research, risk tolerance, and volatility management.

Rule of thumb:

If you’re not active:

➡️ Use IGV ETF + 1–2 satellite AI names (NVDA, SNOW, MSFT)

⸻

6) Portfolio Examples (Illustrative Only) 🧪

Conservative

• 80% IGV

• 15% MSFT

• 5% NVDA

Balanced

• 50% IGV

• 15% SNOW

• 15% MSFT

• 10% NVDA

• 10% cash

Aggressive

• 30% IGV

• 25% NVDA

• 20% SNOW

• 15% GPU/cloud (e.g., CoreWeave)

• 10% cash

⸻

7) Key 2026 Risks to Watch ⚠️

• 🛑 AI monetization slows → SaaS multiples compress

• ⛓️ Compute shortages or GPU cost spikes

• 📉 Macro/rate shock

• 🧨 Cloud competition eroding margins

• 🧮 AI revenue overstated or delayed

Every AI thesis is only as strong as the next quarter’s ARR.

⸻

8) What to Track Quarterly (Very Practical) 📅

• 🧾 AI-specific ARR numbers

• 📈 Net retention

• 🧠 Customer adoption of AI modules

• ⚙️ GPU supply & pricing

• 💵 ETF flows into IGV / software

• 📉 SNOW logos tied to AI workloads

These metrics reveal the real winners early.

⸻

9) Final Takeaways 🎯

• Wedbush’s picks reflect the shift toward compute + data, where AI value actually forms

• SaaS is not dead, but must show AI ARR, not AI marketing

• Snowflake dip = conditional buy → depends on retention + AI revenue

• Use IGV if you want easy exposure; supplement with selective stock picking

• 2026 AI winners will come from infrastructure, data, and enterprise adoption

⸻

Summary Post 🐯🔥

🔥 2026 AI List: Wedbush says the next winners aren’t just SaaS — they’re compute ⚙️ + data 🧠.

SaaS earnings are mixed: Salesforce raised guidance on AI ARR 📈, but others lag.

Snowflake dipped — bulls say opportunity, bears say valuation still heavy ❄️🤔.

My take: buy with discipline, watch ARR & retention closely.

Infra (NVDA/CoreWeave), data platforms (SNOW), enterprise AI (MSFT), and cybersecurity (CRWD/PANW) look strongest for 2026.

ETF route like IGV 🧺 works if you want diversified exposure.

Which AI name is your top conviction for 2026? 🚀🔥