2026 Predictions!
The Year of Liquidity. $1T+ in new public market cap from AI/tech IPOs and direct listings. The private-to-public logjam breaks. Potential candidates: SpaceX, Anthropic, OpenAI, Databricks.
Google Gains Ground. Said it last year “Don’t forget Google.” 2026: Gemini may or may not be the best model... doesn’t matter. It wins because of smart deals (Apple, Reliance Jio) + distribution (Gmail, Maps, Search). 2 billion users don’t pick models... they use defaults.
The great AI sorting. Users actively compare. ChatGPT for X, Claude for Y, Gemini for Z. They pick favorites based on vibes and lived experience. Memory compounds. Switching costs rise. The AI landscape ends 2026 more fragmented than it started.
AI learns to speak first. Not a chatbot waiting in a box. Ambient. Contextual. It notices, nudges, checks in. The relationship inverts.
Open source keeps climbing. Agents learn to mix and match... frontier for the heavy lifting, fine-tuned OSS for everything else. The hybrid stack becomes default. The cash register rings at the model serving platforms.
The Meta question. Nothing major since Llama 4 in Q1 2025. Key departures. No long-term research bets. 2026 is time to deliver.
The bar rises. Labs spending $5-25B on training this year need to show $5-25B in gross margin over next 12-24 months. R&D payback becomes the metric as they get ready for public markets.
Consumer AI experiences growing pains. 40+ countries hold elections including US midterms. AI tries to stay neutral. The “AI is swaying elections” narrative takes hold anyway.
8b) Consumer AI easy money zone is over. 8B people on the planet of which 1B already using AI up 3x from last year. Tripling from here means becoming the #1 consumer app globally. For context, the most used consumer apps: Facebook, Whatsapp, Youtube etc. are around the ~3B user scale.
What am I missing? Which one ages worst? What’s your most wild prediction for AI in 2026? I’d love to hear from you.
2025 Scorecard
A year ago, I made 6 predictions. Here’s how they held up.
1) AI shakeout intensifies. Frontier labs face consolidation or acquihires.
✅ Nailed it. Big Tech deployed $40B+ through “license & acquihire” structures: Microsoft + Inflection ($650M), Amazon + Adept ($330M), Google + Character.AI ($2.7B), Google + Windsurf ($2.4B), Meta + Scale AI ($14.3B), Nvidia + Groq ($20B). The playbook: license the IP, hire the team, leave the shell behind.
2) Enterprise AI blossoms. SWE orgs transform. Compute vs payroll tradeoff becomes real.
✅ Hit. Software Engineering, Customer Support, Legal, and Healthcare being some areas where it saw 10x adoption in 2025.
3) New hardware form factors with AI as killer app.
❌ Miss. Ray-Ban Meta glasses were modest. The AI killer app lives in your phone and browser, not new hardware.
4) Personalization improves 10x. Usage concentrates in a super app.
🟡 Partial. Memory features shipped (ChatGPT, Claude, Gemini all have it). Context windows hit 10M+ tokens. But the super app didn’t emerge. ChatGPT hit 800M+ weekly users but isn’t replacing your phone apps. Yet…
5) Startups collide with frontier models. Consolidation accelerates.
✅ Hit. Frontier models ate “AI wrapper” territory. The value chain compressed to model providers or deeply vertical apps. AI acquihires totaled $40B+. ZIRP-era startups faced down rounds or shutdowns. The IPO dam held... but 2026 is when it breaks.
6) Big tech stays dominant. Don’t forget Google.
✅ Nailed it. Hyperscalers spent $200B+ on AI infrastructure and absorbed the best talent. Google recovered: Gemini improved, deep integration into Gmail/Maps/Search, strategic deals with Apple and Reliance Jio. Distribution + deals + improved models = momentum.
Final Score
4 out of 6 hit. 1 partial. 1 miss.
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