As foundational AI costs balloon, investors are shifting their bets to scalable, workflow-integrated tools delivering real-world ROI.
The VC arms race is shifting from foundation models to real-world use cases—here’s what that means for ecommerce, fintech, and beyond.
Foundational AI was the appetizer. Applications are the main course.
After a $110 billion year for AI-first startups in 2024—up 62% YoY and gobbling up a third of all global VC funding—it’s clear we’ve reached the “AI Everywhere” moment. But now the capital tide is turning.
According to a new report by Prosus and Dealroom, the next investment boom isn’t in the brains of AI (foundation models), but in the bodies—the tools doing actual work. Think sales agents, ecommerce operating systems, healthcare triage bots. VCs are waking up to what operators already know: it’s time to build, not just train.
“We believe we are close to an inversion—value and investments will skyrocket in the application layer,” says Prosus’ Global Head of AI, Euro Beinat.
The catch: foundational AI is a black hole for capital
LLMs are impressive, sure. But training them is capital suicide for all but the top five tech giants. The cost of compute, data, and talent stacks up fast. Even OpenAI is playing catch-up on monetization.
Foundational layers soaked up most of the money in 2024—but with unclear moats and delayed returns, even the savviest investors are questioning the math.
Meanwhile, application-layer startups are proving they can:
- Get to market fast
- Plug into existing enterprise and consumer workflows
- Deliver measurable ROI
It’s the difference between “cool demo” and “this saved me $100K last quarter.”
Where the smart money’s going: ecommerce and enterprise AI
Prosus has been on a buying spree in application-layer AI—and their portfolio shows where the puck is headed:
🛒 Qeen.ai – An AI-powered ecommerce OS that personalizes storefronts per user, delivering a 30% lift in add-to-cart rates.
📈 Advolve – Turns one marketer into an entire paid media team. Automatically generates and deploys ads to slash CAC and boost ROAS.
🤖 Ema – A universal AI employee that can be a sales assistant, data analyst, or support agent—whatever the org needs, without the HR overhead.
⚖️ SpotDraft – Legal contract automation that reduces admin bloat and closes deals faster.
🩺 Corti – AI triage and scribing for healthcare providers, trained on over 250,000 daily interactions.
These aren’t just shiny toys—they’re revenue-driving machines.
Operator POV: where AI actually delivers value
We don’t need another chat demo. Operators want tools that:
- Cut costs
- Shorten cycle times
- Grow sales without growing headcount
And that’s exactly what these applications do.
The old SaaS playbook—point solutions solving specific pain points—is being rewritten with AI as the engine. But here’s the key: distribution still eats tech for breakfast. If an AI app can hook into Shopify, Salesforce, or Slack, it wins.
Why this shift matters for ecommerce operators
This is your second-mover advantage moment.
Forget trying to train your own model or hire prompt engineers. The real edge comes from integrating these AI tools into your ops stack—before your competitors do.
Expect:
- Hyper-personalized customer journeys
- Autonomous ad campaign testing
- AI agents that handle 80% of support tickets
And it’s not just the big guys playing. Tools like Qeen and Advolve are designed for growth-stage brands trying to scale profitably.
So what?
The AI gold rush is moving from model builders to workflow hackers. That’s good news for ecommerce founders, marketers, and operators who just want to drive more revenue with fewer meetings.
If you’re not testing AI apps in your stack by mid-2025, you’re not behind the curve—you’re under it.
