AI’s Next Chapter: Why Escape Velocity Will Be Defined by AI-Native Companies

Two of Wall Street’s most influential research houses just weighed in on AI’s trajectory — and the numbers are staggering. Morgan Stanley projects that AI adoption could generate $920 billion in annual net benefits for the S&P 500, translating into $13–16 trillion of long-term market value creation. Goldman Sachs highlights how AI-exposed equities have already rallied 42% off their April lows, even as investors debate whether valuations are getting ahead of fundamentals.

This isn’t hype. It’s a structural shift — one that validates what we’ve been building Banyan around from day one: AI-Native is not an add-on. It’s the foundation.

Wall Street’s Framing: Phases of the AI Trade

Goldman Sachs describes the AI market in four phases:

1. Phase 1: Nvidia — The chip provider defining the category.
2. Phase 2: Infrastructure build-out — Hyperscalers, power, cooling, and chips.
3. Phase 3: AI-enabled revenues — Software firms capturing new workflows.
4. Phase 4: Productivity — AI adoption embedded across the economy.

Today, Phase 2 stocks tied to hyperscaler capex are still dominating. But as Goldman notes, the eventual slowdown in hyperscaler capex will be a key inflection point. That’s where Phase 3 and 4 companies — the true AI-Native application and infrastructure startups — come into play.

The Productivity Shock Ahead

Morgan Stanley’s research makes one thing clear: the productivity wave is only just beginning. They estimate that 90% of occupations will be impacted by AI automation and augmentation, reshaping labor markets across every sector. The upside isn’t just cost cutting — it’s unlocking new revenue and margin expansion by freeing humans to focus on higher-value work.

In their base case, Healthcare, Transportation, and Consumer Staples Distribution see the highest economic lift. But this isn’t limited to incumbents. It’s the perfect entry point for AI-Native startups that were built to serve these industries from inception.

The Banyan Thesis: Why AI-Native Wins

At Banyan, our thesis is simple:

• AI-Native Infrastructure: Companies that provide the compute, chips, cooling, GPU clouds, and frameworks to make AI adoption possible. These are the picks-and-shovels enabling trillions in market cap creation.
• AI-Native Vertical SaaS: Purpose-built software designed with AI at its core, not bolted on. These companies will dominate in regulated, high-margin verticals like Healthcare, Finance, Manufacturing, and Logistics — where incumbents are slow, but the stakes are massive.

Non-AI-native companies will struggle to retrofit legacy stacks. Investors chasing incumbents adding “AI features” are underestimating the structural disadvantage. As the Morgan Stanley numbers show, the prize is measured in trillions. The winners will be those with escape-velocity adoption curves, not incremental gains.

What This Means for Investors

Both Morgan Stanley and Goldman Sachs reinforce the urgency. The capital cycle won’t wait — hyperscaler build-outs are front-loaded, adoption is non-linear, and the value creation window is now.

For LPs and founders, this means:

• The infrastructure wave is investable, but crowded.
• The real asymmetric upside lies in AI-Native startups that are positioned to dominate Phase 3 and Phase 4.
• The escape velocity dynamic (going from zero to $10M+ ARR in 12–18 months) will define who emerges as category leaders.

Closing Thought

History doesn’t repeat, but it rhymes. Electrification, the web, mobile — all produced trillion-dollar outcomes. Morgan Stanley now pegs AI’s potential at 24–29% of the entire S&P 500 market cap.

At Banyan, we believe this will not be captured by incumbents retrofitting “AI features.” It will be built by founders who are AI-Native from day one. And that’s exactly where we’re investing.