# Enterprise AI use can grow far beyond coding

Markdown copy of https://realalpha.app/s/enterprise-ai-use-can-grow-far-beyond-coding/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Aidan Gomez](https://realalpha.app/builders/aidan-gomez/) · Aidan Gomez is a Cohere co-founder and Transformer co-author. · Co-founded Cohere, the sovereign AI company, and co-authored the Transformer paper, Attention Is All You Need.
- Host: Eric Newcomer
- Show: Newcomer Pod
- Episode: [Aidan Gomez Unfiltered on AGI, China & AI's Biggest Risk](https://realalpha.app/v/GfBEBfbW6YE/), Jun 26, 2026
- Moment: 3:18 to 6:11 of the episode (3 min), playing on https://realalpha.app/s/enterprise-ai-use-can-grow-far-beyond-coding/; the episode from there: https://realalpha.app/v/GfBEBfbW6YE/?t=198

## Quote

> “And so there's probably **another 10 or 100x** in terms of token consumption just on the enterprise side.”
> — [Aidan Gomez](https://realalpha.app/builders/aidan-gomez/) at [5:24](https://realalpha.app/v/GfBEBfbW6YE/?t=324) · Newcomer Pod

## Takeaways

1. Lower model costs can unlock many more applications.
2. Enterprise token use could grow 10 to 100 times.
3. Finance has opportunities in decisions, coordination and compliance.

## About this segment

Aidan Gomez expects spending to correct after companies let AI usage run unchecked, then rebound as model costs fall. He sees most enterprise work beyond coding as largely untouched.

From “Aidan Gomez Unfiltered on AGI, China & AI's Biggest Risk”, Jun 26, 2026. [Watch the full episode](https://realalpha.app/v/GfBEBfbW6YE/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[3:21](https://realalpha.app/v/GfBEBfbW6YE/?t=201) So token maxing has become the buzzword of the moment, but it reflects a real issue, which is companies wanted to incentivize their employees to use AI and get the most out of it. So they said, run wild, we'll have leaderboards, we'll track how much you're spending. Now, you know, I think we've seen people like Uber and some other companies say, oh, maybe we should track what's going on because we're going to blow through our budgets pretty quickly.

[3:46](https://realalpha.app/v/GfBEBfbW6YE/?t=226) You know, you work with a bunch of enterprises. What's your read on is, you know, are the inside tech companies ahead of this trend? And there are lots of old guard companies that still need to have the token maxing fail. before they pull back, or where are we in the arc of sort of spending for spending's sake on using AI? Well, I think a lot of that exuberance came out of coding and those models.

[4:12](https://realalpha.app/v/GfBEBfbW6YE/?t=252) You see this typically in like technology cycles. There's a exuberant adoption phase where the CFO or the CEO tells the CFO, no spend caps, like just adopt, adopt, adopt, and it goes into excess. and then there's a correction period. And that comes from the enterprise itself constraining spend, but then also from innovation and compression and efficiency within the modeling companies. So I think we just did this big ramp up to a much larger tier of model.

[4:41](https://realalpha.app/v/GfBEBfbW6YE/?t=281) You'll now see one of these cycles of compressing back down. So costs will fall dramatically. Is that going to hurt your revenue? I mean, if their customers pull back, there's enough growth elsewhere? No, yeah. Yeah, like the usage growth, as the costs come down, it will just unlock way more applications. We're still so early in enterprise adoption of AI. Yes, coding has taken off, and that might be hitting some sort of saturation point.

[5:11](https://realalpha.app/v/GfBEBfbW6YE/?t=311) But everything else within the enterprise is, from my perspective, still essentially untouched. Like the stuff that we're doing is so simple. There's so much, there's like an iceberg, you know, underneath the surface to go do. And so there's probably another 10 or 100x in terms of token consumption just on the enterprise side. After coding, what's two and three or what are the next buckets? Big applications.

[5:38](https://realalpha.app/v/GfBEBfbW6YE/?t=338) It really depends on the industry. Like that's, it's specific to the industry. So in finance, you'll see much more automated decision-making, communication, coordination between the different business units, automation of regulatory and compliance. There's so much work that gets done inside these organizations beyond just writing software. Actually, the overwhelming bulk of what's done is not writing software inside these legacy organizations.

[6:07](https://realalpha.app/v/GfBEBfbW6YE/?t=367) And all of that is going to be done by machines.