When Ramp’s Economist, Ara Kharazian, jumped into r/Ramp for a live AMA, the conversation quickly focused on some of the biggest questions in AI and business today: Are we in an AI bubble? Where is ROI emerging for the historic spending spree on AI? How are companies reshaping their budgets in response to the rise of new AI tools?

Drawing on Ramp’s business spending data from 50,000-plus businesses, Ara broke down what’s happening inside companies and what those patterns signal about ongoing AI adoption.

Here are six of the biggest insights:

1. Ramp’s data advantage: tech-forward, not just tech

Ara dug into what makes Ramp’s spend dataset unique — and why its “bias” is actually a feature, not a bug.

Ramp’s data tends to reflect early adopters. These are companies that switch tools faster, experiment more, and adopt AI sooner. That makes it a powerful window into where the economy may be heading, not just where it is today.

2. AI budgets are no longer seen as just ‘experimental’

CFOs aren’t treating AI as a side experiment anymore. They’re writing (sizable) checks.

Budgets have expanded dramatically. As Ara mentioned, only a few years ago most companies wouldn't even consider AI contracts above $30–40K. Now mid-market and enterprise teams are regularly approving deals in the six-figure range. That change suggests that:

1. AI products are materially better than they were just a few years ago, and
2. Finance leaders now see these tools as meaningful contributors to performance, not speculative bets.

3. The clearest ROI so far: Software engineering and customer support

A lot of AI discourse is driven by vibes. Ara’s answers pointed to two domains where value is showing up in the data: software engineering and customer support.

Early AI value is concentrated where work is digital, repetitive, and measurable. That makes engineering and customer service work a strong fit for AI. Those categories are beginning to show double-digit percentage improvements in ROI for some businesses, Ara noted.

4. How to measure if AI is working

Instead of staring at GDP or productivity charts, Ara focuses on firm-level behavior and contract patterns.

The signal isn’t in national productivity stats yet but rather in renewals, bigger contracts, and fewer “pilot forever” projects. If companies increase contract size and length, AI is likely making a real difference for these businesses.

5. AI is booming in spend … but productivity stats will lag

AI spend is clearly accelerating, but it’s still early to see that show up in macro data from the government.

We’re in the investment and learning phase: AI spend is up and very real, but it will likely take years before the full impact shows up in GDP and official productivity measures.

6. What Ramp data says about the broader economy

Ara referenced historical patterns and Ramp spend data to answer broader macro questions, from recession risk to interest-rate sensitivity.

On recession risk and unemployment:

On interest rates and spend:

Digital ad spend is emerging as one of the fastest indicators of changing business sentiment. The category tends to adjust quickly to interest rate movements — for instance, companies often scale back digital ad budgets as soon as the Fed raises rates.