The Two Biggest Stories of the Year: AI & Tariffs
Audio Brief
Show transcript
This episode examines business spending on AI and other economic trends using real-time transaction data from finance automation company, Ramp.
There are three key takeaways from this conversation. First, prioritize real-time spending data over traditional surveys for accurate trend analysis, especially for rapidly evolving areas like AI adoption. Second, assess the true viability of the AI boom by tracking business retention and growth in spending on AI products. Third, recognize the significant lag between major policy announcements, such as tariffs, and their actual economic impact.
Real-time transaction data from companies like Ramp offers a more accurate, timely picture of business behavior than traditional government surveys. Surveys often suffer from methodological flaws and outdated questioning. Ramp's data shows AI adoption around 45% among businesses, a stark contrast to government estimates of 9%. Technology and finance sectors are leading this adoption, with OpenAI emerging as the dominant foundational AI model provider.
The current AI cycle differs from past tech bubbles due to high business retention rates and increasing spending on AI products. This indicates companies are deriving tangible value and productivity gains. Such patterns suggest a more sustainable economic impact rather than speculative hype.
Policy announcements, particularly tariffs, often create headlines but have a much slower, more gradual real-world impact than anticipated. Legal frictions, existing trade agreements, and operational delays at ports mean the true incidence of tariffs on invoices remains low for an extended period after initial announcements. The full economic effect typically filters through over time, not immediately.
This discussion underscores the value of real-world spending data for understanding complex economic shifts and business dynamics.
Episode Overview
- Guest Ara Kharazian from Ramp, a finance automation company, shares unique insights into business spending on AI and other trends based on real-time transaction data.
- The discussion highlights a massive discrepancy between Ramp's data on AI adoption (around 45%) and lagging government surveys (around 9%), questioning how we measure technological shifts.
- They analyze AI adoption trends across different business sectors and sizes, revealing that technology and finance companies are leading the charge, with OpenAI being the dominant model provider.
- The conversation also explores the slower-than-expected economic impact of tariffs and data suggesting a rise in the intense "996" work culture in tech hubs like San Francisco.
Key Concepts
- Ramp AI Index: A tool developed by Ramp that tracks the real-world adoption of AI by businesses, based on actual spending data from corporate cards and invoices.
- Data Discrepancy: A significant gap exists between real-time spending data and traditional government survey data on AI adoption, largely due to differences in methodology, timeliness, and the framing of questions.
- AI Adoption Trends: Technology and finance sectors are leading AI adoption, with large businesses adopting faster than small and medium-sized ones. In the foundational AI model space, OpenAI is the dominant market leader, followed by Anthropic.
- Economic Impact of AI: Unlike the dot-com bubble, current AI companies are generating substantial revenue, and businesses are showing high retention rates for AI products, indicating they are deriving real value and productivity gains.
- Tariff Enforcement vs. Announcement: The real-world impact of announced tariffs is much slower and more gradual than headlines suggest, due to legal frictions, existing trade agreements, and operational delays at ports. The incidence of tariffs on invoices remains low.
- 996 Work Culture: Data on corporate card spending for food delivery and takeout on Saturdays suggests a rise in weekend work among employees at San Francisco-based businesses, reflecting a more intense work culture.
Quotes
- At 03:00 - "You say, 'Well, actually, if you really want to know what's going on, the best indicator to look at is how much businesses are spending.'" - Michael Batnick highlighting the value of using real transaction data to understand AI adoption.
- At 06:58 - "The government estimate of AI adoption for US businesses, I do think has one significant flaw. First of all, it's based on a survey...and the question was written a couple of years ago." - Ara Kharazian explaining the massive discrepancy between Ramp's data and official government statistics on AI adoption.
- At 20:33 - "The optimistic view there is that this is going to change the world... And it's also true that in between now and then, there can be a lot of people displaced and there can be a lot of societal change for the worse." - Michael Batnick summarizing the dual nature of technological revolutions like AI.
- At 23:26 - "I read your post and I kind of hit myself in the head like, 'Oh, duh, of course.' And your point is that, listen, all of the announcements and what people are saying, that's not actually what the businesses or consumers are paying just yet. It still hasn't filtered through." - Ben Carlson reacting to the insight that tariff announcements don't immediately translate into real economic impact.
- At 29:51 - "If those retention rates were going to start to decline, that tells us that the products that are making it to the market are not reaching customers in an effective way... they're not showing them value." - Ara Kharazian explaining that high retention for AI products is a key indicator that companies are finding real value, differentiating this cycle from past tech bubbles.
Takeaways
- Prioritize spending data over surveys for trend analysis. When evaluating economic trends like technology adoption, focus on real-time transaction data, as it provides a more accurate and timely picture of business behavior than traditional surveys which can be slow and misleading.
- Assess the AI boom by tracking business retention and contract size. The long-term viability of the AI trend can be gauged by whether businesses continue to pay for and increase their spending on AI products, which signals they are receiving tangible productivity benefits.
- Recognize the lag between policy announcements and economic impact. Be cautious of reacting to headline policy announcements, such as tariffs. Their actual implementation and effect on business costs and consumer prices are often delayed and more gradual due to logistical and legal complexities.
