One billboard, $3M a year: Welcome to AI’s advertising arms race ⁠64%

By Max Harrison-Caldwell⁠52%

8/3/2026, 6:00:00 AM

BS Summary: This article contains 24 faulty reasoning types, including Halo Effect, Post Hoc (False Cause), and Anecdotal, with Hasty Generalization as the most egregious example at 10.8% saturation with 66 hits. Analysis detected 723 faulty-reasoning hits from 611 analyzed words, generating a BS Score of 52% and a BS Rank of ⁠64% (9,725 of 26,881 articles). This article is worse (more manipulative) than 63.80% of the article peer group.

When 23-year-old Avi Schiffman spent $1 million to take over the New York City subway with ads for his AI wearable startup, Friend, it was national news. 
But some San Francisco companies are spending three times that much each year on a single billboard. 
The ads have become the physical manifestation of the AI boom, plastered across Muni buses, BART station walls, and the famously incomprehensible highway billboards on U.S. 
101. 
The cost of the biggest, most visible signs along the 101 has surged 20%-30% from pre-pandemic levels, according to Eric Perko, founder and CEO of the ad firm Apollo Partners. 
Nearly all of those billboards are leased by AI, tech, and finance companies paying a premium to put their names in front of the 100,000-plus people who cross the Bay Bridge into San Francisco each day. 
“The top end of the range would be $200,000 to $250,000 a month,” Perko said. 
That could work out to $3 million annually. 
The two major billboard companies, Outfront and Clear Channel, declined to discuss their pricing. 
That highest tier in the city’s billboard advertising is the biggest and most visible signage on the “skyway” — the section of highway that connects SFO and the Bay Bridge — which companies rent for years at a time. 
These are the huge, prime spots that allow for extended features beyond the typical billboard dimensions. 
This high-value real estate, easy to see from the freeway, is dominated by AI companies, including WorkOS (“Auth for agents”), Nebius (“AI inference at scale”), and Lambda (“That’s so agentic”). 
Perko said skyway billboards that are below that top tier but still desirable cost $50,000 or $100,000 per month, and smaller ones with less visibility rent for less. 
“It totally depends on the actual unit,” he said. 
Billboard prices dipped during COVID but have recovered and then some. 
The AI boom is a major driver, of course, but there’s also renewed enthusiasm for outdoor advertising across industries. 
That could be because people distrust or intentionally avoid ads on their phones. 
It could be related to advertisers focusing more on building brand recognition than on trying to convince existing customers to keep buying. 
It could be because advertisers are just looking for ways to distinguish themselves from competitors. 
What’s certain is that while the tens of thousands of motorists stuck in rush-hour traffic are getting a range of ads on social media, they’re all seeing the same billboards. 
“There are so many places people can put their money, but advertising in real life has been booming,” said Michael Parvin, sales director for Outfront. 
“People want to see their names in big, bright lights. 
It feels like they’ve landed.” 
Dan Berte, a product manager and billboard enthusiast, started tracking the ones on U.S. 101 in March on his website 101ads.org. 
He called the unavoidable freeway ads “a fantastic cultural artifact of the Bay Area” and said he imagines that visitors from all over the world bring tales of the cryptic copy back home. 
“I don’t know how much traction or value they bring in terms of a bottom line, but as a reputation tool, I think they’re pretty powerful,” Berte said. 
This is perhaps especially true for AI startups trying to make a name for themselves in a crowded industry. 
But not all of these startups will survive, which means demand for billboard space won’t stay at its current astronomical level. 
Until then, the freeway may still be the best place in San Francisco to look like you’ve already made it. 
“It certainly can’t last forever,” Perko said. 
“There are cycles for everything.” 
Article reasoning-pattern comparisonThis article: 6.2%Max Harrison-Caldwell: 1.5%The San Francisco Standard: 2.4%Confirmation Bias6.2%This article: 1.3%Max Harrison-Caldwell: 0.8%The San Francisco Standard: 1.0%Anchoring Bias1.3%This article: 8.0%Max Harrison-Caldwell: 2.7%The San Francisco Standard: 2.9%Availability Heuristic8.0%This article: 9.2%Max Harrison-Caldwell: 1.0%The San Francisco Standard: 1.0%Representativeness Heuristic9.2%This article: 0.8%Max Harrison-Caldwell: 0.6%The San Francisco Standard: 0.7%Hindsight Bias0.8%This article: 0.0%Max Harrison-Caldwell: 1.1%The San Francisco Standard: 1.2%Overconfidence Bias0.0%This article: 1.8%Max Harrison-Caldwell: 7.3%The San Francisco Standard: 5.3%Framing Effect1.8%This article: 0.0%Max Harrison-Caldwell: 0.3%The San Francisco Standard: 0.5%Loss Aversion0.0%This article: 5.1%Max Harrison-Caldwell: 0.3%The San Francisco Standard: 0.5%Status Quo Bias5.1%This article: 0.0%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.2%Sunk Cost Effect0.0%This article: 4.9%Max Harrison-Caldwell: 2.8%The San Francisco Standard: 2.2%Optimism Bias4.9%This article: 4.6%Max Harrison-Caldwell: 1.5%The San Francisco Standard: 1.2%Pessimism Bias4.6%This article: 0.0%Max Harrison-Caldwell: 3.4%The San Francisco Standard: 5.8%Negativity Bias0.0%This article: 4.6%Max Harrison-Caldwell: 1.1%The San Francisco Standard: 1.6%Self-Serving Bias4.6%This article: 3.6%Max Harrison-Caldwell: 0.7%The San Francisco Standard: 0.8%Fundamental Attribution Error3.6%This article: 2.5%Max Harrison-Caldwell: 0.4%The San Francisco Standard: 0.2%Actor-Observer Bias2.5%This article: 0.0%Max Harrison-Caldwell: 1.2%The San Francisco Standard: 0.7%In-Group Bias0.0%This article: 4.9%Max Harrison-Caldwell: 0.3%The San Francisco Standard: 0.2%Out-Group Homogeneity Bias4.9%This article: 10.3%Max Harrison-Caldwell: 3.3%The San Francisco Standard: 3.3%Halo Effect10.3%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.2%Horn Effect0.0%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Max Harrison-Caldwell: 0.8%The San Francisco Standard: 1.1%Recency Bias0.0%This article: 0.0%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.2%Primacy Effect0.0%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.1%Blind-Spot Bias0.0%This article: 0.0%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.4%Ad Hominem0.0%This article: 0.0%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.2%Straw Man0.0%This article: 4.6%Max Harrison-Caldwell: 2.7%The San Francisco Standard: 2.4%Appeal to Authority4.6%This article: 0.0%Max Harrison-Caldwell: 1.0%The San Francisco Standard: 1.1%False Dilemma0.0%This article: 3.4%Max Harrison-Caldwell: 0.4%The San Francisco Standard: 0.7%Slippery Slope3.4%This article: 0.0%Max Harrison-Caldwell: 0.2%The San Francisco Standard: 0.1%Circular Reasoning0.0%This article: 10.8%Max Harrison-Caldwell: 5.6%The San Francisco Standard: 4.1%Hasty Generalization10.8%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.2%Red Herring0.0%This article: 0.0%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.4%Bandwagon0.0%This article: 2.5%Max Harrison-Caldwell: 3.1%The San Francisco Standard: 3.5%Appeal to Emotion2.5%This article: 0.0%Max Harrison-Caldwell: 0.5%The San Francisco Standard: 0.4%Begging the Question0.0%This article: 10.0%Max Harrison-Caldwell: 2.8%The San Francisco Standard: 1.9%Post Hoc (False Cause)10.0%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.1%Tu Quoque0.0%This article: 2.3%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.3%Burden of Proof2.3%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.1%Appeal to Nature0.0%This article: 0.0%Max Harrison-Caldwell: 0.4%The San Francisco Standard: 0.1%Composition/Division0.0%This article: 9.8%Max Harrison-Caldwell: 3.7%The San Francisco Standard: 2.7%Anecdotal9.8%This article: 0.0%Max Harrison-Caldwell: 0.2%The San Francisco Standard: 0.1%No True Scotsman0.0%This article: 1.5%Max Harrison-Caldwell: 1.2%The San Francisco Standard: 1.1%Ambiguity (Equivocation)1.5%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.0%Gambler’s Fallacy0.0%This article: 0.8%Max Harrison-Caldwell: 0.1%The San Francisco Standard: 0.1%Middle Ground0.8%This article: 0.0%Max Harrison-Caldwell: 0.2%The San Francisco Standard: 0.0%Personal Incredulity0.0%This article: 0.0%Max Harrison-Caldwell: 0.0%The San Francisco Standard: 0.1%Special Pleading0.0%This article: 0.0%Max Harrison-Caldwell: 0.2%The San Francisco Standard: 0.1%Genetic Fallacy0.0%This article: 0.0%Max Harrison-Caldwell: 1.1%The San Francisco Standard: 1.0%Unattributed Quote0.0%This article: 0.0%Max Harrison-Caldwell: 1.1%The San Francisco Standard: 0.7%Quote-first Misdirection0.0%This article: 0.0%Max Harrison-Caldwell: 5.2%The San Francisco Standard: 4.8%Biased Writer Voice0.0%This article: 0.0%Max Harrison-Caldwell: 0.7%The San Francisco Standard: 1.0%Indoctrination0.0%This article: 0.0%Max Harrison-Caldwell: 0.4%The San Francisco Standard: 0.2%Politically Left Leaning Bias0.0%This article: 0.0%Max Harrison-Caldwell: 0.2%The San Francisco Standard: 0.2%Politically Right Leaning Bias0.0%This article: 4.9%Max Harrison-Caldwell: 1.1%The San Francisco Standard: 2.1%Attempt to Sell a Product or S…4.9%

611 words analyzed.

Speakers

3speakers35%attributed speech395writer words
Selected voice

Dan Berte

74%flagged-word coverage
82 attributed words38% of attributed speech86% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.