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The U.S. spent $30 billion to ditch textbooks for laptops and tablets: The result is the first generation less cognitively capable than their parents

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AITerm Sheet

Exclusive: The next wave of AI drive-thrus is here—and a16z and Arc think it finally works

Lily Mae Lazarus
By
Lily Mae Lazarus
Lily Mae Lazarus
Reporter, News
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Lily Mae Lazarus
By
Lily Mae Lazarus
Lily Mae Lazarus
Reporter, News
Down Arrow Button Icon
May 26, 2026, 6:27 AM ET
Ali Hussain (left) and Mike MacLennan (right) smile
Arc claims it gets orders right more than 95% of the time on its own, and that restaurants see a 4% to 5% bump in the average customer's bill.Courtesy of Arc
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Mike MacLennan’s idea of market research as the CEO of a drive-thru AI company is loitering at Burger King. His company’s first dollar was actually given to him by a group of elderly women who believed he was panhandling at the fast food joint. 

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His company, Arc, is a voice AI startup that takes orders and optimizes business performance at drive-thrus. MacLennan and co-founder Ali Hussain—both Square and Cash App veterans, where they built payment infrastructure—have raised $10.76 million seed funding, Fortune learned exclusively. Andreessen Horowitz led the round. The company is already working with two major fast-food chains, each with hundreds of locations.

Arc’s market is enormous. There are roughly 200,000 drive-thru locations in the U.S., with drive-thrus accounting for approximately 70 to 75% of quick-service restaurant (QSR) revenue. The AI-in-QSR market is projected to reach $12 billion by 2034. But the space is rife with failed concepts. McDonald’s killed its AI drive-thru pilot in 2024 after it couldn’t perform at scale. Presto Automation received an SEC fraud charge for misleading investors about its AI autonomy claims. And Taco Bell is rethinking a 500-plus location rollout after customer complaints went viral (including a prank order for 18,000 cups of water).

Arc’s argument is that the previous wave failed for a specific, fixable reason: the players were using “80% good models trying to take out labor,” MacLennan told me. “Chapter two—which I think is just starting now—is 99% good models focused on wins for customers, wins for employees, and wins for businesses.”

Arc trains brand-specific models on thousands of real drive-thru interactions (including specific accent and dialect exposure). Then, it runs A/B testing where operators can compare model variants in real-time, measuring accuracy, average order value, and order speed simultaneously. When one Arc customer wanted to test the success of an impromptu milkshake upsell at the end of an order, Arc ran it live. It only converted at 5% to 6%. Successful upsells typically run at between 20% to 40%. “We let the data do the talking,” MacLennan said. “He had 20 years of experience and was going the wrong direction on that one.”

Olivia Moore, the partner at a16z who led the round and has arguably spent more time studying voice AI than most, says the conviction here is the team. “This is by far the hardest kind of environmental setup,” she said. “The car has to drive over a sensor, trigger the voice agent, then the voice agent needs to run with screaming kids in the background, with people changing their mind in the middle of the order.” In early diligence, she went to MacLennan’s garage, where he’d built a replica drive-thru environment for testing. “It really gave me an appreciation for the difficulty here,” she said. 

Arc claims it gets orders right more than 95% of the time on its own (a 5% to 10% accuracy improvement), and that restaurants see a 4% to 5% bump in the average customer’s bill thanks to smarter upselling. Those numbers are verified two ways: did the AI finish the order without any human help, and did the food prepared actually match what the customer asked for.

MacLennan is clear-eyed that the voice part is almost beside the point. “Voice AI is a cool technology that’s an enabler of the data and the observability, the measurability, the testing,” he told me. “It lets you take this huge piece of the economy that was operating in a bit of a black box and bring the same precision you get with highly-tuned digital channels.” 

And in a business where net margins routinely run below 5%, that intelligence, and every extra milkshake sold, adds up fast. 

See you tomorrow,

Lily Mae Lazarus
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@LilyMaeLazarus
Email: lily.lazarus@fortune.com
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About the Author
Lily Mae Lazarus
By Lily Mae LazarusReporter, News

Lily Mae Lazarus is a news reporter at Fortune.

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