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AI for America's Small Businesses | Lassie

Business
United States
Commencé July 31, 2026

Alex Rampell and Olivia Moore speak with Lassie cofounders Steijn Pelle and Frédéric Renken about bringing AI to one of the most overlooked parts of the economy: small businesses. Inspired by time spent working inside dental practices, Pelle and Renken set out to automate the administrative work that keeps healthcare providers away from patients. They discuss how AI agents are changing billing, insurance claims, patient payments, and other operational workflows, allowing practices to spend le...

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CLAIM Publié par admin • Jul 31, 2026
Investment in AI technology is essential for the long-term sustainability of small businesses in a competitive market.

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CLAIM Publié par admin • Jul 31, 2026
AI may lead to job displacement in small businesses, particularly in administrative roles.

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CLAIM Publié par admin • Jul 31, 2026
Not all small businesses have the infrastructure or expertise to effectively implement AI solutions.

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CLAIM Publié par admin • Jul 31, 2026
Small businesses should be encouraged to adopt AI tools to improve operational efficiency and customer experience.

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CLAIM Publié par admin • Jul 31, 2026
Collaboration between small businesses and AI developers can foster innovation and lead to tailored solutions.

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CLAIM Publié par admin • Jul 31, 2026
AI should be integrated into small business operations in a way that prioritizes human oversight and decision-making.

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CLAIM Publié par admin • Jul 31, 2026
The use of AI in small businesses raises concerns about data privacy and security for sensitive customer information.

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CLAIM Publié par admin • Jul 31, 2026
AI solutions can democratize access to advanced technology for small businesses that traditionally lack resources.

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CLAIM Publié par admin • Jul 31, 2026
The success of AI in small businesses hinges on proper training and support for employees to adapt to new technologies.

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CLAIM Publié par admin • Jul 31, 2026
The benefits of AI for small businesses must be weighed against potential ethical implications and biases in algorithms.

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