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Solomon Kahn on Artificial Intelligence in the Workplace: Opportunities and Caution

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Manage episode 390427362 series 2951346
Inhalt bereitgestellt von Ametros. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Ametros oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Let us know how you're enjoying the show or ideas for any future topics!

Ever wondered how artificial intelligence is reshaping the landscape of workplaces everywhere? In this episode we’re taking a deep dive into Artificial Intelligence (AI) in the workplace with Solomon Kahn, a data science expert, Founder and CEO of Delivery Layer, and the captivating host of "The Data That Drives Revenue" podcast.

In this episode, we explore the unique challenges faced by the insurance industry, often slow to adapt to new technological advances. Solomon sheds light on how AI can break through these barriers, offering a roadmap for streamlining processes and changing the landscape of workers' compensation. From scaling opportunities in the workplace to managing the delicate balance between innovation and risk, we explore the profound impact of AI on the modern workplace.
This episode is for anyone interested in learning the basics of AI predictive language models, how these models can be used to enhance work processes, and the transformative potential of AI in revolutionizing workers' compensation.

Learn More About Solomon Kahn

Ametros is changing the way injured individuals navigate healthcare by providing them with post-settlement medical management tools for their settlement funds. Ametros helps drive more simplified, secured, and supported settlements and saves money by working closely with injured workers, insurers, employers, attorneys, and Medicare to create a seamless experience.
Learn how Ametros can support you.

  continue reading

34 Episoden

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iconTeilen
 
Manage episode 390427362 series 2951346
Inhalt bereitgestellt von Ametros. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Ametros oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Let us know how you're enjoying the show or ideas for any future topics!

Ever wondered how artificial intelligence is reshaping the landscape of workplaces everywhere? In this episode we’re taking a deep dive into Artificial Intelligence (AI) in the workplace with Solomon Kahn, a data science expert, Founder and CEO of Delivery Layer, and the captivating host of "The Data That Drives Revenue" podcast.

In this episode, we explore the unique challenges faced by the insurance industry, often slow to adapt to new technological advances. Solomon sheds light on how AI can break through these barriers, offering a roadmap for streamlining processes and changing the landscape of workers' compensation. From scaling opportunities in the workplace to managing the delicate balance between innovation and risk, we explore the profound impact of AI on the modern workplace.
This episode is for anyone interested in learning the basics of AI predictive language models, how these models can be used to enhance work processes, and the transformative potential of AI in revolutionizing workers' compensation.

Learn More About Solomon Kahn

Ametros is changing the way injured individuals navigate healthcare by providing them with post-settlement medical management tools for their settlement funds. Ametros helps drive more simplified, secured, and supported settlements and saves money by working closely with injured workers, insurers, employers, attorneys, and Medicare to create a seamless experience.
Learn how Ametros can support you.

  continue reading

34 Episoden

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