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Walter Thompson에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Walter Thompson 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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SnapLogic CTO Jeremiah Stone on overcoming AI adoption barriers

29:43
 
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Manage episode 431255431 series 3533520
Walter Thompson에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Walter Thompson 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Everyone's looking for ways to implement AI solutions, but integrating them into existing systems means entering uncharted territory.

Despite the hype cycle, a majority of enterprise customers “are spending 70-80% of their capacity maintaining legacy application infrastructure,” said Jeremiah Stone, CTO of SnapLogic.

As a result, these companies often lack the necessary talent to effectively assess or integrate AI, making compliance and security the two biggest challenges for AI-first founders.

To overcome these and other adoption barriers, early-stage CEOs need to become educators and great listeners before they can ever act as salespeople.

In this episode, I interviewed Jeremiah to learn more about identifying and overcoming barriers to AI adoption, strategies for effective customer engagement and the importance of transparency and iterative experimentation in AI development.

Episode summary
  • Security and compliance “are the two things that are challenging for adoption right now.”
  • Before selling AI solutions, founders need to listen to (and educate) potential customers.
  • “Enterprises are spending 70-80% of their capacity maintaining legacy application infrastructure.”
  • The risk of data breaches and bad customer outcomes makes enterprises cautious.
  • Focus on solving unique problems AI can address better than existing solutions.
  • Build trust by starting discussions with security, compliance, and risk frameworks.
  • Innovate openly to demystify AI for customers.
  • Make sure your team is ready to answer typical security and compliance questions.
  • Maintain discipline in focusing on scalable solutions rather than niche problems.
  • “You have to create your own talent and upskill your data engineering team.”
  • “Experiment weekly on the things that look promising and treat it as an iterative process.”
  • Be transparent and involve customers early in your development process.
Links

Thanks for listening!

-- Walter.

  continue reading

27 에피소드

Artwork
icon공유
 
Manage episode 431255431 series 3533520
Walter Thompson에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Walter Thompson 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Everyone's looking for ways to implement AI solutions, but integrating them into existing systems means entering uncharted territory.

Despite the hype cycle, a majority of enterprise customers “are spending 70-80% of their capacity maintaining legacy application infrastructure,” said Jeremiah Stone, CTO of SnapLogic.

As a result, these companies often lack the necessary talent to effectively assess or integrate AI, making compliance and security the two biggest challenges for AI-first founders.

To overcome these and other adoption barriers, early-stage CEOs need to become educators and great listeners before they can ever act as salespeople.

In this episode, I interviewed Jeremiah to learn more about identifying and overcoming barriers to AI adoption, strategies for effective customer engagement and the importance of transparency and iterative experimentation in AI development.

Episode summary
  • Security and compliance “are the two things that are challenging for adoption right now.”
  • Before selling AI solutions, founders need to listen to (and educate) potential customers.
  • “Enterprises are spending 70-80% of their capacity maintaining legacy application infrastructure.”
  • The risk of data breaches and bad customer outcomes makes enterprises cautious.
  • Focus on solving unique problems AI can address better than existing solutions.
  • Build trust by starting discussions with security, compliance, and risk frameworks.
  • Innovate openly to demystify AI for customers.
  • Make sure your team is ready to answer typical security and compliance questions.
  • Maintain discipline in focusing on scalable solutions rather than niche problems.
  • “You have to create your own talent and upskill your data engineering team.”
  • “Experiment weekly on the things that look promising and treat it as an iterative process.”
  • Be transparent and involve customers early in your development process.
Links

Thanks for listening!

-- Walter.

  continue reading

27 에피소드

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