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The Future of Business with Generative AI: Opportunities and Challenges

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Manage episode 399028752 series 3451197
Innhold levert av Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In this conversation, Krishnan Venkata, Chief Client Officer at LatentView Analytics, discusses the impact of generative AI on various industries and business functions. He highlights the importance of understanding the business problems that can be solved with generative AI and starting with small pilots to test its effectiveness. Krishnan also addresses misconceptions about generative AI and emphasizes the need for human expertise in complex problem-solving and customer interactions. He suggests that companies should integrate generative AI into their operations by identifying use cases and creating a roadmap for implementation.

Takeaways
Generative AI has the potential to drive growth and solve a wide range of business problems across industries and functions.

When creating decision trees with generative AI, it is important to start with unsupervised learning and continuously refine the model based on known outcomes and context.

There are misconceptions about generative AI being a magic solution that can solve all problems, but it should be seen as an additional layer of intelligence that complements human expertise.

Specialized agents and multi-model structures are emerging in the generative AI space, allowing for more targeted and effective communication with users.

Generative AI can be particularly impactful in targeting the long tail of customers, improving self-service experiences, and personalizing customer interactions.

While generative AI has its limitations, human expertise and understanding of context, sentiment, and complex relationships are still crucial in problem-solving and customer interactions.

Chapters

00:00
Introduction and Personal Updates

01:23
Introduction of Krishnan Venkata and Background

02:21
Generative AI and its Impact

05:20
Creating Decision Trees with Generative AI

08:53
Misconceptions about Generative AI

11:16
Specialized Agents and Multi-Model Structure

16:22
Significant Change with Generative AI in Different Industries

18:08
Targeting the Long Tail of Customers

21:03
AI in Self-Service and Personalized Customer Interactions

25:20
The Limitations of AI and the Importance of Human Expertise

28:08
Integrating Generative AI into Operations

30:31
Closing Remarks

  continue reading

42 episoder

Artwork
iconDel
 
Manage episode 399028752 series 3451197
Innhold levert av Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In this conversation, Krishnan Venkata, Chief Client Officer at LatentView Analytics, discusses the impact of generative AI on various industries and business functions. He highlights the importance of understanding the business problems that can be solved with generative AI and starting with small pilots to test its effectiveness. Krishnan also addresses misconceptions about generative AI and emphasizes the need for human expertise in complex problem-solving and customer interactions. He suggests that companies should integrate generative AI into their operations by identifying use cases and creating a roadmap for implementation.

Takeaways
Generative AI has the potential to drive growth and solve a wide range of business problems across industries and functions.

When creating decision trees with generative AI, it is important to start with unsupervised learning and continuously refine the model based on known outcomes and context.

There are misconceptions about generative AI being a magic solution that can solve all problems, but it should be seen as an additional layer of intelligence that complements human expertise.

Specialized agents and multi-model structures are emerging in the generative AI space, allowing for more targeted and effective communication with users.

Generative AI can be particularly impactful in targeting the long tail of customers, improving self-service experiences, and personalizing customer interactions.

While generative AI has its limitations, human expertise and understanding of context, sentiment, and complex relationships are still crucial in problem-solving and customer interactions.

Chapters

00:00
Introduction and Personal Updates

01:23
Introduction of Krishnan Venkata and Background

02:21
Generative AI and its Impact

05:20
Creating Decision Trees with Generative AI

08:53
Misconceptions about Generative AI

11:16
Specialized Agents and Multi-Model Structure

16:22
Significant Change with Generative AI in Different Industries

18:08
Targeting the Long Tail of Customers

21:03
AI in Self-Service and Personalized Customer Interactions

25:20
The Limitations of AI and the Importance of Human Expertise

28:08
Integrating Generative AI into Operations

30:31
Closing Remarks

  continue reading

42 episoder

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