Enterprise LLMs and AI in Customer Support: A Conversation with Raghu Ravinutala of Yellow.ai

2023-09-06 15:12:22
关注

Illustration: © IoT For All

The AI For All Podcast returns with another captivating episode featuring Raghu Ravinutala, the CEO and co-founder of Yellow.ai, a global leader in Conversational AI. Hosts Ryan Chacon and Neil Sahota engage with Raghu in a comprehensive conversation about the emerging trends in enterprise LLMs and AI’s pivotal role in customer support.

From Chatbots to Intelligent Agents

Raghu kicks off the episode by tracing the evolution of AI chatbots, explaining how they have morphed into highly specialized intelligent agents capable of complex interactions. He paints a vivid picture of how these advancements have revolutionized customer service in multiple sectors.

AI and Job Dynamics

A pertinent issue that often surfaces in AI discussions is its impact on employment. Raghu dives into this topic, assuring listeners that while AI may automate some repetitive tasks, it simultaneously generates new roles requiring a unique skill set, essentially creating a shift rather than a loss in the job market.

Keeping AI Systems Up-To-Date

Discussing the technical aspects of AI in customer support, the conversation moves to the necessity of updating AI systems. Unlike a website or application that can be static, AI will always need to be updated with the latest company data.

Cost Analysis of AI Customer Support

An intriguing segment of the discussion focuses on the economics of integrating AI into customer support. Raghu elaborates on how AI can be both a cost-saver and a revenue-generator, significantly impacting an enterprise’s bottom line.

Industries at the Forefront

Raghu identifies industries that are leading the charge in employing AI for customer support. From financial services to retail, he provides real-world examples of sectors that have successfully embraced this technology.

The Era of Specialized LLMs

The future, according to Raghu, is filled with specialized LLMs capable of ultra-specific functions. These LLMs will not only engage in routine customer support but will also assist in intricate processes requiring a deeper understanding of the subject matter.

Gleaning Customer Insights Through AI

Another salient point raised in the episode is the use of AI for gathering actionable customer insights. Raghu explains how data analytics coupled with AI can provide enterprises with a wealth of information about customer preferences and behaviors. He provides an example of how a PCG company was able to personalize their marketing on a regional basis using insights from their customer support AI.

Advice for Enterprises

For organizations contemplating the leap into AI, it’s a choice between building your own AI and infrastructure or utilizing an outside vendor or third party. Raghu recommends that companies that are not primarily tech companies take advantage of the excellent tools and services that already exist.

Watch the Episode

This episode is an invaluable resource for business leaders, customer support executives, and anyone interested in the interplay between AI and customer experience (CX). With Raghu Ravinutala’s deep expertise and insights, the episode serves as a guide to navigating the evolving landscape of AI in enterprise settings.


Tweet

Share

Share

Email

  • Artificial Intelligence
  • Finance
  • Process Automation
  • Retail

  • Artificial Intelligence
  • Finance
  • Process Automation
  • Retail

参考译文
企业大语言模型与人工智能在客户支持中的应用:与Yellow.ai的Raghu Ravinutala对话
图示:© IoT For All --> 《适用于所有人的AI播客》携另一期引人入胜的节目回归,本期嘉宾是Raghu Ravinutala,他是Yellow.ai的首席执行官兼联合创始人,Yellow.ai是对话式AI领域的全球领先企业。主持人Ryan Chacon和Neil Sahota与Raghu展开了一次深入的对话,探讨企业大语言模型的新兴趋势,以及AI在客户支持中的关键作用。从聊天机器人到智能代理 Raghu从追溯AI聊天机器人的演变开始本期节目,解释它们如何发展成功能高度专业化、能够进行复杂互动的智能代理。他生动地描绘了这些技术进步如何在多个行业彻底改变了客户服务。AI与就业动态 在AI讨论中,一个常见的话题是其对就业的影响。Raghu深入探讨了这一点,并向听众保证,虽然AI可能会自动化一些重复任务,但它同时也创造了许多需要独特技能的新岗位,本质上是在工作市场上带来了岗位的转移,而非岗位的流失。保持AI系统的更新 讨论AI在客户服务中的技术方面时,对话转向了更新AI系统的重要性。与网站或应用可以保持静态不同,AI系统始终需要利用最新的公司数据进行更新。AI客户服务的成本分析 讨论的另一个引人关注的环节聚焦于将AI整合进客户服务中的经济学问题。Raghu详细说明了AI如何在节省成本的同时也能够创造收入,从而显著影响企业的利润。走在前列的行业 Raghu指出了一些在使用AI进行客户服务方面走在前列的行业。从金融服务到零售业,他提供了成功采用该技术的现实案例。专门化大语言模型的时代 根据Raghu的预测,未来将出现能够执行超特定功能的专业化大语言模型。这些模型不仅能够处理常规客户服务,还能够协助处理需要对主题有深入理解的复杂流程。通过AI获取客户洞察 该节目还提到的另一个重要观点是使用AI来收集可操作的客户洞察。Raghu解释了数据分析与AI结合如何为公司提供关于客户偏好和行为的大量信息。他还举了一个PCG公司如何利用其客户服务AI的洞察来实现区域化营销个性化的事例。对企业的建议 对于正在考虑迈入AI领域的企业而言,他们面临的选择是在内部构建自己的AI和基础设施,还是使用外部供应商或第三方。Raghu建议那些并非主要以技术为核心的企业,应该善用已经存在的一流工具和服务。观看该期节目 本期节目是商业领袖、客户服务主管以及任何对AI与客户体验(CX)之间关系感兴趣的人的宝贵资源。凭借Raghu Ravinutala深厚的专长与洞察,本期节目为在企业环境中导航日益演变的AI格局提供了指南。推文分享分享邮件 人工智能金融流程自动化零售 --> 人工智能金融流程自动化零售
您觉得本篇内容如何
评分

评论

您需要登录才可以回复|注册

提交评论

广告

iotforall

这家伙很懒,什么描述也没留下

关注

点击进入下一篇

Twitter改名X的10天,混乱一箩筐

提取码
复制提取码
点击跳转至百度网盘