AI and Machine Learning in Action: Jing Huang, Senior Director of Engineering at Momentive, Shares Insights in Interview

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Momentive’s Senior Director of Engineering and Machine Learning, Jing Huang, recently spoke with AiThority about the role of AI and machine learning in customer experience (CX). According to Huang, AI-powered technologies such as Automated Insights and SurveyMonkey Genius help businesses collect cost-efficient responses from targeted audiences to uncover relevant insights more quickly than ever before. This speed-to-delivery is imperative, and Momentive’s unique ability to balance technology with human experiences drives greater value for their customers.

While AI can greatly impact CX, Huang cautions that it cannot replace human interactions. Instead, businesses must be thoughtful about their approach to incorporating AI into the customer experience flow. The key to successful implementation is an open approach to customer feedback, as well as extensive training and education for employees at every level of the organization. Additionally, companies must remain mindful of AI ethics and ensure an ethical and inclusive approach to data collection.

AI and machine learning can also be used to build feedback options directly into a website or chatbot, or by generating automatic emails after specific customer touchpoints. Huang envisions a future where concepts such as AI copilots and AI assistants gain popularity, and AI buddies appear frequently in daily workflows.

Overall, AI and machine learning play a crucial role in helping businesses harness insights from millions of respondents and delivering a better overall customer experience. By capturing and understanding sentiments, AI can surface valuable information and identify the right focal points so businesses don’t get lost in the vast ocean of digital data.

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Frequently Asked Questions (FAQs) Related to the Above News

What is the role of AI and machine learning in customer experience (CX)?

AI-powered technologies such as Automated Insights and SurveyMonkey Genius help businesses collect cost-efficient responses from targeted audiences to uncover relevant insights more quickly than ever before. This speed-to-delivery is imperative, and Momentive's unique ability to balance technology with human experiences drives greater value for their customers.

Can AI replace human interactions in CX?

No, AI cannot replace human interactions. Instead, businesses must be thoughtful about their approach to incorporating AI into the customer experience flow.

What is the key to successful implementation of AI in CX?

The key to successful implementation is an open approach to customer feedback, as well as extensive training and education for employees at every level of the organization. Additionally, companies must remain mindful of AI ethics and ensure an ethical and inclusive approach to data collection.

How can AI and machine learning be used to build feedback options directly into a website or chatbot?

AI and machine learning can be used to build feedback options directly into a website or chatbot, or by generating automatic emails after specific customer touchpoints.

What is the future vision for the use of AI in CX?

Huang envisions a future where concepts such as AI copilots and AI assistants gain popularity, and AI buddies appear frequently in daily workflows to help businesses harness insights from millions of respondents and deliver a better overall customer experience.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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