The Data Standard

The current state of conversational AI? with Michelle Gregory

Michelle Gregory, Senior Vice President of Data Science at [24]7.ai, sits down with TDS to discuss the current state of conversational AI.

Episode Summary

There’s been so much hype around conversational AI that – unless you’re a researcher in the field – it’s difficult to know what’s possible and what’s not.

Even though AI is still in its early stages of development, it can already offer many benefits to businesses. And conversational AI is surely one of them.

In recent years, the need for implementing chatbots either for customer or sales support has grown tremendously, contributing to the growth of the entire conversational AI market, which is expected to be worth more than $250 million by 2027. As more businesses have started to implement conversational AI, consumers have also been getting friendlier towards chatbots in the past couple of years.

But what is the state of conversational AI now?

Indeed, the current pandemic has introduced some changes to every industry, and conversational AI is not an exception. And the only way we can predict where this industry will be after the pandemic is over is only by analyzing how it is changing right now.

Meet The Host

Catherine Tao

Data scientist at The Data Standard

Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.

Meet The Guest

Michelle Gregory

Senior Vice President of Data Science at [24]7.ai

Throughout my career as a data scientist, I focused on the understanding and visualization of large amounts of data, including real-time social data. Research topics include information extraction, online communication, sentiment and opinion analysis, natural language processing, machine learning, and high performance computing. My real passion lies in making big data solutions, machine learning, and artificial intelligence capabilities applicable and scalable for real world applications. As head of R&D and data science programs, I specialize in understanding customer needs and applying big data engineering and scientific solutions that are used in products and solve real world problems. In order to accomplish this, I focus on building world class data science teams.