Is your Conversational AI (CAI) strategy keeping you up at night? 

Whether you’re working on Conversational AI (CAI) in-house, or you’re a technology vendor building custom CAI offerings for clients, your challenges can be significant. Not only do you have to ensure that your solution results in a great user experience; you also need to make sure that it performs efficiently, is cost-effective, and delivers competitive advantage.

CAI solutions have a lot of moving parts, but one of the most important elements to get right is the data. CAI success depends on high-quality, accurate and unbiased training data.

Today, the conversational AI market is valued at around $6.8 billion (USD) and IDC forecasts that it will grow at a compounded annual rate of nearly 29% between now and 2025. 

With that kind of dramatic growth on the horizon, many industry segments are using CAI to position themselves at the forefront of their respective markets: 

Customer service

Customer service uses virtual assistant solutions to decrease overhead with automated customer support 

Healthcare

Healthcare uses CAI for front-office automation, filling in forms, managing patient history, updating records, and sending alerts about appointments and prescription refills 

Ecommerce

Ecommerce uses CAI to add value to the customer experience, capturing and qualifying leads more rapidly, providing a consistent omni-channel presence, and responding faster to customer inquiries and issues 

Manufacturing

Manufacturing uses chatbots to automate sales, marketing, and support functions, and eliminate communication delays that can result in critical supply-chain issues

Travel and hospitality

Travel and hospitality uses CAI to provide 24/7 automated assistance for reservations, insurance, passport and visa information, and upgrades, and to customers who may require urgent assistance when in a far-away time zone 

Download this eBook, Taking the risk out of Conversational AI , to learn:

  • How to consider and mitigate various risks when rolling out and CAI and strategies
  • How to create a data strategy to develop or enhance your CAI solution
  • How an experienced AI training data partner can help ensure the success of your solution