Artificial intelligence is an ideal match for customer support workflows, but not every support workflow is ready for AI. To determine where your customer support AI opportunities lie, you first have to answer three basic questions:
A big source of business for us at Talla is failed chatbot projects. Building chatbots for customer support is hard because most of them are scripted. You have to go in and do some regular expression matching and then label language intents, and then map those to a workflow. It's a lot of work to create an interaction, and then the bot doesn't really learn much once it is deployed. As the world changes and new support issues arise, you have to go do a bunch of work to add those new issues.
"Inbox Zero" is all the rage for personal productivity, but the equivalent for your support team would be "Backlog Zero" -- and it's achievable with artificial intelligence.
There are a lot of companies that want to use AI, but just don’t know where to start. 85% of executives believe that AI will give their business an inherent advantage (MIT Sloan Management Review and the Boston Consulting Group), however, of the half of CIOs planning to use AI, only 4% have actually implemented the technology (Gartner).
"You never get a second chance to make a first impression" isn't just a truism; it's a warning about deploying customer support chatbots before they are ready. If you prematurely hand off customer interaction to an artificially intelligent chatbot before that chatbot has been properly trained, you can do far more harm than good.
For those trying to introduce AI projects internally, generating buy-in requires more than facts and figures or trusting that the AI mystique will sell itself. As with any software sale, there will be an objection handling effort. It’s likely no one in your company has had to navigate this with an AI implementation yet, so you’ll find little internal advice. To help, here’s a brief look at three objections you’ll face. Included are insights on how to overcome each.