RFP template: Choosing AI technology for enterprise customer service
An excel sheet containing 100+ detailed evaluation questions across seven categories in scoring-ready format you can send directly to vendors.
Learn MoreEnterprises are rethinking how AI fits into their customer service model. From team structures to long-term planning, explore the strategies behind successful transformation.
Here’s a look at the nuts and bolts of an AI agent and what’s most important to know about how to successfully integrate them into your business.
How safe is customer data in a world run by AI agents? And what do companies need to do to protect it?
As this year of impressive innovation comes to a close, it’s the perfect time to think about customer service challenges and opportunities.
CEO of the AI Exchange, Rachel Woods, walks through the playbook that they use for customers and internally, to optimize operations with AI.
Here’s a deeper look at the role AI and data can play in helping companies predict everything from ROI and churn to specific customer service issues.
As AI chatbots become more advanced, should they sound just like us, or retain some bot-ness?
Before you can determine if chatbots or conversational AI is best suited to your customer service needs, you have to understand the difference.
Here’s a look at why containment rate fails as an automation metric, and measures of success that can be tapped instead, such as automated resolutions.
AI can’t do customer service entirely on its own. Human customer service workers have to build new systems and overcome challenges to reap its benefits.
The rising cost of human-led support is a frustrating reality in customer service. Is generative AI customer service the answer?
New generative AI capabilities to automate more with less effort, power more complex use cases, and bring AI to new channels.
Best practices for knowledge management to make the most out of generative AI for CX automation while ensuring it remains relevant, accurate, and safe.