As AI automation grows in customer experience, the most forward-thinking organizations aren’t replacing humans, they’re redefining how humans and AI work together. In this insightful conversation with David DeMarco, SVP of Business Technology at Carta, on AI CX Innovators, Ashish explores why increased automation actually makes quality assurance more crucial and how “white space mining” can uncover the 20% of issues driving 80% of CX improvements. 

David also shares Carta’s strategic approach to channel selection, giving customers choice in how they engage while reserving human expertise for complex equity and valuation discussions. He also details their innovative AI workers program that’s transforming coaching and sentiment analysis without complex rubrics—simply uploading a document with expectations generates comprehensive coaching plans across agent interactions. 

Topics Discussed:

• The counterintuitive relationship between automation and quality assurance, where increasing AI implementation actually makes QA more essential for ensuring accurate responses and uncovering valuable voice of customer insights rather than diminishing its importance.
• Implementing human-in-the-loop strategies for critical financial conversations to maintain oversight in high-value interactions where errors could have significant consequences, while allowing automation to handle straightforward inquiries.
• Mining the white space in conversational data through automated concern mining to extract insights from the majority of customer interactions that receive no formal reviews, identifying patterns that drive 80% of CX improvements.
• Translating conversational intelligence into product roadmap priorities by contextualizing data for product teams with supporting evidence that demonstrates the significance of customer pain points requiring development attention.
• The three-part framework for CX leadership success in the AI era that begins with data literacy to understand patterns, develops storytelling skills to gain cross-functional buy-in, and builds change management expertise to implement effective solutions.
• Strategic channel selection methodology that empowers customers to choose their preferred support avenues while purposefully reserving human touchpoints for complex financial conversations requiring trust and consultation.
• Leveraging ongoing vendor dialogues as an innovation catalyst, continuously exploring new technologies to assimilate ideas and identify emerging solutions even before purchasing decisions are made.
• Implementing specialized AI workers for CX functions including a support coach that automates coaching with no formal rubric required, and a sentiment insights worker that performs multi-step analysis on conversational data.
• Creating document-based coaching automation that eliminates complex scoring frameworks by allowing teams to simply upload expectations documents that AI transforms into comprehensive coaching plans across agent interactions.