When a customer opens a support case, all marketing pretense vanishes. They are frustrated, something is broken, and they need a real solution. This "moment of truth" is where most systems fail due to chaos and complexity, presenting a prime opportunity for AI to streamline and improve the experience.

The quality of interaction trumps the medium. Customers will choose a highly-trained, instantly responsive AI agent that solves their problem over a human who is slow, new to the account, or provides a subpar experience. This establishes a new bar for customer service.

Don't worry if customers know they're talking to an AI. As long as the agent is helpful, provides value, and creates a smooth experience, people don't mind. In many cases, a responsive, value-adding AI is preferable to a slow or mediocre human interaction. The focus should be on quality of service, not on hiding the AI.

Twilio's AI agent is not a traditional sales bot. Its main goal is to help users succeed with the product by answering questions and providing guidance. This customer-centric approach has resulted in users who interact with the agent being three times more likely to upgrade their accounts.

With AI empowering agents, traditional efficiency KPIs like 'average handle time' are losing relevance. Modern CX teams should prioritize effectiveness metrics such as 'resolution quality,' 'customer effort,' and 'first-call resolution,' which better correlate with brand trust and loyalty.

Contrary to fears of customer backlash, data from Bret Taylor's company Sierra shows that AI agents identifying themselves as AI—and even admitting they can make mistakes—builds trust. This transparency, combined with AI's patience and consistency, often results in customer satisfaction scores that are higher than those for previous human interactions.

For companies wondering where to start with AI, target the most labor-intensive, process-driven functions. Customer support is an ideal starting point, as AI can handle repetitive tasks, leading to lower costs, faster response times, and an improved customer experience while freeing up human agents for more complex issues.

By implementing an AI agent trained on its knowledge base, Castos (a SaaS with 4,000 customers) reduced support tickets by 50%. The system provides instant answers while a crucial "escape hatch" button allows customers to easily reach a human, preventing frustration.

Instead of focusing solely on CSAT or transaction completion, a more powerful KPI for AI effectiveness is repeat usage. When customers voluntarily return to the same AI-powered channel (e.g., a chatbot) to solve a problem, it signals the experience was so effective it became their preferred method.