The best filter for automation vs. human support is the customer's emotional state. High-stress scenarios, even if procedurally simple, demand human empathy to maintain brand loyalty. Reserve automation for low-sensitivity, routine queries.

The true value of human interaction in customer service lies in understanding nuance. A person can empathize with a user's underlying frustration or goal—the "story" behind the problem—which is often different from the stated issue. This ability to serve the person, not just the ticket, is a key differentiator that automated systems miss.

Beyond automating 80% of customer inquiries with AI, Sea leverages these tools as trainers for its human agents. They created an AI "custom service trainer" to improve the performance and consistency of their human support team, creating a powerful symbiotic system rather than just replacing people.

Off-the-shelf AI support tools lack the deepest context for accurate answers, which is often found only in a company's proprietary source code (e.g., how interest is calculated). Klarna built its own system so its AI could directly access this 'source of truth,' making support a core part of its tech stack.

Companies adopt AI not to reduce headcount but to address the chronic shortage of skilled customer service advisors. AI handles mundane tasks like password resets, allowing humans to focus on high-value interactions and act as brand ambassadors, ultimately elevating their roles.

Companies aren't using AI to cut staff but to handle routine tasks, allowing agents to manage complex, emotional issues. This transforms the agent's role from transactional support to high-value relationship management, requiring more empathy and problem-solving skills, not less.

The goal of AI in customer service isn't human replacement. Instead, use AI agents to handle predictable, repetitive queries instantly. This strategy frees up human staff to focus their time on complex, empathetic problem-solving where a personal connection is most valuable.

The common practice of offering "premium" human-only support is counterintuitive. These customers often wait longer for a response compared to lower-tier users who receive instant, accurate answers from an AI agent, resulting in a poorer overall experience.

Ladder built custom AI tools to handle operational tasks at scale. "Maeve AI" manages 90% of support tickets, while "Ladder Pulse" synthesizes group chats for coaches. This strategy uses AI for leverage, allowing a small team to deliver a high-touch experience without a large headcount.