The biggest productivity unlock isn't just making customer support cheaper. It's using AI models to eliminate the need for separate human archetypes for sales (yapper) and support (listener). Companies will bundle these functions into one unified team aimed at a higher-level business goal, like improving CAC.

With infinitely scalable AI agents, cost and time per interaction are no longer primary constraints. Companies should abandon classic efficiency metrics like Average Handle Time and instead measure success by outcomes, such as percentage of tasks completed and improvements in Customer Satisfaction (CSAT).

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.

Coastline Academy frames AI's value around productivity gains, not just expense reduction. Their small engineering team increased output by 80% in one year without new hires by using AI as an augmentation tool. This approach focuses on scaling capabilities rather than simply shrinking teams.

While initial sales conversations for BPO replacement focus on 50-75% cost savings, customers discover greater value in AI's unique abilities. These include superhuman speed to close business faster, instant scalability for seasonal demand, and unprecedented observability into previously "black box" processes.

The true power of an AI agent is its capacity to handle the mundane, repetitive work that humans—both internal teams and external agencies—often neglect or de-prioritize. SaaStr couldn't find people willing to consistently manage hundreds of follow-ups, a task their AI now handles flawlessly.

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.

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.

Viewing Customer Success as merely a satisfaction function is an outdated model. With AI lowering barriers to entry for competitors, CS must be a "money generation function for the business," actively driving expansion, retention, and cross-sells to build deep, defensible customer relationships.