Instead of simply automating jobs, ZocDoc's AI redesigns the entire patient intake process. It triages calls, routing simple queries to an AI and complex ones to the most qualified human specialist. This transforms a cost center into a highly efficient system that improves the patient experience.
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.
To ensure reliability in healthcare, ZocDoc doesn't give LLMs free rein. It wraps them in a hybrid system where traditional, deterministic code orchestrates the AI's tasks, sets firm boundaries, and knows when to hand off to a human, preventing the 'praying for the best' approach common with direct LLM use.
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.
An unexpected benefit of setting up an AI system is that it forces you to review customer interaction playbooks. Companies often discover their official scripts and processes are outdated, leading to crucial updates that improve both the AI's performance and the human team's effectiveness.
Instead of replacing humans, Aviva uses AI to anticipate *why* a customer is calling about a claim. The agent receives this prediction and relevant data upfront, skipping lengthy verification and improving the customer experience.
The most significant near-term impact of voice AI will be in call centers. Rather than simply replacing agents, the technology will first elevate their effectiveness and productivity. Concurrently, voice bots will handle initial queries, solving the common pain point of long wait times and improving overall customer experience.
A tangible way to implement a "more human" AI strategy is to use automation to free up employee time from repetitive tasks. This saved time should then be deliberately reallocated to high-value, human-centric activities, such as providing personalized customer consultations, that technology cannot replicate.
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.
Adopt a 'more intelligent, more human' framework. For every process made more intelligent through AI automation, strategically reinvest the freed-up human capacity into higher-touch, more personalized customer activities. This creates a balanced system that enhances both efficiency and relationships.