While AI can increase efficiency, many customers are not yet comfortable relying on it fully. To maximize lead capture, AI-driven systems like chatbots must provide an easy, immediate option to connect with a person. A system that is "AI-driven but human-backed" ensures no customer is lost due to their technology preference.

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.

To mitigate risks like AI hallucinations and high operational costs, enterprises should first deploy new AI tools internally to support human agents. This "agent-assist" model allows for monitoring, testing, and refinement in a controlled environment before exposing the technology directly to customers.

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.

An attempt to use AI to assist human customer service agents backfired, as agents mistrusted the AI's recommendations and did double the work. The solution was to give AI full control over low-stakes issues, allowing it to learn and improve without creating inefficiency for human counterparts.

Prioritize using AI to support human agents internally. A co-pilot model equips agents with instant, accurate information, enabling them to resolve complex issues faster and provide a more natural, less-scripted customer experience.

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.

Fully autonomous AI agents are not yet viable in enterprises. Alloy Automation builds "semi-deterministic" agents that combine AI's reasoning with deterministic workflows, escalating to a human when confidence is low to ensure safety and compliance.

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.