GPT Voice vs. Human Agents

Last week, OpenAI finally launched the anticipated Voice mode, and one thing stood out: its cost.

The Realtime API uses both text tokens and audio tokens. 
Text input tokens are priced at $5 per 1M and $20 per 1M output tokens. Audio input is priced at $100 per 1M tokens and output is $200 per 1M tokens. 
This equates to approximately $0.06 per minute of audio input and $0.24 per minute of audio output.

This translates to $0.15 per minute. It’s arguably quite expensive and higher than expected, leaving many wondering how it compares to the cost of human agents.

This pricing is less expensive than the hourly rate of human agents in the U.S. and U.K., but 2x the cost of human agents in the Philippines and 5x the cost of those in India.

What does this mean for customer support?

There’s been a lot of talk about what Voice mode means for the industry.

There are two main opinions on its impact:

• Bot enthusiasts: People who boast AI bots will very soon completely replace human agents. Likely affiliated with voice bot companies.

• Traditionalists: Legacy thinkers who are skeptical of AI’s potential to replace agents due to the complexity of the industry and technology’s immaturity.

The truth, as almost always, falls somewhere in the middle—AI will eventually disrupt the industry entirely, however it will take way more time.

Let’s get some things straight

• The contact center industry is huge and complex

• Major changes will not happen overnight

• Customer acceptance will be the ultimate driver in bot deployment and adoption

• Millions of people losing jobs is a major political problem. If the process starts to get regulated, it may take much longer.

Voice Bots: Pros and Cons

• Pros

  • The price of Voice AI will go down by 2-3x in a year

  • Voice bots will cover more and more use cases

  • Much easier to manage bots than people

  • Bots work 24/7, without breaks and don’t get tired

  • No paying overtime

  • Speaks multiple languages

  • No onboarding and training

  • Easy to scale.

• Cons:

  • AI hallucinates and, until this is solved, AI won’t be trusted

  • Hallucination errors add up and compound when multiple agentic flows are bound together

  • Large integration cost with legacy systems

Where Humans Outperform

• Show empathy, read between the lines, and connect with customers

• Have intuition, can adapt, and are better at handling complex or sensitive issues

• Create trust and rapport with customers

What happens next?

Few things should happen for the adoption of Bots to accelerate

• Must stop hallucinating

• Reasoning must get better

• The price must go down

• Must have more integrations into enterprise systems and tooling