This is season eleven, episode ten. In this episode, we will focus on how to deploy and maintain your custom GPT for long-term success. You will learn how to continuously update AI with new product data, monitor response accuracy, and scale AI-powered customer support across multiple platforms. By the end of this episode, you will have a clear plan for keeping your AI assistant up to date and improving its performance over time. So far, we have trained AI to handle customer queries, product recommendations, pricing, and even complex edge cases. Now, we need to ensure that the AI remains reliable and scalable as your business grows. Let’s go step by step on how to deploy your AI assistant, maintain accuracy, and expand AI support across different channels. Step One: Deploying AI for Daily Customer Support Once your custom GPT is trained and fine-tuned, it is time to deploy it in real customer interactions. AI can be integrated into different support channels, including: Live chat systems on your website for instant customer assistance. Email automation tools to draft replies for customer inquiries. CRM systems to help sales and support teams generate responses. E-commerce platforms to provide product recommendations and pricing. Before launching AI, businesses should test real...

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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