A support agent copy-pasting the same answer for the twentieth time in one shift is usually the clearest sign that a team is ready for generative AI. This hands-on training course from the Arab British Fellowship Training Academy takes that everyday frustration as its starting point, showing customer service professionals how tools such as custom GPT builders, Google's Gem, and Anthropic's visual AI can take repetitive work off their plate while keeping responses accurate, fast, and personal.

Rather than treating AI as an abstract concept, the course is built around practical assignments and real case studies: attendees configure a custom GPT model, automate an email workflow, and run a visual-AI check on a product issue, all while learning to keep the human touch that customers still expect. Combining prompt engineering with automation best practice, the course leaves customer service teams ready to cut response delays, raise the value of every customer interaction, and keep pace with how support work is actually changing.

Objective

By the end of the course, attendees will be able to:

• Apply generative AI and effective prompt engineering to everyday customer service tasks.
• Build a custom GPT model from customer service data to generate personalised replies to support tickets.
• Automate email-based support by integrating a Google Gem with Gmail.
• Run an Anthropic-powered visual analysis project to flag product defects and suggest recommendations.

Who Should Attend?

• Help desk representatives, call centre agents, and customer success managers looking to work faster with AI.
• Support team leads focused on cutting response times and automating repetitive tasks.
• Professionals across retail, finance, healthcare, and tech support seeking practical AI skills.
• No prior AI knowledge is required to attend.

How Will Attendees Benefit?

• Automate responses, streamline ticket handling, and cut response time using tools like ChatGPT and other LLMs.
• Improve customer satisfaction through consistent, AI-enhanced communication at every touchpoint.
• Interpret customer data to solve even complex support problems in real time.
• Scale support cost-effectively with AI chatbots and virtual assistants, without growing the team.
• Get hands-on practice with the newest AI tools built for customer service.
• Connect generative AI with CRM platforms such as Salesforce, HubSpot, and Zendesk.
• Use AI-generated insights and analytics to improve team performance and customer engagement.
• Personalise responses based on customer history, behaviour, and preferences.
• Apply responsible-AI practices — data privacy, ethics, and bias prevention — to every interaction.
• Build a lasting competitive advantage through AI proficiency in customer care.

Module 1: Prompt Engineering as Your Starting Toolkit

• What prompt engineering is and why it matters for support scenarios.
• Writing prompts that produce accurate, on-brand replies.
• Practice sessions using ChatGPT for real-time support tasks.

Module 2: From Data to a Working Custom GPT

• Collecting and structuring customer service data.
• Fine-tuning or customising a GPT model for support use.
• Deploying the model to generate ticket replies.

Module 3: Automating Email and Everyday Communication

• Introducing Google's GenAI tools, including Gemini/Gem.
• Setting up AI-based workflows for email replies.
• Automating follow-ups and FAQs through Gmail integration.

Module 4: Visual AI for Product and Quality Issues

• Understanding Anthropic's AI tools and visual analysis capabilities.
• Using AI to detect product defects and suggest solutions.
• Applying visual AI within existing service workflows.

Module 5: Connecting AI to CRM, Personalisation, and Real Cases

• Linking generative AI with CRM systems (Salesforce, Zendesk, HubSpot).
• Personalising support using customer profiles and past behaviour.
• Industry case studies across retail, finance, healthcare, and tech, with group problem-solving.

Module 6: Using AI Responsibly

• Understanding the risks: data privacy, bias, and transparency.
• Guidelines for responsible AI use in customer communication.
• Balancing automation with human empathy.

Module 7: Measuring and Sustaining AI Impact

• Defining KPIs and metrics for AI-enabled support teams.
• Using dashboards to track AI effectiveness.
• Driving continuous improvement through feedback loops and analytics.