Master Class: AI Sales Expert (AISE) – Outline

Detailed Course Outline

Day 1: Basics and Use Cases

Module 1: Introduction to AI and GenAI
Contents:
  • Definitions and Concepts:
    • AI: Overview of various AI types, from rule-based systems to deep learning.
    • GenAI: Explanation of generative models that produce content such as text, images, or music.
    • AI Agents: Interactive systems that independently perform tasks based on user interactions and environmental data.
  • Historical Development:
    • Key milestones in AI development.
    • From symbolic AI to machine learning and the era of GenAI.
  • Market Potential and Current Trends:
    • Global market size and growth rates in the AI sector.
    • Relevant industries: healthcare, retail, financial services, manufacturing.
    • Emerging technologies: transformer models, multimodal AI systems, AutoML.
Activity/Exercise:
  • Group Work:
    • Participants analyze the most common use cases in their respective industries.
    • Creation of a short presentation: How can AI/ GenAI/ AI agents deliver concrete improvements?
Module 2: Technologies and Tools for AI Solutions (3 hours)
Contents:
  • AI Technology Basics:
    • Difference between supervised, unsupervised, and reinforcement learning methods.
    • Structure of neural networks and how they recognize patterns in data.
    • Functionality of generative models such as GANs (Generative Adversarial Networks) and transformer architectures (e.g., GPT).
  • Hardware and Software Resources:
    • GPUs, TPUs, and other specialized hardware for AI training and inference.
    • Cloud services (e.g., AWS, Azure, Google Cloud) for AI projects.
    • Open-source libraries: TensorFlow, PyTorch, Hugging Face Transformers.
  • Integrations and APIs:
    • Overview of RESTful APIs and SDKs.
    • Ways to integrate AI models into existing software landscapes.
    • Security and privacy considerations when using AI services.
Activity/Exercise:
  • Practical Demonstration:
    • Participants work in groups with a simple generative model application, such as text or image generators.
    • They compare results and discuss implementation opportunities and challenges.

Day 2: Sales and Customer Focus

Module 3: Selling AI Products and Services
Contents:
  • Understanding Products and Services:
    • Differences between AI services (e.g., APIs, consulting), software products (e.g., pre-built AI solutions), and hardware solutions (e.g., AI-optimized hardware).
    • Use cases and benefits for various target audiences.
  • Communicating Customer Value:
    • Presenting success stories and case studies.
    • Addressing common customer concerns (e.g., data sovereignty, implementation costs) and how to handle them.
  • Industry Examples:
    • Using GenAI in marketing campaigns.
    • AI agents for process automation in call centers.
    • Hardware solutions for AI-powered image analysis in healthcare.
Activity/Exercise:
  • Role-playing:
    • Participants practice sales conversations with different customer types.
    • Peers act as customers, raising typical questions and objections.
    • Feedback session: Strengths and improvement areas.
Module 4: Strategies and Best Practices for AI Sales
Contents:
  • Developing Sales Strategies:
    • Market segmentation: How to identify potential customers.
    • Targeted outreach: Personalizing offers based on customer profiles.
    • Up-selling and cross-selling: Building a portfolio that extends beyond a single solution.
  • Building Customer Relationships:
    • Ongoing engagement with customers: Collecting feedback and deriving improvements.
    • Long-term customer retention through training and support.
  • Best Practices:
    • Case studies of successful AI implementations.
    • Key dos and don’ts in the sales process.
    • Adapting to technological changes and continuous learning strategies for sales teams.
Activity/Exercise:
  • Workshop:
    • Participants create a short pitch deck for an AI product or service.
    • Presentation in front of the group, followed by a feedback session.
    • Goal: Develop a convincing sales presentation that is practical and engaging.
Summary and Wrap-Up
  • Open discussion about lessons learned.
  • Addressing any remaining questions.
  • Participants receive a brief summary of the discussed topics and links to additional resources.