AI for Sales Professionals

AI for Sales Professionals

Understanding GenAI, Agentic AI, and RAG

AI has rapidly shifted from an experimental technology to a core capability that shapes how organizations operate and compete. Customers who buy servers are no longer satisfied with hearing about clock speeds or storage totals. They want to understand how their infrastructure can support intelligent applications, automate work, and handle more demanding digital workloads. This course provides sales professionals with a clear, grounded understanding of modern AI concepts and how those concepts connect to the hardware they sell. The instructor brings more than three decades of industry experience and will focus on practical, commercially relevant insights rather than academic theory.

Learning Outcomes

Participants will be able to:

• Describe what GenAI, Agentic AI, and RAG are in simple business language.
• Articulate the relevance of AI to enterprise customers who purchase servers and data center hardware.
• Recognize how AI adoption influences infrastructure needs.
• Identify potential business use cases that clients may pursue with AI.
• Understand risks, limitations, and responsible use topics that clients may ask about.
• Demonstrate foundational prompt and context engineering concepts.
• Discuss AI tools at a high level without overselling or overpromising.

Prerequisites

• Basic understanding of the company’s hardware product line.
• General familiarity with typical enterprise IT needs.
• Comfort with virtual instructor-led learning.
• No prior AI technical background required.

Training Outline

The following outline may be modified as per requirements.

1. Modern AI in the Business Landscape

• Current trends in business adoption
• Why organizations invest in AI capabilities
• Relationship between AI initiatives and IT infrastructure
• Shifts in customer expectations for data handling and compute capabilities

2. Foundations of AI Concepts

• Overview of traditional artificial intelligence
• Transition toward advanced language models
• Key terminology used in contemporary AI discussions

3. Generative AI Essentials

• Definition and core principles
• Types of generative models
• General categories of business applications
• Infrastructure considerations at a high level

4. Retrieval Augmented Generation (RAG)

• Concept and purpose
• Role of organizational data in RAG
• High level architecture components
• Benefits related to accuracy and relevance

5. Agentic AI

• Definition of AI agents
• How agents differ from simple model queries
• Relevance for workflow automation
• Broad implications for enterprise operations

6. Mapping AI Concepts to Customer Hardware Needs

• How AI workloads affect compute, storage, and network requirements
• Differences between on premises, hybrid, and cloud environments
• Positioning servers as the foundation for AI readiness
• How sales professionals can align AI interest with hardware solutions

7. Risks and Responsible Use Considerations

• Data quality issues
• Bias and fairness concerns
• Security and access control topics
• Reliability and oversight requirements
• Common areas of customer hesitation

8. Prompt and Context Engineering Fundamentals

• Structure of input prompts
• Role of context in improving model outcomes
• Importance of precise instructions
• How business users typically interact with AI tools

9. Overview of Common AI Tools and Platforms

• General categories of widely used AI tools
• Characteristics that customers evaluate when selecting tools
• Interaction between tools and underlying hardware environments

10. Sales Communication Framework for AI Conversations

• Approaching customer discussions about AI objectives
• Identifying potential business drivers
• Linking customer goals to infrastructure implications
• Communicating value without technical overload
• Handling common customer questions

11. Looking Ahead

• Evolving directions in enterprise AI
• Increasing demand for compute power
• Long term hardware considerations for customers preparing for AI expansion