We’re thrilled to announce that our AI in the Workplace course is now available!

The latest addition to our modular training library, AI in the Workplace provides an overview of generative AI, how it’s commonly used in professional environments, and teaches employees how to use these tools in a way that protects your organization’s confidential information and safeguards data privacy.

What is generative AI?

Generative AI refers to a type of artificial intelligence that can create new content, like text, images, audio, or code, by learning patterns and structures from existing data. Unlike traditional AI systems designed to analyze or classify data, generative AI models are capable of producing original, human-like outputs.

Key characteristics of generative AI

  1. Content generation: Generative AI creates outputs such as stories, artwork, or even functional software.
  2. Pattern learning: These models learn from large datasets to mimic the style, tone, and structure of the inputs.
  3. Adaptability: It can generate tailored outputs based on specific prompts or instructions.

Why did we create this course?

Training employees on ethical use of generative AI tools is critical for ensuring their productivity benefits are maximized while mitigating risks. As these tools become more integrated into daily workflows — 92% of the Fortune 500 have adopted generative AI — equipping employees with the knowledge to use them responsibly will enhance productivity, help maintain ethical standards, and protect sensitive data.

Course details

  • 10 minutes
  • Can be delivered via Ethena or your LMS (SCORM)
  • Training auto-saves and is mobile-friendly
  • Meets accessibility standards
  • Customizable training content

Topic coverage: what employees will learn

  • Common ways AI is used in the workplace: Applications for generative AI have been created for functions like customer service chatbots, voice generation, 3D designs, code development, custom music, translations, and, of course, generating text and images based on prompts.
  • The differences between public and enterprise AI: Public AI refers to widely accessible AI models available to the general public, often with less stringent data privacy controls. Enterprise AI is designed specifically for businesses, prioritizing data security and tailored functionality to address specific organizational needs.
  • How to recognize bias in AI tools: While AI can mitigate bias by removing the unconscious biases that can sometimes make their way into our individual decisions, they can also reflect social inequities and — if deploying them at scale — actually amplify them.
  • Awareness of AI errors: AI-generated marketing materials can give wrong information, chatbots have advised information-seekers to break the law, and in some cases it’s possible to manipulate an AI assistant into saying things a customer service representative never should. 
  • How to safeguard confidential information: What’s sensitive or confidential can vary from company to company, but it typically includes IP and future plans for the business — like product and engineering ideas, marketing plans, designs, or service agreements. If you ask an AI to help with revenue projections, does that involve “feeding” the AI your financial model? Think about it!

About Ethena

Hey, we’re Ethena! We take you beyond checking the box with a modern library of 150+ customizable course modules and tech that lets you set it and forget it. An employee hotline, case manager, and phishing simulator are all built-in, so you can identify risks and tailor your training to them. We’re trusted by the People and Compliance teams at Pinterest, ZenDesk, Notion, The Salvation Army, Whitney Museum, and more. So — what are you waiting for?


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