Using AI Responsibly in the Workplace
A branching scenario-based learning module that allows employees to practice making decisions about AI use in a safe environment.
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Target Audience: Corporate employees across departments
Responsibilities: Analysis, Instructional Design, eLearning Development, Visual Design
Tools Used: Articulate Storyline 360, Adobe Illustrator, Adobe Photoshop, Figma, ChatGPT
Overview
With the rise of generative AI tools like ChatGPT and DALL·E, organizations face new opportunities for productivity, but also new risks around data security, compliance, and ethical use. Employees often lack guidance on how to use AI tools effectively while following company policies.
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To address this need, I designed a branching scenario-based learning module that allows employees to practice making decisions about AI use in a safe environment. Instead of reading guidelines, learners experience realistic workplace situations and see the consequences of their choices.​​
Process
To design efficiently without sacrificing quality, I used ChatGPT as a creative and technical partner throughout the storyboarding and development process.
ChatGPT then helped me draft learner choices and feedback that reflected varying degrees of understanding, from fully correct to partially correct and incorrect responses. I also leveraged it to refine tone and difficulty, maintaining a balance between accessibility and authenticity, and to generate clear narration and on-screen text for consistency across screens.
Throughout the process, I carefully reviewed and revised every AI-generated element to ensure accuracy, adherence to policy, and alignment with the intended voice and learning objectives.
Analysis
As AI tools become more integrated into daily workflows, employees are increasingly using them without clear guidance.
Through my analysis, I identified three high-risk areas associated with the rise of AI in the workplace:
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Data security and confidentiality: Employees may unintentionally share sensitive information in AI prompts.
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Accuracy and reliability: Overreliance on AI outputs can lead to errors, misinformation, or misaligned tone.
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Ethical and transparent use: AI-generated visuals and text can create credibility and compliance risks if not properly attributed or disclosed.
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These findings highlighted a need for practical, scenario-based training that helps employees develop good judgment in real-world contexts.
I designed a branching scenario that allows learners to safely explore realistic decision points related to AI use. This approach gives learners the opportunity to:
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Apply critical thinking to nuanced situations, rather than memorize rules.
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See the consequences of their decisions immediately through tailored feedback.
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Build confidence in making ethical, responsible, and productive choices.
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By using this format, the learning experience moves beyond theoretical awareness to actual behavioral practice, helping learners internalize responsible AI use as part of their everyday work.
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I mapped the flow with ChatGPT and Figma, using a decision tree visualization, which clearly outlined:
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Each scenario and choice path
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Points assigned (0, 0.5, or 1)
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Personalized results screen logic
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This, along with a narrative storyboard, ensured logical consistency before moving into authoring tools.
Design
Development
I translated the storyboard and decision tree into an interactive prototype using Articulate Storyline.
The course captures the learner’s name through a variable to create a personalized welcome, enhancing engagement from the start.
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​Visual and text design were carefully crafted to align with WCAG accessibility standards, creating an inclusive experience while maintaining clarity and aesthetic appeal.
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​Each decision point includes custom feedback layers with concise, narrative-style messages, and audio narration with closed captions ensures accessibility and reinforces learning.
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The branching logic was implemented so that each learner choice dynamically determines the next scenario path, allowing realistic consequences and multiple outcomes. Scoring variables track learner decisions across scenarios, accumulating points for correct, partially correct, and incorrect actions.
After initial setup, I tested the scenario for:
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Logical flow and variable scoring accuracy
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Clarity of feedback tone and pacing
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Accessibility compliance (text equivalents, readable narration)
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ChatGPT supported this phase by generating QA checklists and test cases for validating each path.
Evaluation
The course concludes with a results screen that provides feedback tailored to the learner’s total score, highlighting strengths and areas for improvement in responsible AI use.
Key takeaways are reinforced, and learners are encouraged to replay the scenario to explore alternative choices, reflect on different outcomes, and deepen their understanding of ethical and effective AI practices.
Result
This project demonstrates how AI can accelerate the design process while maintaining instructional depth.
By pairing human judgment with AI efficiency, I was able to:
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Develop a complete, high-quality microlearning prototype in days instead of weeks
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Focus more on creative storytelling and learner experience, and less on repetitive drafting tasks​​
