5 Actionable Ways To Use AI In Professional Development Design

Practical, Responsible Ways To Use AI In Professional Development Design

Professional Development (PD) is one of the first terms many of us learn when we step into the world of work. PD can elicit a wide range of emotions from excitement and curiosity to indifference or even dread. Regardless of how we feel about it, PD is here to stay. AI is rapidly transforming both daily life and the workplace. As organizations roll out targeted PD on AI and its uses, many who are already proficient with AI are finding that it improves efficiency and, in some cases, the quality of their contributions. At the same time, educators, trainers, and PD leaders face increasing pressure to design high-quality, flexible professional learning.

Although AI is sometimes met with fear, such as concerns about job replacement or inaccurate outputs, it also inspires optimism due to its potential to enhance productivity and personalize learning. PD is uniquely positioned to help employees develop the knowledge, skills, and mindsets needed for ethical and effective AI use. For PD designers and leaders, AI offers numerous benefits. Used as a digital thought partner, AI can accelerate content creation and reduce the workload of editing and formatting. This article outlines five practical ways PD designers can use AI responsibly to create meaningful, scalable learning experiences.

Understanding LLMs In Professional Development Design

Large Language Models (LLMs) are AI tools capable of understanding and generating humanlike language. Trained on vast amounts of text and code, they identify patterns and predict what comes next in a sequence. Common concerns include:

1. Bias in outputs.
2. Hallucinations or inaccuracies.
3. Overreliance, potentially reducing users' critical thinking.
4. Privacy, particularly regarding personal or organizational data.

Despite these concerns, many professionals have found that AI enhances their work when used thoughtfully. In PD design, LLMs should be treated as support tools, not autonomous creators. Ultimately, human designers remain responsible for the quality, accuracy, and appropriateness of the PD they develop with or without AI. Below are five practical ways to use AI to design PD and training.

1. Generate And Refine Learning Outcomes Around Set Objectives

Effective PD design begins with best practices such as ADDIE, Bloom's Taxonomy, the SAM model, the Dick and Carey model, or the Kemp Design model. Fidelity to existing standards, performance indicators, or organizational objectives is essential, and these elements should remain central to the PD structure. LLMs can assist by drafting, revising, or differentiating learning outcomes for multiple roles or experience levels, supporting greater personalization and relevance. Once outcomes are established, AI can also help generate assessments and aligned activities (see item 4). Remember that while AI can support the design process, it must not replace instructional expertise or dictate the learning pathway.

2. Summarize Key Texts Or Resources To Support Presentation And Materials Development

PD should be grounded in current research, organizational priorities, and professional expectations. AI can summarize key texts, resources, or notes from Subject Matter Experts (SMEs), allowing designers to quickly build slide decks, facilitator guides, or resource packets. Always verify accuracy and credit your sources. Summaries are starting points, not substitutes for understanding.

3. Draft Or Refine Rubrics And Grading And Feedback Criteria

AI can help develop rubrics and feedback criteria aligned to learning outcomes or performance indicators. LLMs can identify key assessment criteria and propose rubric categories, achievement levels (e.g., developing, proficient, excellent), and weighting considerations. This is especially useful for open-ended tasks, reflections, or performance-based demonstrations, which naturally vary from participant to participant. AI can also help create feedback templates or sentence stems that instructors can personalize.

When PD includes multiple roles, such as organization-wide onboarding or training for teachers, paraprofessionals, faculty, and administrators, rubrics provide consistent expectations across diverse participant groups. Since design is iterative, especially when using backward design, revisiting rubrics as your course evolves is expected and beneficial.

4. Develop And Refine Instructional Activities

LLMs can support the creation of engaging and aligned instructional activities. Designers can use AI to generate or refine:

1. Multiple-choice, true/false, and short-answer questions.
2. Discussion prompts.
3. Case studies or scenarios.
4. Workplace simulations or role-play scripts.
5. Fabricated datasets for Excel or data literacy practice including visualizations.
6. Writing prompts.
7. Reflective prompts or journaling questions.
8. Text and images for interactive digital tools (e.g., H5P branching scenarios, drag-and-drop activities, gap fills)
9. Job aids, checklists, or quick-reference guides.
10. Microlearning modules or lesson outlines.

• Important
  Designers remain responsible for ensuring all materials are accurate, culturally responsive, accessible, and appropriate for the audience.

5. Provide Exemplars Of Completed Tasks, Assignments, Or Reflections

Exemplars help participants understand expectations before beginning work. After providing assignment instructions and criteria, LLMs can draft sample responses that illustrate different performance levels. For best results, include parameters such as:

1. Focus or topic.
2. Target level or score.
3. Strengths to demonstrate.
4. Common errors or weaknesses to illustrate.

These exemplars support clarity, reduce confusion, and improve alignment between outcomes and assessments.

Considerations For Responsible AI Use In Professional Development Design

AI-enhanced design is iterative. Expect to revise elements as you build, test, and refine PD modules. Designers should:

1. Remain flexible.
2. Anticipate the unknowns of AI-assisted creation.
3. Approach the design process with curiosity and openness.
4. Treat AI as a collaborator, not an expert or a shortcut.

AI should support human creativity, not replace it.

Keeping Humans At The Center

AI can expand the capabilities of PD designers, school leaders, instructional designers, and L&D professionals. When used thoughtfully, LLMs streamline planning, generate rich instructional materials, and support scalable PD models while keeping the human element at the center. The goal is not to automate professional learning but to amplify the creativity, clarity, and intentionality of the humans designing it.