12 Days of AI Use Cases Day 5: Professional Development Learning

Welcome to the 12 Days of AI Use Cases!

In this series, we’ll be looking at different use cases for AI – in particular, generative AI and large language models, the software that powers tools like ChatGPT, Google Gemini, and Anthropic Claude. Each day, we’ll look at the use case through the lens of the Trust Insights 5P Framework to see the role AI plays in achieving real, tangible outcomes.

These use cases are designed not only to be read, but also to be given to the generative AI tool as part of a prompt to help you achieve the outcomes you’re after. Ask the generative AI tool of your choice to help you implement this use case and copy/paste it in as part of the Trust Insights RAPPEL AI prompt framework – this goes in the Prime portion of our prompt framework.

Let’s dig in!

Purpose

Generative AI transforms complex concepts into understandable formats by translating them through the learner’s domain of expertise. This solves the fundamental challenge of professional development and training: making difficult concepts accessible and relatable to learners. By leveraging AI’s ability to translate concepts across domains, organizations and individuals can achieve better learning outcomes and knowledge retention.

People

Primary Actors

Learners form the core user base, including students tackling challenging coursework, employees understanding new methodologies, and managers developing leadership skills. These individuals actively seek to understand complex concepts by relating them to their areas of expertise.

Stakeholders

Educational institutions, corporate training departments, and professional development leaders hold significant interest in the outcomes. Their success metrics directly tie to improved learner performance, better knowledge retention, and enhanced job performance. Additional stakeholders include mentors and supervisors who benefit from their teams’ improved understanding and capabilities.

Process

• Identify and collect the source material containing complex concepts requiring better understanding
• Document the learner’s domain of expertise (e.g., cooking, sports, music)
• Input the source material into the chosen generative AI platform
• Request concept translation using the learner’s domain of expertise
• Engage in interactive dialogue to refine understanding
• Apply translated concepts to real-world scenarios
• Validate understanding through practical application
• Document insights and create reference materials for future use

Platform

• Primary Tools:
  • Generative AI language models (Google Gemini, ChatGPT, Anthropic Claude, Meta Llama)
  • Learning management systems for tracking progress
  • Note-taking tools for documentation
  • Collaboration platforms for sharing insights
• Technical Requirements:
  • Internet connectivity
  • Access to chosen AI platform
  • Basic understanding of prompt engineering
  • Storage solution for saving translations and insights

Performance

Primary Goals

Organizations measure success through improved educational and professional outcomes. In academic settings, this translates to better grades and increased retention rates. In professional environments, success manifests as enhanced job performance, improved customer interactions, and stronger team collaboration. The ultimate goal centers on achieving demonstrable improvement in concept understanding and practical application.

Key Performance Indicators

• Knowledge Retention Rate: Measure the percentage increase in information retained after AI-assisted learning compared to traditional methods through assessment scores
• Application Success Rate: Track the successful application of learned concepts in real-world scenarios through project outcomes and supervisor feedback
• Learning Efficiency: Monitor the time required to achieve competency in new concepts compared to conventional learning methods, targeting a minimum 25% reduction in learning time

We hope this use case is clear and helpful. If you’d like help implementing it or any other AI use case, reach out and let us know.

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.