By Ray Jimenez, PhD .
Expert consultant, author & innovator with extensive cross-industry experience. Speaker and workshop facilitator driving effective approaches to learning.
Q: How do you see AI like ChatGPT disrupting and enhancing corporate learning and development programs? What gets easier vs. harder?
A: The integration of AI, particularly platforms like ChatGPT, into corporate learning and development (L&D) presents both opportunities and challenges.
On the positive side, ChatGPT enables a huge leap in the learning process. It catapults learners directly toward practical application, sidestepping traditional, often drawn-out learning pathways. This rapid approach ensures that learners can apply their knowledge in real-time scenarios faster, making the overall learning process more efficient.
Moreover, using ChatGPT aligns with the drive towards better performance. Our goal isn’t just to educate but to elevate, pushing our learners to achieve the top 5% of desired outcomes. This means exploring the vast sea of information but narrowing it down to the most important stuff. By assisting learners in sidestepping unnecessary, less crucial, and time-consuming activities, we ensure they are spending their time and energy most productively.
However, it’s not just about efficiency— it’s also about efficacy. ChatGPT aids in making the learning journey both straightforward and potent. The AI-driven approach ensures that the content delivered matches precisely what the learners aim to achieve. By zeroing in on what’s truly essential, learners are guaranteed that every moment spent in the program is valuable.
While AI-driven L&D initiatives like ChatGPT offer numerous advantages, it’s also crucial to recognize and navigate potential challenges. The absence of the human touch in certain learning scenarios where AI is applied might need to be complemented with human expertise. Balancing AI’s efficiency with the irreplaceable qualities of human interaction will be the key to a holistic L&D strategy.
Q: What use cases have you seen where AI-powered chatbots excel in corporate training and where do they fall short?
A: In learning and development, the way you think about generative AI could spell the difference between low-impact, low-retention learning, and effective instruction. One thing many users may overlook, too, is the benefit of organizing your thinking towards generative AI.
While at this point, it’s impossible to completely map out what it can do, it would be a great benefit to build some structure around one’s use of ChatGPT. We addressed that by introducing the 15 ChatGPT Learning Models. These thinking frameworks chart some practical and theoretical use cases of ChatGPT.
The Fifteen (15) Learning Models Using AI ChatGPT.
- Cohorts Learning
- Peer-to-Peer Review
- Growth Leadership
- Coaching
- Building a Casework
- Self-Study
- Refute, Rebut
- Perpetual Thinker
- Re-asking Questions
- Private Content and Context
- Workflow Decision-Making
- Collaborate Lesson
- Financial Planning
- Problem-Solving
- Zero to 99% Facilitations
Q: How can companies effectively blend AI technology with human instructional designers and trainers?
A: To make the best use of AI like ChatGPT with human instructional designers and trainers, companies can combine ChatGPT’s smart features with the knowledge and skills of the trainers. Here’s a simplified way to improve their teamwork.
Questioning
Understand ChatGPT conversations and interactions. In technical terms, ChatGPT prompts are the textual inputs (e.g., questions, instructions) that you enter into ChatGPT to get responses. ChatGPT predicts an appropriate response to the prompt you entered. In general, a more specific and carefully worded prompt will get you better responses. From a learner’s view, the conversation between the learner and ChatGPT is a learning cycle or learning loop. Below are collections of questions from the conversation.
- Asking questions
- Answering questions
- Refining questions
- Clarifying questions
- Confirming understanding
Thinking and Applying.
Each moment of interaction in the ChatGPTCONVO provokes thinking and application. The conversation continuously compels learners to reflect and respond and prods ChatGPT to seek patterns from its algorithms and dataset and reply. The conversation leads to learners applying or getting results. This occurs in incremental bits and pieces. The question, response, and refine process is learning iteration.
Emotions and Context-Driven.
ChatGPT engages learners because it asks and responds to the learner’s context. ChatGPT uses stories, metaphors, and real-life events. The questioning, responding, and refining process is learning iteration.
Capture Learning Behavior.
Observe, capture, and articulate the learning. Scientists in the social and behavioral sciences field agree that it is hard to study human behavior because we are part of the study and we tend to be biased. However, by using a little of Machine Learning and ChatGPT algorithm we can observe behavior as expressed in textual words.
Q: What are some of the biggest challenges or limitations you see right now with AI for corporate learning? How can these be overcome?
A: Integrating ChatGPT into learning design opens up new possibilities while also introducing certain challenges. For learners to make the most of it, they need skills in problem-solving, forecasting outcomes, verifying information, and protecting sensitive data.
To ensure these capabilities are used effectively, creating strong security measures is essential. This not only safeguards against risks but also ensures that the use of ChatGPT is both responsible and ethical. A well-informed approach, knowing what’s allowed and what’s not, enhances the AI experience. It encourages critical thinking, builds trust in the information provided, and secures the data involved.
Moreover, using ChatGPT wisely contributes to the development of a knowledgeable and ethical community. However, it’s important to acknowledge the limitations that come with AI, such as the availability and currency of data, and the possibility of mistakes from both machines and humans.
ChatGPT’s ability to produce accurate and relevant content depends on how it’s been trained, so it’s important to interact with it as you would with a specialist in your organization—using clear, contemporary, and conversational language.
In crafting your interactions with ChatGPT, consider that the quality of the output is a reflection of the training it has received. The better the questions and commands you provide, the better the AI can serve your needs, leading to a more effective learning experience and a more intelligent use of technology.
Q: How do you ensure that AI training solutions align with a company’s core competencies and business objectives?
A: Ensuring that AI training solutions align with a company’s core competencies and business objectives involves a strategic approach that incorporates several key elements such as:
Developing private content
AI training solutions should be customized with content that reflects the company’s unique processes, language, and scenarios. This means using the company’s data and examples to develop training materials, which ensures that the learning is directly relevant to the employees’ roles and the company’s core competencies.
Seamless integration
The AI should integrate with the company’s existing technological ecosystem, such as its knowledge bases, project management software, and communication platforms. This helps in creating a cohesive learning environment where employees can see how their training fits into their daily work and the larger company objectives.
Fostering problem-solving skills
The training provided by AI should focus on developing problem-solving skills that are aligned with the company’s strategic challenges. AI can simulate complex, real-world problems that employees can work through, providing a safe space to learn and experiment with different solutions.
Enhancing critical thinking
AI training should also include tools and exercises that enhance critical thinking skills. This could involve scenarios that require employees to analyze data, consider different perspectives, and make decisions based on incomplete or ambiguous information, which are key skills in most business environments.
By focusing on these areas, companies can ensure that their investment in AI training technologies translates into tangible business results and a workforce that is well-equipped to meet the company’s strategic goals.