By Rachel Bastow
Using AI is a lot like hiring an enthusiastic intern. They are quick, helpful and productive. But they are also confident. Sometimes more confident than their experience justifies. If you let them, they start making decisions you should still be making yourself.
That’s the challenge for today’s workplaces.
AI tools are now embedded in everyday work, especially in writing, analysis and communication. They promise speed and efficiency. But they also introduce a quieter risk: the gradual offloading of thinking. As organisations focus on learning in the flow of work, this raises a key question. Are these tools helping people learn, or helping them avoid thinking?
Cognitive Offloading: Useful, Until It Isn’t
Cognitive offloading is not new. People have always used tools to reduce mental effort. Writing a to-do list, setting a reminder or saving a document all offload memory. They free up your brain to focus on more complex tasks.
In these cases, offloading supports thinking.
AI changes this. It does not just store or organise information. It generates it. It drafts emails, writes reports and summarises content. It starts to take on tasks that were once part of thinking itself. That’s where the risk lies. When tools move from supporting thinking to replacing it, the nature of learning changes.
What Happens When We Stop Thinking?
Early research suggests a link between heavy AI use and weaker critical-thinking performance. Critical thinking includes analysing information, evaluating sources and making sound decisions. These are essential workplace skills.
If people rely on AI outputs without questioning them, they bypass these processes. Over time, this can reduce their ability to think critically on their own.
In a workplace that expects continuous learning, that’s a problem.
Learning in the Flow of Work: Opportunity and Risk
Learning in the flow of work means integrating learning into everyday tasks. It makes learning immediate and relevant.
AI fits naturally into this model. It provides support at the moment of need. It can suggest ideas, summarise information and provide feedback.
Used well, this supports learning. AI can prompt thinking and highlight patterns. Used poorly, it replaces thinking. Tasks get done, but little learning happens. The difference comes down to how people use the tool.
Microlearning: Fast, but is it Effective?
Microlearning is designed to be short and focused. It fits into busy workflows and supports immediate needs. AI can generate microlearning content quickly. It can create summaries, quick guides and examples. But faster is not always better.
When learning is too easy to consume, people may engage with it at a surface level. They read it, but don’t question it. They apply it without fully understanding it. Effective learning requires effort. It requires people to think. Organisations need to design microlearning that prompts reflection, not just consumption.
Enhancing the Learner Experience
A strong learner experience is not just about access to content. It is about engagement and retention. AI can personalise learning. It can adapt content and provide targeted support. This can improve relevance. But personalisation alone is not enough.
Learners need to stay mentally active. They need to interpret, question and apply what they see. Simple design choices can help:
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Ask learners to review and improve AI-generated content
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Prompt them to compare different approaches
- Include questions that require justification
These approaches keep the thinking with the learner.
Real-time Insights: What the Data Doesn’t Show
Modern learning systems focus on real-time data. AI can track activity and generate insights. This data is useful. It shows what people are doing. But it does not always show how well they are thinking.
A completed task may look polished, especially if AI helped produce it. But that does not mean the person understood it. Organisations need to look beyond outputs. They need to consider how work is done, not just what is delivered.
Work is now more flexible and less structured. Learning needs to be continuous.
AI supports this by providing on-demand help. It reduces friction and makes information easier to access. But access alone does not create learning. People need to stay engaged in the thinking process. They need to use AI as a tool, not a replacement. Leaders and facilitators play a role here. They can encourage questioning and model critical thinking.
Stay in Control of the Thinking
The goal is not to avoid AI. It is to use it well. Strong performers are selective. They use AI to support their work, but not to replace their thinking. They:
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Use AI to gather and organise information
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Question what it produces
- Take responsibility for decisions
This keeps the cognitive load where it matters.
AI is a powerful tool. But its value depends on how it is used. Learning in the flow of work should strengthen capability, not weaken it. If people stop thinking, learning stops too. The challenge for organisations is clear. Use AI to support work, but design learning so people stay actively engaged in the thinking that matters.
Interested in AI and eLearning?
AITD offers several courses on both AI and eLearning:
AI Essentials for L&D Professionals: Do you want to transform your L&D workflow and enhance learner experiences using Generative AI? In this blended learning course, you’ll learn how to use Generative (Gen) AI for a range of key L&D functions, including skills gap analysis, content creation, personalised learning and feedback. Register now.
eLearning: Foundations: This is Part I of an engaging, social learning suite of courses that provides you with access to learning experiences, activities and a comprehensive knowledge base. Register now. You may also be interested in eLearning: Planning and Design; and eLearning: Production and Delivery.
About the Author: Rachel Bastow
Rachel is the Client Solutions Manager at the Plain English Foundation. As a plain language practitioner and active member of the international plain language community, Rachel believes in the power of plain language to promote equity, accessibility and inclusion. Since joining the team, Rachel has helped hundreds of organisations on their path to clear communication. She has seen first hand the transformative impact of plain language tools for readers, writers and entire organisations and is passionate about sharing that widely. Rachel's appreciation of words began as a young language learner living overseas. Rachel has since lived and taught in five countries and learned as many languages. It was through these experiences that she began to understand the communication challenges people can have and how each writer can play their part in easing the load.
