I HAVE spent many years working in e-commerce, digital transformation, research, training, and artificial intelligence. More recently, homeschooling my grandchildren has allowed me to observe how technology is changing not only the way children find answers but also how we determine whether they genuinely understand them.
This became apparent during an online tutorial session attended by our Grade 7 learner and other homeschool participants last year. When the tutor asked a question, the learners naturally searched online for information. Today, however, a search may immediately display an AI-generated summary before the user even reaches the original sources.
When our learner responded, the tutor noticed that the answer did not sound like the learner’s usual way of speaking and asked whether it was indeed the learner’s own answer.
The concern was valid. Learners should understand and be able to explain any answer they present as their own. At the same time, I wondered whether it was fair to assume that the learner had deliberately chosen to use AI or intended to misrepresent its output. AI-generated answers are now built into the environment in which children search for information. They may encounter AI assistance even when they believe they are simply using a search engine.
This experience reminded me that responsible AI use can no longer be taught merely by telling learners not to copy answers. We must teach them to recognize when AI has shaped the information they receive, verify it against reliable sources, and explain what they understand in their own words.
The same challenge is emerging in organizations. Employees now encounter AI-generated summaries, recommendations, and suggested responses through search engines, office applications, and business platforms. The question is no longer simply whether someone used AI. Leaders must determine whether the person retained understanding, exercised judgment, and remained accountable for the result.
I have found it useful to distinguish between being AI-assisted and becoming AI-dependent.
A person is AI-assisted when the tool helps with brainstorming, exploring possibilities, organizing information, or completing a task more efficiently while the person remains intellectually involved. The tool may make the process faster, but the person can still direct the work, evaluate the result, and decide what should be accepted, rejected, or changed.
AI dependence begins when confidence or capability disappears without the tool. A writer may reasonably use AI to brainstorm or refine a draft. Dependence becomes a concern when the writer feels unable to begin an article, form an argument, or recognize that the generated text does not reflect what they actually believe.
The test is not whether the person can reproduce every AI-assisted output manually. That would disregard the legitimate productivity these tools provide. The better test is whether the person still understands the problem, can evaluate and correct the output, and is willing to take responsibility for it.
As a homeschool guide, I also benefit from AI assistance. Preparing practice tests item by item can take several hours. AI can help me generate initial questions based on the lessons we are studying.
For answer keys, I ask AI for detailed explanations showing how each answer was reached. I then review the questions and explanations against the textbook and curriculum before using them. The material refreshes my own understanding and becomes a conversation tool for discussing the reasoning with the learner.
The AI-generated answer key does not become the teacher. I still need to determine whether the content is accurate, appropriate for the learner’s level, and aligned with what has been taught. More importantly, the learner must still explain how an answer was reached.
This is similar to responsible AI use at work. AI may reduce the time required to prepare a report, analyze information, draft a proposal, or develop training materials. However, the person using it must remain capable of examining the output, relating it to the actual situation, and defending the final recommendation.
Leaders themselves are not exempt from the risk of dependence. They may use AI to summarize reports they have not read, interpret policies they have not examined, or recommend actions based on assumptions they have not questioned. Delegating the preparation of information may be reasonable. Delegating responsibility for judgment is not.
The need for reliable source material also deserves attention. Some homeschooling programs do not require a standard set of textbooks as long as the prescribed curriculum is followed. This may provide flexibility and reduce costs. However, dependence on technology may increase when learners are not provided with a coherent set of curriculum-aligned materials, whether printed or digital.
Without a stable primary resource, families may have to search continuously for explanations, examples, and answers. Search engines and AI-generated summaries can gradually become the learner’s default source of knowledge.
A well-designed textbook, official module, or structured digital curriculum provides sequence, context, and a body of material to which the learner can return. It does not contain every answer and should not be treated as the only legitimate source. Instead, it provides a foundation against which information from AI, search engines, videos, and online articles can be evaluated.
AI may explain a difficult concept in several ways. Search engines may provide more recent information. Videos may make an abstract lesson easier to understand. These resources can enrich learning, but scattered online content and AI-generated answers do not automatically provide the coherence of a carefully developed curriculum.
Organizations face the same danger when employees stop consulting original policies, contracts, operating manuals, research reports, and source data because AI can summarize them.
A summary may be useful, but it is not always an adequate substitute for the source. Important qualifications may disappear, context may be compressed, and an uncertain interpretation may be presented confidently.
An organization can become faster at producing answers while becoming less familiar with the knowledge on which those answers depend. It may appear more productive while becoming less capable underneath. If employees can generate outputs but cannot explain, verify, or correct them, the organization has gained speed while accumulating operational risk.
This changes how leaders should review work. An AI-assisted output should not be accepted merely because it looks complete and professional. Leaders may need to ask what sources were used, what the AI contributed, what the employee verified, what assumptions could change the conclusion, and which parts reflect the employee’s own judgment.
These questions are not intended to catch people using AI. They help preserve understanding and accountability in an environment where AI assistance is becoming increasingly difficult to separate from ordinary digital work.
Homeschooling has taught me that the goal is not to reject technology or force learners to do everything manually. It is to help them benefit from technology without allowing it to replace the knowledge, confidence, and judgment they still need to develop.
The same principle applies to digital leadership.
The next time an AI-assisted report, proposal, or recommendation reaches a leader’s desk, the question should not be limited to whether the output is complete. The leader should also determine whether the person presenting it understands the source material, can explain the reasoning, recognizes the limitations, and is prepared to take responsibility for what happens next.
AI assistance should expand what people are capable of doing. It should not quietly take away their confidence that they can still think, learn, write, and decide for themselves.