Students are rarely asked the most important questions: When does this matter? Why does it matter in one context but not another? What changes when conditions shift?

This is an image of a student sitting at a table looking confused. Image generated using ChatGPT (OpenAI), 2026.
Image generated using ChatGPT (OpenAI), 2026.

Instead, they are trained to recall, replicate, and reproduce. Education emphasizes answers over understanding. But context cannot be memorized-it must be constructed. And too often, students are not being asked to construct anything at all.

Experiential Adaptation
The real world does not present problems in neat, labeled formats. It presents ambiguity. Navigating that ambiguity requires experiential adaptation-the ability to adjust in real time, refine understanding through action, and respond dynamically to changing conditions. Yet most education systems are designed to eliminate variability. Inputs, assessments, and expectations are standardized. Students are rewarded not for adapting, but for complying.

Adaptation cannot be developed through static methods like multiple-choice questions or purely simulated AI scenarios. It requires friction-iteration, failure, and recalibration. Learning environments must include experiential elements such as simulations and real-world problem-solving. Without experience, there is no adaptation. Without adaptation, there is no resilience.

Decision-Making
At the same time, students are surrounded by answers but deprived of opportunities to make decisions. Decision-making is not about selecting the correct option from a list. It is about navigating uncertainty, weighing incomplete information, and accepting consequences.

Education rarely teaches consequence. It teaches correctness.

Artificial intelligence amplifies this gap. It delivers outputs that feel authoritative, positioning the student as a passive validator rather than an active thinker. But leadership requires the ability to decide under pressure, often without a clear answer.

Students should be asked: What would you do, and why? What risks are you willing to take? What trade-offs are you making?

Instead, they are asked: What is the right answer?

These are fundamentally different questions.

Curiosity
Curiosity suffers under this model. It is not a personality trait but a discipline-the pursuit of the unknown and the refusal to accept surface-level explanations. Yet education rewards completion over exploration and prioritizes coverage over depth. AI compounds this by collapsing the search process, delivering answers before questions fully form.

As a result, students lose the habit of wondering. Learning becomes transactional. The question shifts from “What is possible?” to “What is required?”

Creativity
Creativity is also misunderstood. It is not expression but synthesis-the ability to connect ideas, see patterns, and generate something new. In an AI-driven world, creativity becomes a key differentiator. Machines recombine knowledge, but humans provide direction and meaning.

Despite this, creativity is treated as secondary. Students are taught to follow frameworks, not challenge them, to execute rather than invent.

This is a headshot of the author Michael N. Daily
Michael N. Daily, APR

The Strategic Failure
The deeper issue is not that competencies like adaptation, decision-making, curiosity, and creativity are absent. It is that they are not treated as outcomes. They are assumed to emerge naturally.

They do not.

These capabilities must be designed for through environments that embrace ambiguity, tolerate failure, and prioritize depth over speed. Educators must act not just as transmitters of knowledge, but as architects of experience.

Most importantly, success must be redefined.

A student who can generate a flawless answer with AI assistance may still struggle with real-world problems that do not resemble a prompt. Producing correct answers is no longer a sufficient measure of capability.

The standard must shift.

The question is no longer whether students can learn. It is whether they can think when learning is automated-adapt when conditions change, decide when no answer is given, remain curious when answers are abundant, and create when everything appears to already exist.

The Closing Reality
Education now sits at an inflection point. It can continue optimizing for efficiency, scalability, and measurable outputs that signal progress but conceal fragility.

Or it can confront a harder challenge: developing human capability in an age where machines have mastered information.

Students are graduating with unprecedented access to knowledge. But access alone is not power. Without context, adaptation, decision-making, curiosity, and creativity, access becomes dependence.

And dependence, no matter how advanced the technology, is not education.

Michael Daily is a graduate of the United States Naval Academy, with additional master’s degrees from the University of Southern California and National University, and is a 1999 graduate of the Defense Information School and retired Marine Corps Colonel, Public Affairs Officer. He is currently Co-Founder and CEO of Communication Metrics, Inc., a Space and Defense Industry Strategic Communications Company, and an instructor in the Rutgers Continuing and Professional Studies Public Relations Certificate program, within the Rutgers School of Communication and Information.

Learn more about the Rutgers Continuing and Professional Studies Public Relations Certificate program.