Guiding AI for Learning, Development, and Sustainable Performance

AI, used well, is a scaffold — something that supports capability, then steps back as mastery grows. It fills the initially blank page with something that can be shaped. It gets you around writer’s block. It narrows the gap between the best and the rest for tasks with codified input and verifiable output (e.g., software coding). It accelerates the performance of the best for tasks with tacit knowledge input and non-verifiable output (e.g., strategy formulation)

Three questions matter to help guide your choices.

First, do you use it as a tool or as a crutch? When AI completes tasks that people should be learning to do themselves, it hollows out capability over time. Organizations must ask: is this application accelerating development, or replacing it? The answer should shape every deployment decision. Remember: a fool with a tool is still a fool.

Second, do you let it work without reflection? Speed is seductive. But sustainable performance depends on individuals understanding why something works, not just that it works. Moments of reflection — a prompt to review AI output critically, a team conversation about what the AI got wrong — can convert efficiency into learning. Remember: it doesn’t matter how fast you climb a mountain if it is the wrong mountain.

Third, do you lead with intent? Most organizations govern AI reactively, through policy and prohibition. Try instead to clearly articulate what you are trying to develop in people and work backward to ask how AI can serve that goal. Strategy precedes tooling. Remember: culture eats strategy for breakfast.

The deeper question behind AI adoption is not technological — it is developmental, and connected to a foundational mindset: are you afraid or are you curious?

Organizations that keep humans at the center of their AI strategy will perform better; they will learn faster, they will adapt more readily, and they will remain resilient when the technology inevitably changes again. The organizations that will benefit most from AI are not those that deploy it fastest, but those that deploy it most thoughtfully.

Institute Reflection: AI as a Scaffold for Learning

At the Institute for Sustainable Human Performance, this perspective highlights an important shift in how organizations approach AI: its greatest value may lie not in doing the work for people, but in helping them learn, think, and grow.

Research increasingly supports the distinction between using AI as a tool and using it as a crutch. Fang and Feng (2026) found that people tend to use generative AI in two very different ways. Some rely on it too heavily, accepting answers without questioning or modifying them. Others use it as a thinking partner—carefully checking the information, selecting what is useful, and improving their own ideas based on AI suggestions. The study shows that people are less likely to become dependent on AI when they feel capable, have freedom in how they use it, and remain genuinely interested in learning.

This idea is reinforced by broader research on AI and learning. In a review of 84 studies, Banihashem et al. (2025) found that AI is increasingly used to provide personalized support, feedback, and intelligent tutoring. However, most applications focus on improving knowledge and problem-solving, while much less attention is given to encouraging curiosity, confidence, and the habits that help people become lifelong learners.

The contributor's recommendation to "lead with intent" reflects an important lesson for organizations. Rather than starting with the latest AI tool, leaders may benefit from first asking what they want people to learn and how AI can support that goal. Recent research also suggests that relying too heavily on generative AI can reduce critical evaluation, especially when people trust AI more than their own judgment (Lee et al., 2025). Pausing to question, verify, and reflect, therefore, remains essential.

From our perspective, AI should be treated as a scaffold for learning: something that provides support while people build their own capabilities, not something that replaces thinking altogether. The organizations that will benefit most from AI are those that use it to strengthen the qualities technology cannot replace—curiosity, independent judgment, critical thinking, and the willingness to keep learning as work continues to evolve.

References:

• Banihashem, S. K., Bond, M., Bergdahl, N., Khosravi, H., & Noroozi, O. (2025). A systematic mapping review at the intersection of artificial intelligence and self-regulated learning. International Journal of Educational Technology in Higher Education.

• Fang, X., & Feng, J. (2026). Research on the application behavior of generative artificial intelligence learning of college students based on self-determination theory. Frontiers in Psychology, 17, Article 1805498.

• Lee, H.-P. H., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.