10 ways AI can support learning and skills resilience (or not) 

10 ways AI support tools should be used

• Prompt learners with challenging questions that develop skills identified by the World Economic Forum Core Skills 2030 framework
• Enable feedback on 2030 course skills, such as adaptive leadership
• Provide scaffolding for human–AI collaboration techniques
• Encourage metacognitive reflection about core skills development
• Generate diverse challenges to stimulate original creative thinking
• Present complex scenarios requiring critical evaluation and improvement
• Support the iterative development of 2030 course skills
• Help educators track progress on core and emerging skills
• Enhance the development of future-relevant competencies
• Focus learning on skills that humans will need in an AI-integrated world

10 ways they should not be used

• Provide complete solutions for creative thinking or analytical reasoning tasks
• Replace human judgment in developing uniquely human capabilities
• Automate the creative or analytical processes learners need to develop
• Make learning decisions that bypass the necessary cognitive struggle
• Create final products that demonstrate creative or analytical thinking
• Mask limitations when learners need to develop technological literacy
• Allow learners to bypass developing future-essential human skills
• Automate assessment of uniquely human capabilities
• Replace learning experiences that build competitive human advantages
• Develop capabilities that are better handled by AI systems

Finding the right balance: the 75/25 principle

Equipping future talent with core cognitive and creative skills means continuing to focus on traditional teaching methods, which should represent 75% of what goes on in the classroom. The 75/25 principle also applies to executive development. Traditional techniques include:

• Discussions that build critical thinking.
• Hands-on activities that develop resilience.
• Peer collaboration that enhances social influence.
• Independent research that cultivates curiosity and lifelong learning.

AI integration should be used strategically to support future-relevant skills development through:

• Immediate feedback on specific aspects of creative or analytical work.
• Scaffolding for developing human-AI collaboration capabilities.
• Metacognitive exercises that build self-awareness about skills development.
• Diagnostic tools that identify gaps in core competencies.
• Practice environments for technological literacy and AI fluency.