AI & Finance

Technical exposure does not establish an economical case for automation Adoption depends on complete costs, complementary skills and organisational scale Demand responses make employment effects conditional rather than automatic

Adaptive tutoring should be assessed through retention and transfer as well as scores Evidence from a bounded trial does not validate an entire school model Human interaction and source quality remain important parts of learning design

Europe's research strengths coexist with limited access to AI infrastructure Compute capacity and the skills to use it must develop together Shared facilities should be assessed by the scientific opportunities they create <

High performance inside a tutoring system may conceal weak transfer outside it Scientific reasoning depends on exceptions, source quality and changes of representation AI tutoring should be evaluated as an epistemic instrument, not only an instructional product