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AI and Hyper-Personalised Retirement Education

How AI can target each member's Zone of Proximal Development to personalise retirement education, moving beyond the one-size-fits-all approach.

One of the most exciting use cases of AI is the hyper personalisation of learning activities that will be made possible by targeting each individual's Zone of Proximal Development (ZPD), as introduced by Lev Vygotsky.

Thinking about traditional classroom education, historically students would be taken through a syllabus designed to target the ZPD of the average student. This of course meant that many students were left behind since the syllabus was too complex for them. At the same time, there were students at the other end of the spectrum for whom the material was too simple, and therefore their educational experience was also suboptimal.

Zone of Proximal Development applied to retirement education – slide 1
Vygotsky's Zone of Proximal Development applied to member retirement education.
AI hyper-personalised member education framework – slide 2
AI-driven personalisation framework for super fund member engagement.
Retirement literacy targeting individual member needs – slide 3
Moving beyond one-size-fits-all to hyper-personalised retirement literacy.

Extending this analogy to retirement planning, with advancements in technology and data collection, super funds should be thinking about how to assess the retirement literacy of their membership and target their assistance (education, guidance and advice) to each member's ZPD. The current "one size fits all" approach will be deprecated and funds that can develop a consistent member experience across a portfolio of assistance tools will come out on top.