Activity 4

Introduction

Maya’s story, back in Activity 1, asked whether AI was helping her think, or thinking for her. The learner profiles in Activity 2 showed that cognitive diversity means genuinely different needs to cater to, rather than the same need showing up in different forms. Activity 3 gave you a lens for telling support from dependence: does the tool reduce a barrier while the learner still does the thinking, or does it quietly take over the thinking.

This question matters to our Opportunity Forecast because the answer determines what is actually worth building, adopting, or funding in this market. 

What You'll Do

In this activity you will:

• explore emerging AI tutor venture categories, grounded in real products or research, and see what each calibrates to and leaves out

• decide on each one using three investment options: invest, pilot, or reject

• find out what your verdict reveals about the kind of adaptive AI tutoring design you value most

The Emerging Market

• AI-enabled adaptive tutoring that is grounded in educational neuroscience is still a nascent market category. Its target population is substantial and well-documented for ADHD and autism, in the U.S., Canada, and globally. But the full neurodivergent population cannot yet be sized with confidence as profiles overlap, and no reliable estimate exists for dyslexia or twice-exceptional (2e) learners. Select a geographic region below to see which numbers are verified.

• It sits at the intersection of three design philosophies:

Numbered regions in the diagram correspond to the tabulated descriptions 

Population data sources: United States (Danielson et al., 2024; Shaw et al., 2025; Wang et al., 2024), Canada (Public Health Agency of Canada, 2026), and global meta-analyses (Ayano et al., 2023; Issac et al., 2025; Zeidan et al., 2022). No validated estimate exists for dyslexia or twice-exceptional learners in any of these sources.