Participants

1023

Age Groups

18-25

292

26-35

412

36-45

196

46-55

98

55-65

34

65+

9

Gender

Male

292

Female

412

Non-binary

196

65+

9

Countries

64

India

190

Kenya

125

United States

80

China

65

United Kingdom

48

Canada

44

Indonesia

35

Brazil

31

Chile

29

Vietnam

23

Israel

23

Egypt

22

Pakistan

20

South Korea

17

Italy

17

Germany

17

Mexico

16

Philippines

15

Japan

15

Kazakhstan 20

14

France

14

Spain

12

Romania

11

Bangladesh

11

Australia

11

Türkiye

9

Russian Federation

9

Argentina

9

South Africa

8

Morocco

8

Poland

6

Malaysia

6

Malawi

6

Saudi Arabia

5

United Arab Emirates

4

Ireland (Republic)

4

Belgium

4

Ukraine

3

Switzerland

3

Austria 40

3

Algeria

3

Singapore

2

Portugal

2

Norway

2

Netherlands

2

Greece

2

Finland

2

Croatia

2

Syria

1

Sweden

1

Slovakia

1

Saint Vincent & the Grenadines

1

New Zealand

1

Luxembourg

1

Hungary

1

Ghana

1

Denmark

1

Czech Republic

1

Cuba

1

Armenia

1

Angola

1

Andorra

1

Some regions are more optimistic than others that AI will work there

Regional variation in AI optimism is large and does not follow the pattern you might expect. When asked whether AI benefits will reach their region, Sub-Saharan African respondents are by far the most confident, with 80% saying it's likely (Chart 13b). Southeast Asians, South Asians, and North Americans form a middle tier. The most skeptical are Eastern Europeans, Latin Americans, and East Asians. The pattern on whether wealthy-country AI is useful locally (Chart 14) largely mirrors the confidence question. North Americans and Sub-Saharan Africans are the most positive. East Asians and Latin Americans are the most skeptical.

Will AI's economic benefits reach you?

Expectations by region

Overall

1,082

24%

24%

52%

Western Europe

139

33%

29%

38%

Sub-Saharan Africa

144

10%

10%

80%

South Asia

227

18%

27%

55%

Southeast Asia

82

16%

23%

61%

Middle East & N. Africa

80

25

31%

44%

Eastern Europe

53

43%

25%

31%

East Asia

104

21%

38%

41%

Latin America

104

43%

10%

47%

North America

136

25%

24%

51%

Oceania

13

42%

17%

42%

Unlikely

Neutral

Likely

The pattern on whether wealthy-country AI is useful locally (Chart 14) largely mirrors the previous chart. North Americans and Sub-Saharan Africans are the most positive. East Asians and Latin Americans are the most skeptical.

Will AI from wealthy countries work here? (detailed)

C5: "Do you think AI systems developed in wealthy countries will be useful for solving problems in your community?"

Overall

1,082

12%

46%

19%

16%

7%

Western Europe

139

6%

49%

22%

19%

4%

Sub-Saharan Africa

144

27%

42%

11%

13%

7%

South Asia

227

11%

52%

14%

17%

6%

Southeast Asia

82

12%

44%

26%

12%

6%

Middle East & N. Africa

80

11%

41%

28%

12%

8%

Eastern Europe

53

6%

44%

12%

18%

20%

East Asia

104

8%

38%

32%

19%

3%

Latin America

104

12%

35%

14%

24%

15%

18%

North America

136

11%

54%

17%

19%

5%

Oceania

13

0%

58%

25%

8%

8%

Extremely likely

Somewhat likely

Neither

Somewhat unlikely

Extremely unlikely

Sub-Saharan Africa's high optimism across both measures is consistent with their broader AI attitudes: they also show the highest expected AI impact scores across nearly every domain, from healthcare (4.30/5) to education (4.39/5) to leisure (4.07/5; Chart 7). 

This is a surprising result on the surface, since one might expect those furthest from AI's centres of development to be the most sceptical. But Chart 15 offers a plausible explanation: respondents identified specific applications they believe will transfer – business and productivity tools, healthcare, and education – as well as specific barriers that won't, such as cultural relevance, local language support, and understanding of local institutions). The optimism appears to be conditional rather than naive; people are distinguishing between AI's technical capabilities, which they see as portable, and its contextual fit, which they recognise as limited.

How do people expect AI to change things?

Expected AI impact (B4) by region — mean scores (1=much worse, 3=same, 5=much better)

Healthcare

Education

Food & water

Housing &
infrastructure

Safety

Governance

Social
support

Meaningful
work

Environment

Community

Leisure time

Western Europe

139

3.6

3.6

3.1

3.0

3.0

2.6

3.0

2.8

2.9

2.5

3.5

Sub-Saharan Africa

144

4.3

4.4

4.0

4.2

3.9

3.5

3.8

3.8

3.8

3.4

4.1

South Asia

227

4.0

4.1

3.3

3.7

3.3

3.2

3.5

3.4

2.9

3.0

3.6

Southeast Asia

82

3.9

4.0

3.2

3.3

3.1

2.9

3.2

3.0

2.8

3.0

3.6

Middle East & N. Africa

80

3.8

3.8

3.2

3.2

3.4

2.9

3.0

3.0

2.8

2.3

3.5

Eastern Europe

53

3.6

3.4

2.9

3.0

3.4

2.6

3.0

2.5

2.7

2.4

3.2

East Asia

104

3.8

3.8

3.2

3.2

3.3

2.9

3.0

2.8

3.0

2.9

3.5

Latin America

104

4.0

3.7

3.1

3.4

3.4

2.6

3.3

2.7

2.6

2.8

3.5

North America

136

3.7

3.7

3.2

3.1

3.3

3.0

3.1

2.7

3.1

3.0

3.8

Oceania

13

3.9

3.8

3.3

3.2

3.2

3.3

3.3

3.2

3.0

2.9

3.6

Expect worse

Expect better

Sub-Saharan Africa’s comparatively high optimism towards western AI may also reflect lived experience with technologies that leapfrogged legacy infrastructure rather than diffusing gradually through existing systems. In contexts such as Kenya (which accounts for 89% of respondents in this regional sample) innovations such as mobile banking (notably M-Pesa) and off-grid solar microgrids have delivered tangible, everyday benefits without requiring the fixed-line banking networks or centralized power grids, typical of wealthier economies. This recent history of direct, visible gains from externally developed technologies may plausibly shape expectations that advanced AI systems could generate similarly practical and immediate value.

C5: Will AI from wealthy countries help your community?

Keyword-classified themes from open-ended responses (n=1,032, multi-tag per response)

What people think will transfer

Business & productivity

17%

Healthcare & diagnostics

12%

Education & learning

12%

Jobs & employment

8%

Safety & security

3%

Scientific research

2%

Agriculture & food

2%

What people think won't transfer

Local context & culture

11%

Governance & corruption

5%

Affordability & inequality

4%

Infrastructure & access gaps

3%

Data bias

2%

Securing humanity's AI future

© 2026 Windfall Trust. All rights reserved.

Securing humanity's AI future

© 2026 Windfall Trust. All rights reserved.