Use Case Adoption Framework (UCAF)
From Pilots to Population Scale:
Making AI Work for Everyone
As AI is rapidly evolving, the real friction lies not in building technology but in ensuring safe impact and adoption at-scale, beyond early pilots.
People+ai is stewarding the Use Case Adoption Framework to bridge the gaps faced during adoption.
As AI is rapidly evolving, the real friction lies not in building technology but in ensuring safe impact and adoption at-scale, beyond early pilots.
People+ai is stewarding the Use Case Adoption Framework to bridge the gaps faced during adoption.
Read About the Framework
Read About the Framework
Read About the Framework
Read About the Framework
Shalini Kapoor,
Chief Strategist - Data and AI
Shalini Kapoor,
Chief Strategist - Data and AI
Use Case Adoption Framework (UCAF)
From Pilots to Population Scale:
Making AI Work for Everyone
As AI is rapidly evolving, the real friction lies not in building technology but in ensuring safe impact and adoption at-scale, beyond early pilots.
People+ai is stewarding the Use Case Adoption Framework to bridge the gaps faced during adoption.
Read About the Framework
Read About the Framework
Shalini Kapoor,
Chief Strategist - Data and AI
Shalini Kapoor,
Chief Strategist - Data and AI
Together with Our Knowledge Partners
Together with Our Knowledge Partners
UNDP
UNDP
UNDP
GATES FOUNDATION
GATES FOUNDATION
GATES FOUNDATION
CARNEGIE INDIA
CARNEGIE INDIA
CARNEGIE INDIA
ORF INDIA
ORF INDIA
ORF INDIA
Co-created with insights from
25+ organisations across 20+ countries
who consulted with us, this framework represents a shared global construct.
Co-created with insights from
25+ organisations across 20+ countries
who consulted with us, this framework represents a shared global construct.
Shankar Maruwada, CEO, EkStep Foundation presenting the framework at DPI Summit, Cape Town
Keyzom Ngodup Massally, UNDP talking about how scalable AI for Good needs strong building blocks at UNGA Week, New York
Shalini Kapoor, Chief Strategist - Data and AI, EkStep Foundation presenting UCAF at Cape Town Conversation, 2025
Shankar Maruwada, CEO, EkStep Foundation presenting the framework at DPI Summit, Cape Town
Keyzom Ngodup Massally, UNDP talking about how scalable AI for Good needs strong building blocks at UNGA Week, New York
Shalini Kapoor, Chief Strategist - Data and AI, EkStep Foundation presenting UCAF at Cape Town Conversation, 2025
AI Journey Starts at a Use Case
AI Journey Starts at a Use Case
A use case is a real-world, repeatable application of AI that meets a clear user need and delivers measurable societal value. It goes beyond pilots or prototypes by showing how AI improves outcomes for people, systems, or communities in ways that can be sustained and scaled responsibly.
A use case is a real-world, repeatable application of AI that meets a clear user need and delivers measurable societal value. It goes beyond pilots or prototypes by showing how AI improves outcomes for people, systems, or communities in ways that can be sustained and scaled responsibly.
What's Slowing AI Adoption?
What's Slowing AI Adoption?
Everyone is seeking “scale” yet many AI initiatives stall after initial deployment: they may work in a few sites or sandboxes but fail to generalize across states or nationwide.
Everyone is seeking “scale” yet many AI initiatives stall after initial deployment: they may work in a few sites or sandboxes but fail to generalize across states or nationwide.
Availability of in-shore Compute
Availability of in-shore Compute
Limited, costly compute and unreliable energy restrict model training and scaling, keeping many innovations stuck at prototype stage.
Limited, costly compute and unreliable energy restrict model training and scaling, keeping many innovations stuck at prototype stage.
Local Datasets
Local Datasets
Gaps in local language and culturally grounded data make global models unreliable, especially in low-resource contexts.
Gaps in local language and culturally grounded data make global models unreliable, especially in low-resource contexts.
Bias in Current Models
Bias in Current Models
Models inherit systemic biases across sectors, reducing accuracy and trust for underrepresented communities.
Models inherit systemic biases across sectors, reducing accuracy and trust for underrepresented communities.
Unavailability of Population Scale Testing
Unavailability of Population Scale Testing
Pilots rarely scale beyond small user groups due to compute, cost, and infrastructure constraints, delaying real-world validation.
Pilots rarely scale beyond small user groups due to compute, cost, and infrastructure constraints, delaying real-world validation.
Engaging deeply with the larger ecosystem has made one thing clear: the value of an AI use case lives in the Vertical Sectors, but the real-world scale happens with Horizontal Unlocks.
Engaging deeply with the larger ecosystem has made one thing clear: the value of an AI use case lives in the Vertical Sectors, but the real-world scale happens with Horizontal Unlocks.
USE CASES
USE CASES
Verticals
Horizontals
Verticals Create Value
Agriculture
Climate
Law
Healthcare
Livelihoods
Justice
Transportation
Govt. Services
Education
Verticals
Horizontals
Verticals Create Value
Agriculture
Climate
Law
Healthcare
Livelihoods
Justice
Transportation
Govt. Services
Education
Verticals
Horizontals
Verticals Create Value
Agriculture
Climate
Law
Healthcare
Livelihoods
Justice
Transportation
Govt. Services
Education
Introducing UCAF Use Case Adoption Framework
Introducing UCAF Use Case Adoption Framework
The Use Case Adoption Framework maps how AI solutions progress from pilot to scale by linking vertical sectors with horizontal enablers such as data, talent, safety, and interpretability.
It serves as a practical tool to identify bottlenecks, challenges, and pathways to maturity focusing on learning and improvement rather than evaluation.
The Use Case Adoption Framework maps how AI solutions progress from pilot to scale by linking vertical sectors with horizontal enablers such as data, talent, safety, and interpretability.
It serves as a practical tool to identify bottlenecks, challenges, and pathways to maturity focusing on learning and improvement rather than evaluation.
Practical vs. theoretical, comes from our lived experiences.
Practical vs. theoretical, comes from our lived experiences.
Framework is as strong as the Use Cases it has been validated with.
Framework is as strong as the Use Cases it has been validated with.
Outputs of the framework should be useful to to you in your context
Outputs of the framework should be useful to to you in your context
Use Case Adoption Framework in Practice
Migrasia, a Hong Kong based organisation provides technology-enabled support to low-wage migrant workers navigating recruitment, contracts, and rights across major migration corridors. Its platform ‘PoBot’ helps workers identify deceptive practices, understand legal obligations, and access verified assistance channels.
By analysing patterns in cases and grievances, Migrasia also helps governments and partners detect systemic recruitment risks. This improves transparency, protects workers, and strengthens fair migration pathways.
Migrasia, a Hong Kong based organisation provides technology-enabled support to low-wage migrant workers navigating recruitment, contracts, and rights across major migration corridors. Its platform ‘PoBot’ helps workers identify deceptive practices, understand legal obligations, and access verified assistance channels.
By analysing patterns in cases and grievances, Migrasia also helps governments and partners detect systemic recruitment risks. This improves transparency, protects workers, and strengthens fair migration pathways.
Use Case Adoption Framework in Practice
Migrasia, a Hong Kong based organisation provides technology-enabled support to low-wage migrant workers navigating recruitment, contracts, and rights across major migration corridors. Its platform ‘PoBot’ helps workers identify deceptive practices, understand legal obligations, and access verified assistance channels.
By analysing patterns in cases and grievances, Migrasia also helps governments and partners detect systemic recruitment risks. This improves transparency, protects workers, and strengthens fair migration pathways.
This use case operationalizes four horizontal enablers
This use case operationalizes four horizontal enablers
Democratise Data
Democratise Data
AI Safety & Alignment
AI Safety & Alignment
Multilingual AI & Voice
Multilingual AI & Voice
Interpretability
Interpretability
Positioning Global Use Cases Inside the Framework
SET OF INSTRUCTIONS TO VIEW THE MAP:
Scroll to zoom in; drag across to explore the map.
Pointers mark use cases across different countries.
View the map in two modes: Country-wise & Sector-wise.
To learn more, click a pointer. A panel will open on the left side with full details.
Scroll in the panel to read the complete use case information.
SET OF INSTRUCTIONS TO VIEW THE MAP:
Scroll to zoom in; drag across to explore the map.
Pointers mark use cases across different countries.
View the map in two modes: Country-wise & Sector-wise.
To learn more, click a pointer. A panel will open on the left side with full details.
Scroll in the panel to read the complete use case information.
Positioning Global Use Cases
Inside the Framework
SET OF INSTRUCTIONS TO VIEW THE MAP:
Scroll to zoom in; drag across to explore the map.
Pointers mark use cases across different countries.
View the map in two modes: Country-wise & Sector-wise.
To learn more, click a pointer. A panel will open on the left side with full details.
Scroll in the panel to read the complete use case information.
Country - wise Use Cases
Sector - wise Use Cases
Country - wise Use Cases
Sector - wise Use Cases
Country - wise Use Cases
Sector - wise Use Cases
Who is This Framework For?
Who is This Framework For?
Public Institutions
Public Institutions
to spot emerging AI use cases, fix common hurdles, and plan joint action.
to spot emerging AI use cases, fix common hurdles, and plan joint action.
Researchers and Civil society
Researchers and Civil society
to study what works in AI adoption and inform evidence-based policy.
to study what works in AI adoption and inform evidence-based policy.
Philanthropies and Enablers
Philanthropies and Enablers
to fund and support key system gaps like compute, evaluation, and talent.
to fund and support key system gaps like compute, evaluation, and talent.
Tech Developers
Tech Developers
to map data, model, and other dependencies, and align on shared tools or standards.
to map data, model, and other dependencies, and align on shared tools or standards.
Spot Us in Action
Spot Us in Action
Share Your Use Case
Share Your Use Case
If you'd like it to be featured on the Global UCAF Map, please send your details to harshal@peopleplus.ai
If you'd like it to be featured on the Global UCAF Map, please send your details to harshal@peopleplus.ai
From India To The World
Our work is designed around the belief that technology, especially AI, will cause paradigm shifts that can help people reach their potential. Join us in building AI systems that work for billions.
From India To The World
Our work is designed around the belief that technology, especially AI, will cause paradigm shifts that can help people reach their potential. Join us in building AI systems that work for billions.
From India To The World
Our work is designed around the belief that technology, especially AI, will cause paradigm shifts that can help people reach their potential. Join us in building AI systems that work for billions.