Where NGOs Can Use Robo Claw and How to Choose Rollout Candidates
We recommend evaluating candidate use cases on impact on beneficiaries, donors and volunteers; whether AI makes support, grant or safety decisions; presence of personal or sensitive information; presence of information about minors, victims or people needing support; impact on donations, grants, remittances or spending; external publication on the web, social media, etc.; external transmission to supporters, donors or beneficiaries; and ability to require human approval, escalation, and stop/correction/rollback, as well as feasibility of operation with small teams across multiple sites — and prioritizing low-risk use cases centered on reading, classification and drafting, where a human makes the final check.
When NGOs and nonprofits choose Robo Claw rollout candidates, prioritize use cases where (1) impact on beneficiaries, donors and volunteers is small, (2) AI does not make the final decision on support, grants or safety, (3) handling of personal or sensitive information is well organized, (4) external publication or transmission can be made approval-gated, (5) human approval, escalation, and stop/correction/rollback can be preserved, and (6) continuous operation is possible even with small teams across multiple sites. The more a use case satisfies these, the easier it is to validate impact during the Pilot, and the lower the risk.
Who This Is For
Who This Is For
This is written for executive directors, heads of communications, fundraising leads, and field program managers who are considering which use case to start Robo Claw adoption with.
What You'll Decide
What You'll Decide in This Step
In this Discover step, you identify candidate use cases for Robo Claw, prioritize them based on impact on beneficiaries and donors and risk, and decide on the first program, region, language, and channel to start with. Detailed design of requirements, permissions, and division of responsibility happens in the next Refine step.
Fit Check
Good Fit / Not a Good Fit
Good Fit
- High-frequency, well-defined-procedure tasks such as initial classification of inquiries or aggregation of activity reports
- Information-organizing tasks a human can easily check and revise, such as drafting replies or draft reports
- Communications tasks such as drafting social media or newsletter copy, where a human makes the final call and publishes
- Tasks that do not directly affect distribution or benefits to beneficiaries, and where transmission can be made approval-gated
- Tasks where input data is internal activity records or KPI data, making confidentiality easy to control
Not a Good Fit
- The final decision itself on accepting or rejecting beneficiaries, granting or paying out benefits, or emergency or safety judgments
- Tasks involving medical, welfare, or legal judgment, or finalizing donations, spending, or remittances
- Tasks that automate, without approval, the external sharing of supporter or beneficiary information or the publication of official positions
- Tasks where rules for handling personal or sensitive information have not been organized
Industry Challenges
Challenges Specific to NGOs and Nonprofits
At the stage of choosing a use case, many NGOs and nonprofits face the following challenges.
Too many candidate use cases to narrow down
Candidates range across inquiry handling, communications, report writing, multilingual support, and more, making it hard to judge where to start.
No standard for judging risk level
There is no mechanism for evaluating each use case's risk level against a consistent standard, so selection tends to depend on individual judgment.
Unclear whether personal or sensitive information can be handled
You must judge, without specialized expertise, how to classify and whether you may use data involving beneficiaries or donors.
Unsure how to handle use cases involving external publication or transmission
There is no standard for judging whether posting to a website or sending to supporters should be in scope.
Method
Implementation Steps
1. Inventory candidate use cases
Take stock of in-house work such as inquiry handling, report writing, multilingual communication, and social media posting.
2. Assess impact on beneficiaries and donors
Check whether the candidate use case affects beneficiaries' rights or donors' interests.
3. Confirm who makes the final decision
Check that the design does not have AI making the final decision on beneficiary acceptance, grant approval, safety judgment, or similar matters.
4. Check for personal or sensitive information
Check whether the candidate use case involves information about minors, victims, or people needing support.
5. Check impact on donations, grants, remittances, and spending
Check whether the candidate use case affects the disbursement of donations or grants, or remittances.
6. Check for external publication or transmission
Check whether publication on the web, social media, etc., or transmission to supporters, donors, or beneficiaries occurs.
7. Check for finalization processing
Check whether the task involves writing to systems or finalization processing, such as support decisions or grant confirmations.
8. Check for human approval, escalation, and stop/correction/rollback
Work out how much human approval can be preserved over outputs, and whether the design allows correction, stopping, or rollback when an error occurs.
9. Check feasibility with small teams and multiple sites
Check whether the use case can be operated continuously given a limited staff and site structure.
10. Decide on priority
Tabulate the evaluation results and decide on the first program, region, language, and channel to start with.
Evaluation Table
Use Case Evaluation Table
Below is a sample evaluation table. Replace it with your own organization's candidate use cases. The smaller the impact on beneficiaries and donors, and the less the final decision is made by AI, the higher the Discover priority.
| Candidate Use Case | Impact on Beneficiaries | Final Decision | Personal/Sensitive Info | External Publication/Transmission | Human Approval |
|---|---|---|---|---|---|
| Initial classification of inquiries | None | Not applicable | Handled in a limited way | None | Recommended |
| Drafting email/chat replies | Indirect | Human | May be handled | Assumes transmission to supporters | Required |
| Summarizing activity reports | None | Not applicable | Handled in a limited way | None | Recommended |
| Draft social media/newsletter posts | Indirect | Human | Handled in a limited way | Assumes external publication | Required |
| Organizing information for grant reports | Indirect | Program manager | Handled in a limited way | Assumes submission to grant provider | Required |
Data & Systems
Data and Systems Used
In the Discover step, you check the status of the following data and systems in order to evaluate candidate use cases.
Human-in-the-loop
Where Human Approval Is Required
No implementation happens at the Discover step, but when evaluating candidate use cases, organize the work on the premise that a human, program manager, safety officer, or specialist always makes the following decisions.
- The final decision on whether a use case may be selected as an automation candidate
- Whether to include a use case that handles personal or sensitive information among the candidates
- Confirming that beneficiary acceptance, grant approval, or safety judgment has not been delegated to AI
- Prior confirmation with the program manager, safety officer, and privacy officer
Measurement
Candidate KPIs
In the Discover step, record the following as hypotheses for each candidate use case, to be used as material for validation in later steps.
Current handling effort
An estimate of the human effort currently spent on the candidate use case
Impact hypothesis
A hypothesis about the effort/time expected to be reduced if automated
Risk score
A risk assessment calculated from impact on beneficiaries, the final decision, data classification, and similar factors
Pitfalls
Common Pitfalls
Choosing only use cases with visible impact
Skipping risk assessment and choosing only use cases with visible impact causes redesign of permissions and division of responsibility in later stages.
Deferring the data classification check
Deciding on candidate use cases before checking how personal or sensitive information is handled causes rework in later steps.
Starting multiple regions or languages at once
Proceeding with multiple regions and languages in parallel from the start complicates permission design and Pilot evaluation, and prolongs validation.
FAQ
Frequently Asked Questions
How many use cases is it appropriate to start with?
In most cases, we recommend starting with one program, one region, one language, and one channel. Proceeding with multiple at once complicates permission design and Pilot evaluation.
Should use cases that handle personal or sensitive information be excluded from candidates?
They do not necessarily need to be excluded. However, this is premised on confirming data classification, purpose of use, consent, and permissions, and designing so that a human or program manager makes the final decision.
Can drafting replies for supporters be a candidate?
Drafting a candidate reply can be a candidate, but the actual sending must always go through human approval by design.
Who should evaluate candidate use cases?
We recommend that the responsible manager for communications/programs and the privacy officer and safety officer conduct the evaluation jointly. Both actual work conditions and risk need to be reflected in the evaluation.
Continue
Previous and Next Steps
Once the use case is decided, next you specify its requirements, permissions, and division of responsibility.
Would you like to organize your use case selection together?
Taking your current workload, risk, and data classification into account, you can discuss Robo Claw application candidates and priority on the official LP.