Stakeholder mapping AI cheatsheet

Explain the difference between context-based materiality and double materiality. How should I apply context-based materiality to my work in [SECTOR] in [REGION]?

Include:
- Key planetary boundaries relevant to my sector
- Social foundations I should consider
- How this differs from traditional materiality assessment
- [Request confidence rating and alternatives]

I work in [SECTOR] in [REGION]. What are the key planetary boundaries relevant to my work? For each boundary, explain:
- Current global status (safe, uncertain, transgressed)
- How my sector impacts this boundary
- Thresholds I should track to stay within safe limits
[Request confidence rating and alternatives]

Using the Doughnut Economics framework, what are the critical social foundations (human rights, equity, access) relevant to [SECTOR] in [REGION]? Prioritise the top 5 based on:
- Severity of current shortfalls in the region
- Direct influence of my organisation’s work
- Stakeholder priorities
[Request confidence rating and alternatives]

My organisation [BRIEF DESCRIPTION OF ACTIVITIES]. Using a context-based materiality lens:
1. What are our most material impacts on planetary boundaries? (e.g., climate, biodiversity, water)
2. What are our most material impacts on social foundations? (e.g., equity, livelihoods, health)
3. Which impacts are absolute (exceeding thresholds) vs relative (improving efficiency)?
4. Rank these by severity and urgency.
[Request alternatives for ranking criteria]

For [SPECIFIC IMPACT AREA, e.g., carbon emissions], help me design threshold-based indicators:
- What is the absolute threshold I should aim for? (e.g., science-based targets, regional limits)
- How do I measure progress towards this threshold?
- What proxies can I use if direct measurement is infeasible?
- What are the risks of using proxies vs direct measurement?
[Request confidence rating on threshold data]

Explain the 5 key drivers of effective impact management:
1. Intentionality (beyond harm reduction)
2. Systemic Perspective (beyond linear logic)
3. Stakeholder-Centricity (beyond tokenism)
4. Adaptive Learning (beyond static plans)
5. Transparency (beyond selective reporting)

For each driver, provide:
- Why it matters
- Common mistakes organisations make
- How to implement practically
[Request confidence rating and examples]

My organisation [BRIEF DESCRIPTION]. Using the 5 impact management drivers, assess where we’re strong and where we have gaps:
- Rate each driver (1-5 scale)
- Explain reasoning for each rating
- Suggest 2-3 concrete actions to strengthen weak areas
- Prioritise based on feasibility and impact
[Request alternatives for prioritisation]

I’m working on [PROJECT/PROGRAMME DESCRIPTION]. Help me identify all potential stakeholders across these categories:
- Participants (who is the work meant for?)
- Indirectly involved (who feels it indirectly?)
- Affected parties (who feels the change, intended or not?)
- Influencers (who shapes opinions, policies, or funding?)
- Implementers (who delivers the work?)
- Funders/investors (who provides resources?)
- Regulators (who sets the rules?)

For each category, list 3-5 specific groups. Flag any I might be overlooking.
[Request confidence rating on completeness]

For the following stakeholders [LIST], map them onto a Power/Interest grid:
- High Power / High Interest: Key Players (active engagement required)
- High Power / Low Interest: Keep Satisfied (monitor and inform)
- Low Power / High Interest: Keep Informed (regular updates)
- Low Power / Low Interest: Monitor (minimal effort)

Explain the reasoning for each placement. What assumptions am I making about their power and interest?
[Request alternatives for stakeholders on the borderline]

Using the Salience Model, categorise these stakeholders [LIST]:
- Definitive (Power + Legitimacy + Urgency): Top priority
- Dominant (Power + Legitimacy): Important, but less urgent
- Dangerous (Power + Urgency): High risk if ignored
- Dependent (Legitimacy + Urgency): Morally important, but low power
- Demanding (Urgency only): Noisy but not critical
- Dormant (Power only): Latent threat/opportunity
- Discretionary (Legitimacy only): Optional engagement

For each stakeholder, explain which attributes they have and why.
[Request confidence rating and examples of engagement strategies]

Create a dependency matrix for my project [BRIEF DESCRIPTION]:
- Who depends on us? (e.g., participants, partners)
- Who do we depend on? (e.g., funders, regulators, suppliers)
- Mutual dependencies (e.g., co-creators, strategic partners)

For each dependency, assess:
- Strength (weak/moderate/strong)
- Risk if relationship fails
- Opportunity if relationship strengthens
[Request alternatives for managing high-risk dependencies]

My project [BRIEF DESCRIPTION] generates this data [LIST KEY METRICS/OUTCOMES]. Help me identify narrative themes that:
- Connect data to human experiences
- Resonate with [TARGET AUDIENCE, e.g., donors, community members, policymakers]
- Highlight systemic insights, not just individual success stories
- Avoid oversimplification or ‘hero narratives’

Suggest 3-5 themes with examples of how to tell each story.
[Request alternatives for different audiences]

I have strong quantitative data [DESCRIBE] but struggle to make it compelling. Suggest:
- How to frame numbers as human stories without being manipulative
- What qualitative data would complement the numbers
- How to show causality vs correlation honestly
- Examples of organisations doing this well
[Request confidence rating on causal claims]

Review this impact story [PASTE DRAFT]. Identify:
- Any ‘saviour’ or ‘hero’ framing (we fixed them)
- Tokenistic representation (participants as passive recipients)
- Oversimplification of complex problems
- Missing stakeholder voices

Suggest revisions that:
- Centre stakeholder agency and voice
- Acknowledge complexity and trade-offs
- Show collaboration, not charity
[Request examples of re-framed narratives]

For each stakeholder group [LIST], recommend the best communication channels:
- Annual reports (formal, data-heavy)
- Websites (accessible, SEO-optimised)
- Videos (emotional, human-centred)
- Social media (frequent, conversational)
- In-person events (high-touch, participatory)
- Email newsletters (regular, relationship-building)

For each recommendation, explain why this channel fits this stakeholder’s preferences and information needs.
[Request alternatives for stakeholders with limited digital access]

Create a 6-month communication plan for [PROJECT]:
- Primary message: [CORE NARRATIVE]
- Audiences: [LIST]
- Goals: [e.g., awareness, funding, behaviour change]

For each month, suggest:
- Which channels to use
- Content types (story, data, infographic, case study)
- Frequency of engagement
- Metrics to track success
[Request alternatives for low-budget scenarios]

We discovered [DISAPPOINTING FINDING, e.g., programme had no impact, unintended harm occurred]. Should we:
1. Report it fully and transparently?
2. Bury it and focus on the results that look good?
3. Report selectively (mention but downplay)?

For each option, explain:
- Ethical implications
- Reputational risks
- Impact on stakeholder trust
- Long-term consequences

Recommend a course of action with reasoning.
[Request alternatives for different stakeholder audiences]

Using the Radical Candour framework (Care Personally + Challenge Directly), help me communicate [DIFFICULT MESSAGE, e.g., programme underperformance, funding shortfall] to [STAKEHOLDER GROUP].

Draft a message that:
- Shows empathy and care for their interests
- States the problem directly without sugar-coating
- Explains what we’re doing about it
- Invites collaboration on solutions

Avoid:
- Ruinous empathy (caring but not honest)
- Obnoxious aggression (honest but uncaring)
- Manipulative insincerity (neither caring nor honest)
[Request confidence rating on tone]

Review our impact claims [PASTE]. Identify:
- Overstated impact (claiming too much credit)
- Cherry-picked data (showing only what looks good)
- Vague metrics (unmeasurable or unverifiable)
- Attribution errors (confusing correlation with causation)

Suggest revisions that:
- Use precise, verifiable language
- Acknowledge limitations and disappointing findings
- Distinguish contribution from attribution
- Cite sources and methods
[Request examples of transparent impact reporting]

[ANY IMPACT MANAGEMENT QUESTION]. Please include:
- Confidence rating (1-5): How certain are you about this recommendation?
- Accuracy rating (1-5): How tailored is this to my specific context?
- Reasoning: Why these ratings?
- Alternatives: What other approaches exist with different trade-offs?

You recommended [SUGGESTION] with [Confidence: X/5 | Accuracy: Y/5]. Help me calibrate:
- What would increase confidence to 5/5? (more data? precedent? validation?)
- What would increase accuracy to 5/5? (more context from me?)
- What are the risks if I follow this at current confidence/accuracy levels?
- How can I test or validate this recommendation before full commitment?
[Request alternatives for low-confidence scenarios]

Explain how I should interpret these confidence levels in decision-making:
- [Confidence: 1/5] Speculative: When is it okay to act on low-confidence advice?
- [Confidence: 3/5] Reasonable Certainty: What validation should I do?
- [Confidence: 5/5] Extremely Confident: Can I fully trust this, or should I still verify?

Provide examples of decisions at each confidence level and appropriate next steps.

For stakeholder group [NAME], design a 6-month engagement plan:
- Objectives: What do we want to achieve with them?
- Tactics: What activities/touchpoints? (meetings, surveys, co-design workshops)
- Frequency: How often should we engage?
- Depth: Surface consultation or deep co-creation?
- Risks: What could go wrong? (engagement fatigue, tokenism, power imbalances)

Prioritise tactics by feasibility and impact.
[Request alternatives for resource-constrained scenarios]

Review our engagement plan [PASTE]. Identify signs of tokenism:
- Stakeholders consulted after decisions are made
- No genuine influence over outcomes
- Extractive data collection (we take, they don’t benefit)
- No feedback loop (we don’t report back)

Suggest revisions that:
- Involve stakeholders earlier (co-design, not just validation)
- Share power (voting rights, veto power, co-governance)
- Reciprocate value (what do they gain from participating?)
[Request examples of authentic participation]

You recommended [AI OUTPUT]. Help me validate this by:
- Identifying assumptions I should verify
- Suggesting which experts/sources to consult
- Listing potential blind spots or biases in the recommendation
- Recommending tests or pilots before full implementation
[Request confidence rating on validation methods]

Compare [OUR APPROACH] to best practices in [SECTOR/FRAMEWORK, e.g., GRI, IRIS+, SDGs]. Identify:
- Where we align
- Where we diverge (and whether that’s justified)
- Gaps or missing elements
- Opportunities to strengthen alignment without losing authenticity
[Request alternatives if full alignment is infeasible]

I need to develop a Theory of Change for [PROJECT DESCRIPTION]. Please:
- Recommend whether ToC, Logic Model, or Impact Value Chain is best for my context
- Include confidence/accuracy ratings
- Provide 2-3 alternatives with pros/cons
- Explain assumptions you’re making about my resources, timeline, stakeholders
- Suggest next steps with clear rationale

Help me map stakeholders for [PROJECT]. Please:
- Suggest the best model (Power/Interest, Salience, Dependency, Onion)
- Provide confidence/accuracy ratings for your suggestion
- Identify which stakeholders I’m likely overlooking
- Recommend engagement strategies for top 5 priority stakeholders
- Flag risks of tokenism or power imbalances

I need indicators for [IMPACT AREA, e.g., education outcomes]. Please:
- Suggest 5-7 indicators (mix of output, outcome, impact)
- Rank by feasibility (cost, data availability, measurement complexity)
- Include confidence/accuracy ratings for each
- Provide alternatives for low-resource contexts
- Explain trade-offs (precision vs practicality)