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Exercises/Relationship Mapping/Appreciative Interviews (AI)
Collaborative Story Building · Relationship Mapping

Appreciative Interviews (AI)

Appreciative Interviews (AI) is a collaborative story building exercise for relationship mapping: it helps participants build useful connections and understand how people, roles, or ideas relate.

Under 5 minutesTIME
Medium group (9-25), PairsGROUP SIZE
ActiveENERGY
In person, RemoteSETTING
High cognitive loadCOGNITIVE LOAD
Strengthens Network Design This relationship mapping exercise strengthens Network Design, one of the eight Gathering Effectiveness pillars.

How to run it

  1. In pairs, participants take turns conducting an interview and telling a success story, paying attention to what made the success possible. 7-10 min. each; 15-20 min. total.
  2. In groups of 4, each person retells the story of his or her pair partner. Ask participants to listen for patterns in conditions/assets supporting success and to make note of them. 15 min. for groups of 4.
  3. Collect insights and patterns for the whole group to see on a flip chart. Summarize if needed. 10-15 min.
  4. Ask, “How are we investing in the assets and conditions that foster success?” and “What opportunities do you see to do more?” Use 1-2-4-All to discuss the questions. 10 min.
  5. Above: An Appreciative Interview underway in Peru
  6. Generate constructive energy by starting on a positive note.
  7. Capture and spread tacit knowledge about successful field experience.
  8. Reveal the path for achieving success for an entire group simultaneously
  9. All methods All authors IAF Library Library Appreciative Interviews (AI) 762 326 In less than one hour, a group of any size can generate the list of conditions that are essential for its success.
  10. You can liberate spontaneous momentum and insights for positive change from within the organization as “hidden” success stories are revealed.
Live facilitator

Run this exercise live

The facilitator console stays in this browser. Its QR handoff is a short-lived participant snapshot containing only public exercise instructions, phase, prompt, and timer state.

Prompts to use +

In pairs, participants take turns conducting an interview and telling a success story, paying attention to what made the success possible. 7-10 min. each; 15-20 min. total.

In groups of 4, each person retells the story of his or her pair partner. Ask participants to listen for patterns in conditions/assets supporting success and to make note of them. 15 min. for groups of 4.

Collect insights and patterns for the whole group to see on a flip chart. Summarize if needed. 10-15 min.

Ask, “How are we investing in the assets and conditions that foster success?” and “What opportunities do you see to do more?” Use 1-2-4-All to discuss the questions. 10 min.

Above: An Appreciative Interview underway in Peru

Generate constructive energy by starting on a positive note.

Run this with your AI assistant +

Works with Claude, ChatGPT, Gemini, or your own local model: paste this prompt and your AI will co-facilitate this exercise with you.

Adapt this exercise for my exact room. Exercise: Appreciative Interviews (AI). Readiness: Publishable Draft. Core moves: In pairs, participants take turns conducting an interview and telling a success story, paying attention to what made the success possible. 7-10 min. each; 15-20 min. total.; In groups of 4, each person retells the story of his or her pair partner. Ask participants to listen for patterns in conditions/assets supporting success and to make note of them. 15 min. for groups of 4.; Collect insights and patterns for the whole group to see on a flip chart. Summarize if needed. 10-15 min.; Ask, “How are we investing in the assets and conditions that foster success?” and “What opportunities do you see to do more?” Use 1-2-4-All to discuss the questions. 10 min.. Return a concise facilitator script with timing, wording, safety notes, and remote/in-person adjustments.

Origin unverified

  • Where we observed it: The strongest current observations come from Liberating Structures; aggregators are listed as additional observations, not origin proof. (2 sources observed, including Liberating Structures, SessionLab.)
  • What that means: we track where an exercise has been observed in public sources. We do not claim to know who created it, or how popular it is.
  • No efficacy claims: appearing in this library is not a claim that the exercise is proven effective. Facilitator judgment and context decide whether it works for a given room.
  • Method lineage: this exercise shares its method name with work attributed to David L. Cooperrider and Suresh Srivastva in our people index. That is a name match, not an origin claim.
  • Corrections: if you have evidence of an earlier or more accurate source, read our methodology and trust boundary and tell us.

Pairs well with