Appreciative inquiry — Organizational Development

Appreciative inquiry (AI), developed by David Cooperrider and Suresh Srivastva, is a strengths-based approach to change. Its premise: organizations move in the direction of what they persistently study, so studying problems produces more problem-focus, while studying what works when the organization is at its best produces more of that.

Evidence: Weak to mixed. The published evidence is largely case studies written by advocates, with few controlled comparisons against problem-focused approaches. Partial indirect support comes from solution-focused practice, from research on positive affect broadening cognition, and from the fact that studying successes generates more actionable specifics than studying failures. The suppression-of-the-negative criticism is substantive and should be stated whenever the method is used.

Use when: the organization is exhausted by problem-focused change; when there is real existing excellence to build on; when energy and hope are the missing ingredients rather than analysis.

Do not use when: there is a serious failure requiring root cause analysis; when harm is occurring; when the approach would suppress legitimate grievances. AI used to avoid a real problem is dishonest, and participants will name it as such.

The 4-D cycle

Discovery — "What gives life here?" Paired appreciative interviews in which people tell stories of peak experiences: a time they felt most alive, effective, and proud in this organization. The interview is the intervention; the stories carry the data.
Dream — "What might be?" Amplify the best of what is into an image of the future. Often expressed creatively — a headline from five years hence, a scene, a presentation — because propositional statements flatten the energy.
Design — "What should be?" Craft provocative propositions — statements of the ideal, written in the present tense, grounded in real examples from Discovery, and stretching beyond current practice.
Destiny (originally Delivery) — "What will be?" Self-organized action. People commit to what they will do, individually and in groups. No master plan, no central allocation.

A fifth, Define, is often prepended: choosing the affirmative topic. This choice determines everything downstream and deserves real care.

The affirmative topic choice

The single most consequential decision. Topics are stated as what you want more of, not as the problem inverted.

Not "reduce staff turnover" → "what makes people build a career here"
Not "fix handover failures" → "handovers that leave the next team fully equipped"
Not "reduce incidents" → "how we catch problems early"

The reframe is not a euphemism. It changes what people can remember and therefore what data the interviews produce.

The core principles

Constructionist: words create worlds; the language a group uses shapes what it can do.
Simultaneity: inquiry is intervention. The first question changes the system.
Poetic: an organization is an open book; you can choose which chapter to study.
Anticipatory: the image of the future guides current behavior.
Positive: positive affect and social bonding sustain change effort.

The AI summit

A large-group form: 100–1000 people, three to four days, running the full 4-D cycle with the whole system in the room — including customers, patients, suppliers, and partners. Enables enterprise-wide commitments in days rather than months, and is expensive to run badly.

Examples by audience

Health care: an AI approach to patient experience interviews staff and patients about the times care felt genuinely excellent, then designs to reproduce those conditions. Clinicians who are exhausted by incident reviews often engage with this when they will not engage with another improvement program. Balance it with real safety work; do not substitute.
Software: "tell me about the last time deploying felt effortless" produces more actionable design input than "what's wrong with our pipeline", because people describe concrete conditions rather than generalized frustration. This is the bright-spots move. See switch-framework.
Executive: valuable in merger integration, where problem-focused integration planning entrenches "us and them". Studying both organizations at their best creates a shared vocabulary neither side owns.

Criticisms

Suppression of the negative. The most serious charge. Participants with genuine grievances can experience AI as enforced positivity, and facilitators can use "stay appreciative" to silence dissent. Skilled practice makes room for difficulty inside an appreciative frame; unskilled practice does not.
Power blindness. Appreciation does not neutralize hierarchy; senior people's stories still dominate.
Evidence base is largely case-study based, and largely written by advocates.
Energy generated in Dream can dissipate if Destiny lacks resourcing and accountability.