Benefits
- Benefit
-
Raised solution quality by 0.37 SD and spent 16.4% less time
Awaiting review
- Outcome identifiers
-
Unresolved
Not reviewedUnresolved
- Category
-
Increased Creativity
Awaiting review
- Status
-
Reported benefit
Awaiting review
- Beneficiary groups
-
People. Organizations.
Awaiting review
- Beneficiaries
-
Unresolved
Not reviewedUnresolved
- Reach
-
Unresolved
Not reviewedUnresolved
- Distribution and access
-
Unresolved
Not reviewedUnresolved
- Duration
-
Unresolved
Not reviewedUnresolved
- Expected?
-
Yes
Awaiting review
- Costs and harms
-
Unresolved
Not reviewedUnresolved
AI system
- System
-
GenAI tool built on GPT-4 (GPT-4o for the July workshop), accessed through Microsoft Azure
Awaiting review
- Model
-
This is an explicit unresolved assignment: the sources on record do not settle this question.
Not reviewedUnresolved
- Reported configuration
-
GPT-4; GPT-4o in the July 2024 sessions
Awaiting review
- Provider
-
Unresolved
Not reviewedUnresolved
- Role
-
Unresolved
Not reviewedUnresolved
- Configuration
-
Unresolved
Not reviewedUnresolved
- Inputs and outputs
-
Unresolved
Not reviewedUnresolved
- Autonomy
-
Unresolved
Not reviewedUnresolved
- Workflow
-
Professionals worked on real product challenges in the company's standard process. Those with AI received one hour of training in prompting the tool.
Awaiting review
- Human oversight
-
Unresolved
Not reviewedUnresolved
- Relation to AI
-
Professionals were randomly assigned to work with or without AI and alone or in teams, so the differences isolate the effect of AI access.
Awaiting review
- AI contribution
-
Professionals were randomly assigned to work with or without AI and alone or in teams, so the differences isolate the effect of AI access.
Awaiting review
Measurement
- Studies
-
Randomized. [2]
Fully reviewed: supporting details for Studies
Review date: 29 October 2026.
Sources: [2]
- Study design
-
Randomized. [2]
Fully reviewed: supporting details for Study design
Review date: 29 October 2026.
Sources: [2]
- Measurement
-
Blinded expert quality scores, time on task, self-reported emotions. [2]
Fully reviewed: supporting details for Measurement
Review date: 29 October 2026.
Sources: [2]
- Setting and sample
-
776 P&G professionals in R&D and commercial roles. [2]
Fully reviewed: supporting details for Setting and sample
Review date: 29 October 2026.
Sources: [2]
- Measures
-
Standardized solution quality. [2]
Fully reviewed: supporting details for Measures
Review date: 29 October 2026.
Sources: [2]
- Comparison
-
Individuals without AI. [2]
Fully reviewed: supporting details for Comparison
Review date: 29 October 2026.
Sources: [2]
- Results
-
0.37 SD (individuals with AI), 0.39 SD (teams with AI), 0.24 SD (teams without AI). [2]
Fully reviewed: supporting details for Results
Review date: 29 October 2026.
Sources: [2]
- Additional value from AI
-
AI let individuals match teams. [2]
Fully reviewed: supporting details for Additional value from AI
Review date: 29 October 2026.
Sources: [2]
- Limitations
-
One-day workshop tasks; quality judged as proposals; P&G funding and co-authors. [2]
Fully reviewed: supporting details for Limitations
Review date: 29 October 2026.
Sources: [2]
Money
- Kind of value
-
The kind of monetary value is unclear.
Not reviewedUnresolved
- Amount
-
The monetary value is not established.
Not reviewedUnresolved
- Currency and prices
-
The currency and price basis are unclear.
Not reviewedUnresolved
- Period and unit
-
The period and unit of the monetary estimate are unclear.
Not reviewedUnresolved
- Realization
-
Whether the monetary value was realized is unclear.
Not reviewedUnresolved
- Recipients and payers
-
The recipients and payers are unclear.
Not reviewedUnresolved
- Gross or net
-
Whether the monetary figure includes costs is unclear.
Not reviewedUnresolved
- Included costs
-
The costs included in the estimate are unclear.
Not reviewedUnresolved
- Comparison
-
The financial comparison is not established.
Not reviewedUnresolved
- Method
-
The method used to calculate monetary value is unclear.
Not reviewedUnresolved
- Return and payback
-
The return on investment or payback period is not established.
Not reviewedUnresolved
People and places
- Participants
-
Developer:
OpenAI (model), accessed through 
Microsoft Azure. Operator: Procter & Gamble, with the Harvard Business School Digital Data Design Institute.Awaiting review
- Jurisdictions
-
Benefit: Procter & Gamble (the sources do not name the sites). Developer:
United States. Operator: United States.Awaiting review
- Ownership and control
-
Unresolved
Not reviewedUnresolved
- Dependencies
-
Unresolved
Not reviewedUnresolved
- Cross-border connections
-
Unresolved
Not reviewedUnresolved
- Geopolitical implications
-
The geopolitical implications are unclear.
Not reviewedUnresolved
Follow-up
- Conditions for replication
-
Tasks must benefit from mixed technical and commercial knowledge that the model can supply. Experts must judge the quality of the proposals.
Awaiting review
- Replication attempts
-
1 follow-up entry. Benefit recurred: 1.
Awaiting review
- Later findings
-
Unresolved
Not reviewedUnresolved
- Availability
-
Unresolved
Not reviewedUnresolved
- Institutional decision
-
A relevant institutional decision has not been established.
Not reviewedUnresolved
- Grounds
-
The grounds for an institutional decision are unclear.
Not reviewedUnresolved
- Action and result
-
The result of an institutional decision is not established.
Not reviewedUnresolved
- Success criterion
-
The criterion for a successful institutional decision is unclear.
Not reviewedUnresolved
Evidence
- Source numbers
-
AIBD-0671-source-0001–0002
Awaiting review
- Citations
-
Numbered references below.
Awaiting review
- Language
-
Unresolved
Not reviewedUnresolved
- Source relationships
-
Operator
Awaiting review
- Original evidence
-
Unresolved
Not reviewedUnresolved
- Access and versions
-
Unresolved
Not reviewedUnresolved
- Supported findings
-
Unresolved
Not reviewedUnresolved
- Evidence links
-
Unresolved
Not reviewedUnresolved
- Evidence strength
-
The deployer's account. Sources: the deployer's peer-reviewed study and the deployer's preprint. The cited evidence includes no independent source and no finding by a regulator or court. [1] [2]
- Missing evidence
-
Unresolved
Not reviewedUnresolved
Grades
- Assessed benefits
-
People. Organizations.
Awaiting review
- Depth
-
People: 1. Organizations: 2.
Awaiting review
- Reasons
-
People: Professionals with AI spent 16.4% less time and reported more positive emotions. Organizations: Individuals with AI produced solutions rated 0.37 SD higher, on par with teams without AI.
Awaiting review
- Observed or intended
-
Unresolved
Not reviewedUnresolved
- Rubric
-
Unresolved
Not reviewedUnresolved
- Assessor and date
-
Unresolved
Not reviewedUnresolved
- Alternative assessments
-
Unresolved
Not reviewedUnresolved
- Fill
-
The deployer's account
Awaiting review
Entry details
- Kind
-
The case describes an evaluation or a study. A preregistered field experiment. [1]
Fully reviewed: supporting details for Kind
Review date: 29 October 2026.
Sources: [1]
- Related entries
-
No incident in the AI Incident Database snapshot of 26 October 2026 concerns the same kind of system harming the same kind of stakeholder.
Partly reviewedUnresolved: supporting details for Related entries
Compared with the incidents in the AI Incident Database snapshot of 26 October 2026.
- Field
-
Consumer goods product development.
Awaiting review
- Purpose
-
The tool was a general GPT-4 assistant configured for the experiment. Better and faster product development work was the purpose that the experiment tested.
Awaiting review
- Dates
-
Source information as of: July 2024. Updated: 29 October 2026.
Awaiting review
- Stage
-
The system was used in a pilot. The tool was provided in workshops within an experiment and upskilling program. [1]
Fully reviewed: supporting details for Stage
Review date: 29 October 2026.
Sources: [1]
- Version
-
SHA-256: 142efe1afe49…
Awaiting review: supporting details for Version
SHA-256 of the public case, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.
References
- Other identifiers
-
Unresolved
Not reviewedUnresolved
- Category mappings
-
Unresolved
Not reviewedUnresolved
- Citable summary
-
Unresolved
Not reviewedUnresolved
- Revisions
-
1 revision. Latest: 29 October 2026.
Awaiting review
Sources
-
Peer-reviewed study Deployer
Dell'Acqua F, Ayoubi C, Lifshitz H, Sadun R, Mollick E, Mollick L, Han Y, Goldman J, Nair H, Taub S, Lakhani KR. The Cybernetic Teammate: A Field Experiment on Generative AI and Teamwork. Organization Science. 2026;37(4):1217-1242. doi:10.1287/orsc.2025.20702 (publisher abstract as deposited with Crossref).
individuals with AI matched the performance of teams without AI, suggesting that AI can effectively replicate certain benefits of human collaboration
-
Preprint Deployer
Dell'Acqua F, Ayoubi C, Lifshitz H, Sadun R, Mollick E, Mollick L, Han Y, Goldman J, Nair H, Taub S, Lakhani K. The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise. NBER Working Paper 33641, April 2025.
individuals with AI demonstrate a 0.37 standard deviation increase (p < 0.01), while teams with AI show a 0.39 standard deviation improvement (p < 0.01)