Benefits
- Benefit
-
Completed 12.2% more tasks, finished 25.1% more quickly
Awaiting review
- Outcome identifiers
-
Unresolved
Not reviewedUnresolved
- Category
-
Reduced Task Time
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
-
GPT-4 (via a ChatGPT-style interface with default system prompt and temperature)
Awaiting review
- Model
-
This is an explicit unresolved assignment: the sources on record do not settle this question.
Not reviewedUnresolved
- Reported configuration
-
GPT-4 as available at the end of April 2023
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
-
Consultants used GPT-4 on tasks that experts had chosen as within its reach. Some consultants also received a short overview of prompt engineering. Human graders scored the quality of the work.
Awaiting review
- Human oversight
-
Unresolved
Not reviewedUnresolved
- Relation to AI
-
Consultants were randomly assigned to work with or without GPT-4, so the differences in output isolate the effect of access to the model.
Awaiting review
- AI contribution
-
Consultants were randomly assigned to work with or without GPT-4, so the differences in output isolate the effect of access to the model.
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
-
Subtasks completed, time to completion and graded quality of outputs. [2]
Fully reviewed: supporting details for Measurement
Review date: 29 October 2026.
Sources: [2]
- Setting and sample
-
758 BCG consultants, two experiments, 18 tasks inside the frontier and one outside. [2]
Fully reviewed: supporting details for Setting and sample
Review date: 29 October 2026.
Sources: [2]
- Measures
-
Tasks completed, speed and quality score. [2]
Fully reviewed: supporting details for Measures
Review date: 29 October 2026.
Sources: [2]
- Comparison
-
Consultants without AI. [2]
Fully reviewed: supporting details for Comparison
Review date: 29 October 2026.
Sources: [2]
- Results
-
12.2% more tasks, 25.1% faster, more than 40% higher quality inside the frontier; 19 points lower correctness outside it. [2]
Fully reviewed: supporting details for Results
Review date: 29 October 2026.
Sources: [2]
- Additional value from AI
-
Gains of 43% for below-average and 17% for above-average consultants. [2]
Fully reviewed: supporting details for Additional value from AI
Review date: 29 October 2026.
Sources: [2]
- Limitations
-
Designed tasks; one firm; one model version; BCG co-authors; lower correctness on the task outside the frontier. [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. Operator: Boston Consulting Group, with the Harvard Business School Digital Data Design Institute research team.Awaiting review
- Jurisdictions
-
Benefit: Boston Consulting Group offices (the sources do not list countries). 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
-
The task must lie within what the model can do well. Workers must check output on tasks where the model is weak.
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-0665-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: 2. Organizations: Not assessed.
Awaiting review
- Reasons
-
People: Consultants below the average baseline score raised their task performance by 43%, and those above it by 17%. Organizations: The tasks were designed for the experiment, and the sources report no realized outcome for Boston Consulting Group as a firm.
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 randomized experiment. [1]
Fully reviewed: supporting details for Kind
Review date: 29 October 2026.
Sources: [1]
- Related entries
-
Both cases concern a consulting firm that uses a large language model to produce client work, where errors in the output fall on the firm.
Fully reviewed: supporting details for Related entries
Compared with the incidents in the AI Incident Database snapshot of 26 October 2026; a second reading confirmed that the incident concerns the same kind of system and stakeholder.
Sources: incidentdatabase.ai
- Field
-
Management consulting.
Awaiting review
- Purpose
-
OpenAI built GPT-4 as a general-purpose language model. The experiment tested its use on consulting tasks.
Awaiting review
- Dates
-
Source published: 22 September 2023. Updated: 29 October 2026.
Awaiting review
- Stage
-
The system was used in a pilot. The model was provided for an experiment on designed tasks. [1]
Fully reviewed: supporting details for Stage
Review date: 29 October 2026.
Sources: [1]
- Version
-
SHA-256: c38b2d53e6f5…
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
-
AI Incident Database: 1193.
Awaiting review
- Category mappings
-
Unresolved
Not reviewedUnresolved
- Citable summary
-
Unresolved
Not reviewedUnresolved
- Revisions
-
3 revisions. Latest: 29 October 2026.
Awaiting review
Sources
-
Peer-reviewed study Deployer
Dell'Acqua F, McFowland E III, Mollick E, Lifshitz H, Kellogg KC, Rajendran S, Krayer L, Candelon F, Lakhani KR. Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality. Organization Science. 2026;37(2):403-423. doi:10.1287/orsc.2025.21838 (publisher abstract as deposited with Crossref).
subjects using AI outperformed those not using AI, completing 12.2% more tasks and completing them 25.1% more quickly on average while also delivering solutions of significantly improved quality
-
Preprint Deployer
Consultants across the skills distribution benefited significantly from having AI augmentation, with those below the average performance threshold increasing by 43% and those above increasing by 17% compared to their own scores.