Directed AI Research

Directed AI Research

Primary Category: AI Governance & Research Oversight

Secondary Focus: Prompt Governance, Evidence Validation, and Responsible AI Use

Artifact Profile

Directed AI Research is a governance artifact for structuring AI-assisted research around explicit questions, scope, and validation criteria. It ensures that AI is used to accelerate inquiry without drifting into unfocused exploration or unsupported conclusions.

Using defined research questions, constraints, source requirements, and evaluation rules, the artifact channels AI output toward decision-relevant insight. It makes assumptions explicit, limits scope creep, and preserves human judgment over conclusions.

This artifact is built for executives, analysts, educators, researchers, and governance teams who must rely on AI-assisted research while maintaining rigor, traceability, and accountability.

Three Key Questions This Artifact Helps You Answer

• What specific question or decision is this AI research meant to inform?

• What constraints, sources, and validation rules should govern the inquiry?

• How should AI-generated insight be evaluated before it is used or acted upon?

What This Framework Supports

This artifact supports organizations seeking:

- Explicit definition of the question or decision AI-assisted research must inform

- Clear constraints on scope, sources, assumptions, and validation standards

- Reduction of scope creep, hallucination risk, and unsupported conclusions

- Preservation of human judgment and accountability over AI-generated insight

How It Is Used

The artifact provides a structured AI-governance framework that guides executives, analysts, educators, researchers, and governance teams through:

- Defining a decision-aligned research objective before AI engagement

- Establishing scope boundaries, source requirements, and validation rules

- Structuring prompts and outputs around explicit evaluation criteria

- Reviewing AI-generated insight against documented constraints and standards

This enables organizations to accelerate research while maintaining rigor, traceability, and defensible oversight over how AI-generated insight is produced and used.

What This Produces

• A clearly scoped AI research question and objective

• Defined constraints, sources, and validation criteria

• Structured AI outputs aligned to the research purpose

• Governance guidance for evaluating and using results

Common Use Cases

• Structuring AI-assisted market, policy, or academic research

• Preventing scope creep and hallucination in AI research outputs

• Aligning AI research with decision or learning objectives

• Establishing validation rules for AI-generated insight

• Using AI responsibly in regulated or high-stakes contexts

How This Artifact Is Different

Unlike open-ended prompting or exploratory querying, this artifact treats AI research as a governed process. It embeds scope, validation, and accountability into how AI is used—ensuring speed without sacrificing rigor or trust.

Related Framework Areas

This artifact is commonly used alongside other SolveBoard frameworks focused on:

- Decision reliability and evidence validation

- Data lineage and audit traceability

- Risk governance and escalation design

- Strategic research and analytical oversight

Related Terms

AI research governance, directed inquiry, prompt governance, research validation, AI oversight, evidence-based research, responsible AI.

Framework Classification

This artifact is part of the SolveBoard library of structured decision and governance frameworks. It is designed as a repeatable AI-research governance framework rather than open-ended prompting, exploratory querying, or intuition-driven interpretation of model outputs.

Directed AI Research: Structure Targeted Investigation

A governance framework for guiding AI to investigate specific questions using defined scope, sources, and evaluation criteria

Definition

Directed AI Research is a structured framework for using AI to conduct targeted investigation against a clearly defined question, scope, and evidence standard. It forces explicit research objectives, source boundaries, evaluation criteria, and output format. Within SolveBoard, this artifact operationalizes how AI should gather, synthesize, and assess information without drifting into speculation or unfocused exploration.

When to Use

• When you need focused answers to a specific research question

• When sources must be constrained (internal docs, specific domains, or uploaded files)

• When evidence quality and traceability are required

• When outputs must follow a prescribed analytical structure

When Not to Use

• For open-ended exploration or brainstorming

• When source restrictions cannot be defined

• When speculative or creative outputs are desired

Common Mistakes

• Asking broad questions without defining scope or success criteria

• Failing to specify what sources are allowed or excluded

• Accepting synthesized conclusions without reviewing evidence

Purpose of Directed AI Research

The purpose of Directed AI Research is to convert a vague information need into a controlled investigative process. It ensures AI work is aligned to a defined research question, grounded in approved sources, evaluated against explicit criteria, and delivered in a format that supports decision-making, audit, or further analysis.

How to Apply

• Define the primary research question and sub-questions

• Set scope boundaries: topics, time horizon, geographies, and exclusions

• Declare permitted sources (uploaded files, specific sites, internal repositories)

• Specify evaluation criteria (credibility, relevance, recency, bias)

• Require evidence mapping and structured synthesis

Example Scenario

A policy team needs to assess whether a new regulation impacts their operations. Using Directed AI Research, they define the exact regulatory clauses of interest, restrict sources to official government publications and uploaded legal memos, and require a structured output mapping each claim to cited evidence. The result is a defensible research brief suitable for leadership review.

Boundaries

This artifact governs how AI performs research. It does not replace human subject-matter expertise, legal review, or final judgment, but ensures that AI-driven investigation is disciplined, traceable, and aligned to governance standards.

What This Artifact Does

Directs AI to investigate a specific question using defined scope, sources, evaluation criteria, and structured output.

You Provide

(You may provide some, all, or none of the items below. Partial inputs are valid.)

• Primary research question and any sub-questions

• Scope boundaries (topics, time period, geography, exclusions)

• Permitted sources (uploaded files, links, domains, internal docs)

• Evaluation criteria (credibility, relevance, bias, recency)

• Desired output format (brief, matrix, evidence map, summary)

• Written descriptions or pasted text

• Links to reference material or data sources

• Files, PDFs, spreadsheets, images, and other uploads (always acceptable)

• Optional context notes

Core Question

What does the available evidence, within the defined scope and sources, say about this specific research question?

Decision Logic

• If scope is too broad → narrow topics, timeframe, or sources

• If sources conflict → surface discrepancies and assess credibility

• If evidence is insufficient → identify gaps explicitly

What the Output Means

• A structured research output tied to specific evidence

• Explicit identification of assumptions, gaps, and uncertainties

• Traceable linkage between conclusions and sources

Do Not Use When

• You want unconstrained ideation or creative exploration

• You cannot specify allowable sources or scope

• Outputs do not require evidence or traceability

You do not need to complete every section below. Provide only the information you have available or wish to provide. The AI will generate output using only the inputs you supply and will not assume or infer missing information.

Section 1 — Primary Research Question and Sub-Questions

What This Input Represents

The specific question the AI is being directed to investigate and any sub-questions that structure the inquiry.

If You Have Materials, You May Provide (List file names here in your input document):

- Research briefs

- Problem statements

- Policy or decision questions

Guiding Questions:

- What is the exact research question to be answered?

- Are there sub-questions that must be addressed separately?

- What would a useful or decision-ready answer look like?

Section 2 — Scope Boundaries and Exclusions

What This Input Represents

The topics, time horizons, geographies, and domains that define what the AI is allowed and not allowed to consider.

If You Have Materials, You May Provide (List file names here in your input document):

- Scope definitions

- Project charters

- Policy or analytical boundaries

Guiding Questions:

- What topics or domains are in scope?

- What time period or geographic limits apply?

- What should be explicitly excluded from consideration?

Section 3 — Permitted Sources and Evidence Base

What This Input Represents

The documents, files, links, or domains the AI is allowed to use as evidence.

If You Have Materials, You May Provide (List file names here in your input document):

- Uploaded files

- Links or URLs

- Internal repositories

- Approved external domains

Guiding Questions:

- Which sources is the AI permitted to use?

- Are there any sources that must not be used?

- How should conflicts between sources be handled?

Section 4 — Evaluation Criteria and Quality Standards

What This Input Represents

The standards by which evidence should be judged and synthesized.

If You Have Materials, You May Provide (List file names here in your input document):

- Credibility criteria

- Relevance standards

- Bias or recency rules

Guiding Questions:

- How should evidence be evaluated (credibility, relevance, bias, recency)?

- What constitutes sufficient versus insufficient evidence?

- How should gaps or uncertainty be reported?

Section 5 — Required Output Structure and Format

What This Input Represents

The structure and format the AI must use when presenting results.

If You Have Materials, You May Provide (List file names here in your input document):

- Report templates

- Matrices or tables

- Evidence maps or briefs

Guiding Questions:

- What output format is required (brief, matrix, evidence map, summary)?

- What sections must be included in the output?

- How should claims be linked to sources?

Section 6 — Supporting Context, Files, and References

What This Input Represents

Any additional information that may affect interpretation, including organizational context, decision use, risk sensitivity, or how the research output will be applied.

You May Include (List file names here in your input document):

- Policies, memos, or internal guidance

- Spreadsheets, datasets, or analyses

- Images, scans, or annotated documents

- Links to repositories, dashboards, or official publications

- Pasted text or excerpts

Additional Instructions (Optional)

You may add extra instructions to further shape the output, including:

Requesting PDF or other output formats
Limiting page length or response size
Layout preferences (section order, headings, structure, templates)
Specifying tone, style, or format (executive, concise, detailed, formal, etc.)
Output consistency preferences (fixed structure, standardized phrasing, strict formatting)
Prioritization or scoring preferences (how gaps, risks, or actions should be ranked)
Desired mode behavior as outlined in the section below
Any other constraints, rules, or priorities relevant to your use case

If included, the AI will follow these instructions when they do not conflict with the bridge’s execution rules. More specific instructions generally produce more consistent, repeatable, and targeted outputs.

Desired Mode Behavior

Strict Mode

• Maximize determinism and repeatability
• Minimize wording variation, structure changes, and interpretive flexibility
• Do not extend beyond explicit user inputs

Balanced Mode (Default)

• Maintain structure and discipline
• Allow limited analytical judgment where inputs are incomplete
• Do not introduce external assumptions

Exploratory Mode

• Expand hypothesis space and analytical angles
• Surface alternative interpretations and scenario paths
• Still grounded only in user-provided inputs

If no mode is specified, default to Balanced Mode.

What This Enables

Based on your prepared inputs, this artifact directs AI to investigate a narrowly defined question using only approved sources, evaluate evidence against explicit criteria, and produce a structured, traceable research output. The result supports decision-making, audit, and governance by making assumptions, evidence, and uncertainty explicit.

Canonical Input Rule (For All SolveBoard Artifacts)

Documents are optional. Sections may be partially completed or left blank. Structured answers to any subset of guiding questions constitute valid input. The AI will evaluate only provided information and will not infer missing content.

AI Execution Instructions

You are operating in Bridge Execution Mode. Follow these rules exactly. Do not reinterpret, summarize, optimize, or override them. Do not introduce external knowledge, assumptions, or inferred content. Evaluate only user-provided inputs. If required information is missing or ambiguous, flag it rather than guessing. Output must follow the defined Output section exactly.

Users may provide some, all, or none of the input sections. Process only what is explicitly provided. Treat empty sections as intentionally omitted.

Purpose

Apply Directed AI Research to investigate the defined question using only the specified scope, sources, and evaluation criteria.

What This Bridge Answers

What does the approved evidence, within this scope, indicate about the specific research question?

Inputs (All Optional)

• Primary research question and sub-questions

• Scope boundaries and exclusions

• Permitted sources (files, links, domains)

• Evaluation criteria and output format

• Files, PDFs, spreadsheets, images, links, or other uploaded material

• Context notes

Note: Output Quality and specificity scale with input completeness. The user has been informed of this via the input sheet.

Processing Rules

A valid Directed AI Research output must satisfy all of the following:

• Only permitted sources are used and referenced

• Claims are mapped to specific evidence

• Conflicts, gaps, and uncertainties are explicitly identified

• Conclusions are derived strictly from the provided evidence

When inputs are sparse:

• Produce the most complete output possible with available data

• Explicitly flag what's missing and how additional inputs would enhance the analysis

• Do not infer or assume missing information

Execution Steps

• Parse the research question and scope

• Review only the permitted sources and uploaded materials

• Extract relevant evidence and map it to sub-questions

• Evaluate evidence against the defined criteria

• Synthesize findings in the required structured format

Output

• Assumptions and scope boundaries

• Evidence map (claims → sources)

• Structured analysis and conclusions

• Identified gaps, conflicts, and uncertainties

Failure Conditions / Misuse

• Use of sources outside the permitted scope

• Conclusions presented without evidence mapping

• Speculative or generalized claims beyond the defined question

Mode Behavior (From Input Sheet)

Strict Mode

• Maximize determinism and repeatability
• Minimize wording variation, structure changes, and interpretive flexibility
• Do not extend beyond explicit user inputs

Balanced Mode (Default)

• Maintain structure and discipline
• Allow limited analytical judgment where inputs are incomplete
• Do not introduce external assumptions

Exploratory Mode

• Expand hypothesis space and analytical angles
• Surface alternative interpretations and scenario paths
• Still grounded only in user-provided inputs

If no mode is specified, default to Balanced Mode.

Additional Instruction Governance

User-provided additional instructions must be followed exactly unless they conflict with core Bridge Execution Rules. If a conflict exists, Bridge Execution Rules take priority.

Additional instructions may control format, tone, structure, length, or ordering, but must not introduce inferred content, external knowledge, or speculative assumptions.

If instructions are ambiguous, flag ambiguity rather than guessing.

Additional Instructions Execution Rule

If the user provides instructions in the Additional Instructions field, they are binding execution constraints.

Failure to follow them constitutes a Bridge Execution Failure.

Reminder to AI: If a format is requested (e.g., PDF, DOCX), the final output MUST be delivered in that format.

Artifact Instructions

This guide explains what information the Directed AI Research artifact requires and how to prepare your inputs.

How to Prepare Your Input Document (Required Format)

Create a new Word (or similar) document.
Copy all text from the Input Sheet tab into the document.
Save it — this is now your Input Document.
Answer the guiding questions directly in the Input Document and reference any supporting files there.
Save the completed Input Document (Word, PDF, etc.).
Copy all text from the Bridge AI Prompt tab and paste it into the prompt field.
Attach the completed Input Document and any referenced files when submitting the prompt.

No Supporting Files? No Problem.

You can proceed without uploading any supporting documents, spreadsheets, dashboards, reports, or other attachments.

The Input Document is still required, but it may contain only plain-text answers to the guiding questions.

Written responses alone are sufficient for the AI to generate output.

Supporting files, links, and pasted materials are always optional.

Missing Inputs Are OK

You do not need to complete every section.
You do not need supporting files.

The AI will still run. It will:

Use only the inputs you provide
Skip or flag missing sections
Never fail due to incomplete information

Output quality scales with input depth — but execution never breaks.

Submitting Files

If you upload files, list each file name under the relevant “If You Have Materials” section in your Input Document. This ensures each file is clearly tied to its intended use.

What to Expect From This AI Bridge

This bridge generates a structured, high-value starting point, not a guaranteed final deliverable. Output quality improves as inputs become clearer, deeper, and more complete.

This artifact supports iteration. Users are encouraged to refine inputs, test variations, and rerun the bridge to improve results.

The AI organizes complexity and accelerates insight — but final judgment and decisions remain with the user.

In Short

Stronger inputs → stronger outputs
Iteration improves results
Cross-artifact testing can reveal new perspectives
This artifact enables progress, not perfection