How to Build a Source-Checked AI Research Workflow

Build a source-checked AI research workflow by defining one narrow question, selecting authorised original sources, asking AI to extract rather than invent, checking each material point against the source and separating evidence from interpretation and decision.

Use a small source register and stop rule. If a source is incomplete, inaccessible, out of scope or unsupported, pause, qualify the wording or leave the point out. A polished summary is not a checked evidence brief until a person reviews the source-to-claim trail.

What is a source-checked AI research workflow?

It is a repeatable sequence from one research question to a small evidence brief. It shows what a source says, what it may mean and what decision can follow.

This is different from asking AI to “research the topic” and accepting a fluent summary. The tool may select weak sources, combine claims or fill a gap. A person remains responsible for source selection and verification.

1. Define one question and a stopping rule

Write a question narrow enough to answer with inspectable material. “What does our market want?” is too broad. “What checks should a marketer apply before using AI-generated website content?” has a clearer boundary.

Add a stopping rule: use two or three original sources, record relevant passages and stop if a material point remains unsupported or conflicting. This prevents an endless collection of links.

Write what is out of scope, such as ranking outcomes, audience demand or legal advice.

2. Select and register original sources

Choose sources that can support the question. Prefer original guidance, standards, studies, policies or first-party documentation. Record enough for another person to reopen the source:

A source register is a control record, not evidence by itself.

3. Ask AI to extract and compare

Give the tool the question and the selected sources. Ask it to quote or paraphrase only what the supplied material supports, preserve source locations and flag gaps. Do not ask it to make the research “complete”.

An instruction might be:

Using only the three sources below, extract the points relevant to the research question.
For every point, include the source name, passage or section, scope and any limitation.
Separate source-supported evidence from interpretation. If the sources disagree or do not answer
the question, write REQUIRES SOURCE or CONFLICT, and do not fill the gap.
Research question: [one narrow question]

The generated table is not a source. Keep originals open.

4. Verify each material point manually

Open the source and check the exact passage. Ask:

• Does the passage support the whole point or only part of it?
• Is the wording stronger than the source?
• Are the date, scope and conditions still relevant?
• Has the answer combined passages?
• Is a number, named source or causal statement present in the original?

Mark each point supported, partly supported, unsupported or requiring a source. If the source is silent, do not let a fluent sentence become an answer. Qualify, source, remove or leave it open.

5. Handle gaps and conflicting sources

Make failure states explicit:

Do not silently pick the convenient result. Record the conflict or gap.

6. Separate evidence, interpretation and decision

The AI-assisted B2B audience research method uses a three-part boundary: evidence, interpretation and content decision. B12 adds source selection and verification first.

Write the evidence as the source's point with its limitation. Write interpretation as a possibility. Then record the decision: use, qualify, investigate or leave out.

This keeps an AI synthesis from becoming a new source.

An illustrative three-source trial

Illustrative teaching example: The question and synthesis below are not a measured result or legal conclusion.

Question: What checks should a marketer apply before using AI-generated website content?

Synthesis: Check accuracy, quality, relevance and added value, keep responsible-use questions visible and verify confident generated output. This is a synthesis across three sources, not a quotation.

Decide when the brief is ready

Before handing over the evidence brief, confirm:

• the question and scope are still visible;
• each material point has a source passage or an explicit gap status;
• source dates, ownership and limitations are recorded;
• conflicts and inaccessible sources are visible;
• interpretation is labelled as interpretation; and
• the final decision identifies what can be used and what still needs review.

If a material point fails, keep the brief in review. Visible gaps are more useful than unsupported detail.

Keep authorisation and privacy visible

Use only sources and notes authorised for the selected tool and purpose. Remove personal data, private customer detail, confidential material, credentials and restricted commercial information unless permitted.

For sensitive questions, involve the appropriate reviewer. A source register records provenance; it does not grant permission.

Your next step

Choose a question. Select two or three authorised sources, record passages and ask AI only to extract, compare and flag gaps.

Open the sources, mark points supported, partial, unsupported or requiring a source, then separate evidence, interpretation and decision. Stop where evidence stops.

Further Reading

• How to Use AI to Organise B2B Audience Research Without Losing Human Judgement
• Google Search Central: Guidance on using generative AI content on your website
• GOV.UK: Data and AI Ethics Framework
• NIST: Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

These sources support narrow points, not a universal workflow.