Source Alignment Checklist for IR Teams

That makes source alignment more important.

If public sources are inconsistent, outdated, thin, or hard to interpret, AI systems may produce answers that do not fully reflect the company's current narrative.

This checklist can help IR teams identify where the risk of narrative drift may exist.

Confirm the core company description is consistent

Start with the basics.

Does the company describe itself the same way across public sources?

Review:

• •Homepage
• •About page
• •Investor relations page
• •Corporate overview
• •Investor deck
• •Press release boilerplate
• •Conference profile
• •LinkedIn company page
• •Third-party database descriptions

Look for mismatches.

If one source describes the company as early-stage, another as clinical-stage, and another by an older business focus, AI may struggle to determine which description is most current.

The company description should be clear, current, and consistent.

Review how the lead asset or product is explained

For companies with a lead product, platform, therapy, or solution, the explanation needs to be easy to understand.

Ask:

• •Is the product described clearly?
• •Is the mechanism or model explained in plain language?
• •Is the current stage of development accurate?
• •Is the target market or patient population clear?
• •Is the differentiation easy to identify?
• •Are outdated descriptions still appearing on public pages?

AI tools tend to summarize. If the source material is unclear, the summary may become generic.

Check whether recent milestones are visible

Narrative drift often happens when important updates are published but not reflected broadly enough across the company's public footprint.

Review whether recent milestones appear in the right places.

Examples include:

• •Trial progress
• •Financing updates
• •Partnerships
• •Regulatory milestones
• •Leadership changes
• •Product launches
• •Market expansion
• •Strategic repositioning
• •New data or publications

A milestone buried in one press release may not be enough.

If the update changes how the company should be understood, it may need to be reflected across multiple high-value pages.

Identify outdated pages that may still be discoverable

Old content can continue influencing AI-generated answers.

Search for older public pages, PDFs, archived materials, event descriptions, or third-party profiles that may no longer represent the company well.

Look for:

• •Old investor decks
• •Outdated pipeline charts
• •Expired event pages
• •Old product descriptions
• •Legacy boilerplate
• •Past conference abstracts
• •Old executive bios
• •Former company positioning

These sources may still be visible to search engines and AI systems.

They may not need to be deleted, but they should be reviewed for accuracy and context.

Compare how competitors are being framed

AI answers often explain a company in relation to other companies.

That means IR teams should understand not only how their own company is described, but also how the category is being framed.

Ask:

• •Which companies are AI tools naming as competitors?
• •Are those comparisons accurate?
• •Is the company being left out of relevant category answers?
• •Is a competitor being treated as more established because their source material is clearer?
• •Is the company being compared to the wrong class, product type, mechanism, or market?

This helps reveal whether the issue is visibility, categorization, or narrative clarity.

Test the questions investors may actually ask

Do not only test branded queries.

Test the real questions a stakeholder might ask during early research.

Examples include:

• •What does this company do?
• •What should investors know about this company?
• •What are the company's key upcoming milestones?
• •How does this company compare to others in the space?
• •What is the market opportunity?
• •What are the biggest risks?
• •What is differentiated about the lead asset or platform?
• •Who are the competitors?
• •What recent updates matter most?

Save the answers and review them against the company's intended public narrative.

Look for missing context, not just incorrect facts

AI answers are not always obviously wrong.

Sometimes the bigger issue is what they leave out.

Look for missing context around:

• •Timing
• •Differentiation
• •Market need
• •Stage of development
• •Clinical or commercial relevance
• •Recent updates
• •Strategic focus
• •Customer or patient population
• •Category definition

A technically accurate answer can still be incomplete in a way that creates misunderstanding.

Make the strongest sources easier to interpret

Once gaps are identified, strengthen the sources that matter most.

This may include:

• •Updating the homepage
• •Improving the investor relations page
• •Adding a plain-language product explainer
• •Creating a market or disease-state overview
• •Improving FAQs
• •Updating press release boilerplate
• •Aligning investor deck language with website language
• •Adding clear milestone context
• •Creating internal links between related pages

The goal is not to overpublish.

The goal is to make the correct narrative easier to find, understand, and repeat.

Monitor over time

Source alignment is not a one-time project.

AI answers can change as new sources appear, models update, competitors publish, and search results shift.

IR teams should periodically review high-value prompts and track whether the company narrative is improving, weakening, or drifting.

The most important questions are:

• •Is AI using current information?
• •Is the company being described accurately?
• •Are important milestones included?
• •Are comparisons improving?
• •Are outdated assumptions fading?
• •Is the company showing up in the right category conversations?

Final thought

Investor relations has always been about helping the market understand the company.

AI does not change that responsibility.

It changes where the first impression may be formed.

A source alignment review helps IR teams see whether the public record is strong enough for AI systems to interpret the company accurately.

When the sources are aligned, current, and clear, the narrative has a better chance of staying intact.

Related: Read our main article on AI narrative drift to understand how gaps between public information and AI interpretation can affect market perception.