Most cultural institutions still think about digital strategy in terms of websites, calendars, and seasonal promotions. However, a recent discovery call with The Durham Museum showed that the real challenge facing museums today isn’t just outdated infrastructure. It’s understanding how people now discover experiences in an AI-driven search environment.
Museums don’t lose visitors to other museums. They lose them to “What should we do this weekend?” prompts, last-minute family plans, and algorithmic recommendations made before a visitor ever types a museum’s name into a browser.
The Durham Museum is a perfect example of this tension.
They’re preparing for a full website rebuild, managing wildly different audiences. This includes LEGO exhibits, summer camps, The Green Book exhibition, and Omaha’s most iconic Christmas experience. That combination makes them representative of a broader challenge facing museums, tourism organizations, and experience-driven brands everywhere.
5 Ways to Improve AI Discovery for Museums
Below are five strategic insights that surfaced during our conversation. These lessons on AI discovery for museums apply not just to The Durham Museum, but to museums, science centers, historic sites, and cultural destinations across the country.
1. Discovery Begins Before Users Ever Reach Your Website With AI Search.
One of the first topics we discussed was AI search visibility.
Traditional SEO assumes a user searches, reviews results, clicks a link, and then evaluates a website. AI-assisted search disrupts that sequence entirely. Large language models increasingly summarize answers before users ever see a list of links.
As I explained during the call, AI tools tend to operate in two phases. First, they look outward, considering external citation sources such as Reddit threads, Wikipedia entries, social signals, or industry-specific publications.
Only after that do they evaluate whether a brand’s own website is structured in a way that satisfies the user’s prompt.
In other words, AI doesn’t start with your homepage. It starts with what the internet is already saying about you.
For a museum, that has major implications. A parent searching for “things to do in Omaha with kids” or “Halloween events this weekend” may never encounter a museum’s brand name. That is, unless it’s already being referenced in the right external conversations.
This is because AI mirrors human behaviour. It scans multiple channels for consensus about your brand and its offerings, before delivering a recommendation. Museums that aren’t visible in those reference ecosystems simply won’t make the cut.
Takeaway: If your museum isn’t showing up in the broader conversation around activities, events, and experiences, AI search will bypass you before visitors ever reach your site.
2. External Citations Matter as Much as Your Website
A key question raised during the call was whether local mom bloggers, event calendars, and community listings actually matter in AI search.
The short answer? Yes. Often more than your own site.
Platforms like Reddit, Wikipedia, and even niche local blogs often serve as trusted reference points for language models. In some cases, if a keyword isn’t overly saturated, even traditional blog posts can become citation sources if they surface prominently for certain queries.
For the Durham Museum and other museums, this is not a weakness. It’s an opportunity. It means your brand visibility can’t be confined to owned channels. More importantly, AI systems use these mentions to determine whether to cite your brand or not.
However, most museums are not deliberate about AI visibility, treating it only as passive PR when it happens instead of developing an intentional digital strategy.
As I explained, “External citations are one of the few things you can influence without touching your website.” Strengthening Wikipedia entries, ensuring consistent event listings, and encouraging authentic community mentions all improve the likelihood that AI systems will surface the museum when users ask experience-based questions.
Takeaway: In AI search, your reputation is assembled elsewhere before visitors ever reach your site. As such, museums must pay as much attention to external visibility as they do to on-site content.
3. Structured Content Beats Volume in Museum SEO and AI Search
One of the most practical insights from the call centered on content structure, especially the role of FAQs.
Museums often struggle with balancing rich educational content with usability. Dense pages can overwhelm visitors, while minimal content limits search visibility. AI search introduces a third requirement known as retrievability.
Historically, SEO rewarded volume. More copy, more keywords, more pages. That led to keyword stuffing, but that era is fading. Search engines and AI models now prioritize contextual clarity. They want to understand what a page is about and whether it can answer a specific question.
FAQs do this exceptionally well.
At Blacksmith, we intentionally place page-specific FAQ sections at the bottom of nearly every major page. Each FAQ set is unique, designed to satisfy different prompts without cluttering the main experience.
With the proper FAQ schema in place, this content becomes highly readable for AI systems while remaining unobtrusive for human visitors.
“You can never have enough FAQs,” I said during the call, “especially when it comes to AI.”
Takeaway: Museums don’t need more content. They need better-structured content that allows you serve humans, SEO, and AI at the same time.
4. Organizing by Internal Departments Breaks Discovery
Late in the conversation, the discussion shifted from AI back to a more foundational issue: site structure.
The Durham Museum team candidly acknowledged a problem many institutions like theirs share. Their website is organized around internal departments rather than visitor intent.
This is a costly digital mistake.
Visitors don’t know your organizational chart. They don’t care which department runs an exhibit, camp, or event. They care about outcomes: What can I do? When can I do it? Is it right for my family?
AI search exacerbates this issue. If a site’s structure reflects internal language not easily understood by an external user, AI systems will struggle to retrieve necessary information from the site, even if that information technically exists.
As I noted during the call, UX and SEO aren’t opposing forces. A website optimized for user journeys is easier for AI to parse because it clearly maps experiences to user needs.
To take advantage of this, museums may need to reorganize their web experience around families, events, education, and seasonal experiences, rather than their internal departments. This guarantees clarity at every level of discovery.
Takeaway: If your site only makes sense to staff, it won’t work for visitors or AI tools. Intent-driven structure is foundational.
5. AI Optimization Is An Ongoing Practice
Perhaps the most important point to emphasize is that there is no fixed rule about how to optimize for AI discovery. Not yet. This is because the space is still evolving. What works today may shift tomorrow as models evolve.
We test our strategies, observe the results, and refine the approach across our own site and our clients’.
Such levels of uncertainty make foundational SEO best practices even more important. This includes clean structure, clear content, strong external signals, and alignment between UX, SEO, and AI considerations.
This is why we often start with focused audits rather than a complete infrastructure overhaul. Testing our approach with a handful of high-impact pages allows us to see what’s working, what isn’t, and where AI optimization can be factored into existing redesign efforts.
For organizations already planning a rebuild, this timing is critical. Retrofitting AI and SEO considerations after launch is far more expensive than integrating them during content rewrites and structural planning.
Takeaway: AI optimization isn’t about hacks. It’s about building clarity, relevance, and adaptability into your digital foundation.
The Opportunity for Museums Is Bigger Than Search
What stood out most in this conversation was the scale of opportunity.
AI search is accelerating the decision-making process. Museums that understand how discovery now works and structure their content, visibility, and experience accordingly will win disproportionate attention.
The institutions that wait will still exist. They’ll just be harder to find.
And in a world where attention is the scarcest resource of all, that’s a risk no mission-driven organization can afford to ignore.
