Artificial intelligence (AI) is appearing in all corners of museums. Staff are using it to create marketing content, dreamp up social media strategies, generate descriptive images, organize collections, andChan engage their member base, and observe how visitors move through galleries. These new mechanics are starting to support curators and educators in ways that make everyday work more manageable and streamlined.
Recent research on human-centric AI shows that museums are exploring these possibilities with intention, ethics, and their audience in mind. Rather than blindly following trends, institutions are folding AI into existing practices, asking how it can improve daily tasks and strengthen their work with the public. What we see is careful progress and a growing sense of what’s possible.
At Cuseum, we examined the latest research on human-centric AI. What we found is a field full of optimism, but still looking for the best ways in which to incorporate this tech into its already functioning systems.
The Reality: What AI Is and Isn’t in Museums
Since 2021 (and even earlier), AI has appeared in a growing number of operational functions and roles of museums. Teams have started using AI to supercharge some interesting innovations like: cataloging artworks, detecting patterns in visitor movement, and monitoring the condition of fragile pieces. In some institutions, AI has even suggested new ways to present stories or help staff answer questions more quickly.
Rather than relying on one size fits all solutions, museums are choosing the AI tools that make sense for their own collections and communities. This thoughtful approach creates space for creative projects and prepares institutions to adapt as technology continues to evolve.
Museum leaders are consistently pointing out a fundamental truth: AI is not about replacing people, but rather, AI should be here to support our teams and free-up more bandwidth for critical, high-level tasks.
In a recent article in “Museum Management and Curatorship,” one digital education specialist admits that “[AI] is a fascinating development, but it can be tricky to implement.” Others see AI as a “helping hand” for translation, accessibility, or making collections more searchable, but no one is clamoring to surrender the curatorial vision to an algorithm.
What is happening? Let's get to the bottom of this:
For several years now institutions have piloted AI for image recognition, sentiment analysis, and visitor flow optimization: “practical, limited-scope tools that can enhance what we already do, not upend it”.
The biggest headline use cases? Automated transcriptions, multilingual audio guides, and personalized content recommendations.
Many teams still rely on expensive software development projects, external partners, agencies, and design studios for anything more advanced than a basic chatbot or a basic analytics dashboard.
AI is incredibly affordable, accessible, and gives small museums new super powers... as compared to needing to hire expensive consults, firms, etc. to achieve similar results. AI is being built and marketed in many forms, and a growing number of accessible tools are beginning to catch the attention of institutions of all sizes - whether on a free plan of ChatGPT or a paid subscription to Claude by Anthropic. As options continue to expand, there is a sense of optimism that more museums will find the right fit for their needs, regardless of their size or resources.
Attitudes: Optimism Meets Expectations
When asked about AI, many museum professionals express a mix of curiosity and anticipation. Concerns about the impact on workforce or bias sometimes appear, especially with so much dramatic coverage in the media. Yet for many, the real questions are rooted in purpose. They want to make sure new technology supports the heart of their mission and preserves what makes museums unique. This ongoing conversation is shaping a thoughtful path forward, as teams look for ways AI can help without losing sight of their values.
As one Museum Professional put it:
“A good, already knowledgeable curator could use AI to augment their knowledge, bring new ideas, frame stuff in different ways and use AI to do a lot of the grunt work.” — Mike Ellis, Director of consultancy Thirty8 Digital, speaking in Museums Journal about AI’s potential in museums.)
Several recurring themes came up in our review of the field:
AI can increase access (translation, content, discoverability, wayfinding) and make certain operations more efficient, but most museums don't want AI to define visitor experience or take curatorial control.
Staff take into consideration ethical challenges—privacy, bias, data misuse, and the risk of eroding public trust.
There’s some concerns that AI could “distract” from core experiences, overcomplicate simple pleasures, or create barriers between visitors and the art itself:
Recent Stats & Findings on AI Adoption in Museums / Cultural Institutions (2025-ish)
Let’s ground this in numbers:
72% of respondents for a recent study said their museums are actively discussing possible AI uses. 33% said they are using AI daily. 40% are still exploring potential vs seeing concrete benefit.
Out of 19 prominent museums in Europe, 42% have adopted AI in some operations.
A study conducted this year introduced a model combining reinforcement learning, computer vision, and affective computing to optimize exhibition layouts. The optimized layout improved spatial flow by 18.1%, reduced congestion, increased exhibit visit rates by ~50%.
In a study of museum practitioners: • ~14.6% saw AI as having a multifaceted positive impact; • ~87% of participants believed AI applications could enhance accessibility and appeal to diverse audiences.
The projected global market for AI-generated museum tour guides: USD ~$412 million in 2024. Expected CAGR ~18.7% from 2025–2033, reaching ~USD $2.15 billion by 2033.
AI is a highly promising utility but we also don’t expect it to do everything. And in a sector built on trust, educational value, and slow thinking, that opinion might be a superpower
Why Human-Centric AI (Still) Matters
What does human-centric mean in practice?
In short: every step toward automation, optimization, or AI-powered convenience must be filtered through the museum’s core values and the visitor’s needs.
AI is useful when it helps real people, staff or public, access collections, find meaning, or participate in the life of the institution. But it can not produce impactful results when it solely chases novelty. As Graham Black, senior curator of the Nottingham Castle Museum and others have argued, museums are “bastions of reliable knowledge” in a chaotic information landscape. Losing that title is not an option.
The good news? Most practitioners agree. Human oversight, ethical frameworks, and transparency are at the heart of every serious AI conversation in museums. These tools are only as valuable as the mission they serve.
What Comes Next: Laying the Foundations
So, where does this leave us? Not necessarily in a sci-fi future, but in a landscape of methodical, considered, incremental experimentation.
AI is a supportive tool, not a replacement.
Visitor-centered design, ethical oversight, and human curation are a good starting point.
Pilot programs are popular, but full-scale deployments will probably be employed at larger scale in the future.
This is a sector with its eyes open: willing to experiment, but determined to keep people at the center of the story.
In the next article, we’ll move from the big picture to the practical: Six Principles Every Museum Should Use for Visitor-Focused AI. We’ll break down how human-centric frameworks (like the HC-AIM) can turn cautious optimism into real value, without losing what makes your institution unique.