MCN 2026

To commemorate the 250th anniversary of the Unites States, the central @Smithsonian social media team was tasked with creating 250 pieces of content with an emphasis on video. To meet this ambitious goal, they have been building new workflows across internal communications teams to tell stories across 21 museums, research centers, and the National Zoo.  

First, the team expanded beyond social media. The central Office of Public Affairs formed a working group that includes members of the marketing, press, social media, web, and 250 communications teams. Presenters will cover how responsibilities have been divided (and conquered) and how the strategy has been rolled out to garner internal buy-in across the institution.  

How do they tailor content to specific channels and platforms? In a multi-channel strategy where all channels matter, how do they handle internal competition? Who participates in the planning and editing process? How do they measure success? 

By diving into specific video series, presenters will explore these questions and share lessons learned.

In recent years there has been much productive discussion both at MCN and within institutions on AI-generated visual descriptions for accessibility: how to generate descriptions, how good they need to be, and how institutions should oversee their use. Some museums have already successfully released AI-generated descriptions as accessibility text. 

The Met has been treating AI-generated descriptions as something different: not (yet) as a final user-facing product, but as raw search material. With descriptions of what artworks depict, embedded into vector space and indexed alongside traditional metadata, one can build a discovery experience that works not only for experts, but also for the roughly two-thirds of users who arrive at our collection without a specific artwork in mind. Users searching for "year of the horse," "mythical beasts," or "eating food together" can find relevant works for the first time. Users searching in Chinese, Spanish, or any of dozens of languages can now find the same works as users searching in English. Users without art-historical vocabulary find what they are looking for without needing to know an artist's name or an artwork’s title. And yes, the search still works for our experts and researchers who search via fields like accession number.

We will share what we learned shipping this to a production system of The Met’s 550,000 objects used by millions of visitors a year. We will cover the technical pipeline (vision-language models, embeddings, hybrid lexical-and-semantic search), the evaluation problem (with different concerns when descriptions are an input to search rather than user-facing text), the UX work (in many ways more difficult than the engineering), and what our post-launch analytics and user feedback have actually shown. We will be candid about what worked, what surprised us, what still fails, and what we would do differently. We will also share what transfers to other institutions and what is specific to working at this scale.

Many museum digital projects have an accessibility gap. Images go without alt-text not because institutions don't care, but because writing it at scale – across hundreds of objects, for rotating content, with limited staff – is genuinely hard. When Bloomberg Connects introduced AI-generated alt-text into its CMS, the goal was to close that gap. What we learned was something different: that trust in an AI tool isn't primarily about what the AI can do. It's about what the human can still decide.

This session tells that story from both sides of the table.

In a structured 9-institution pilot, we ran 450+ images through the tool and measured every interaction. Every metric outperformed its target. But the most striking result wasn't the acceptance rate or the time savings; it was that 100% of pilot partners reported feeling in control of the final alt-text. That didn't happen by accident. It was the product of specific design choices: a clear visual separation between AI suggestion and human-editable field, an explicit accept or reject step, no auto-population. The design assumed that curatorial judgment was non-negotiable, and partners felt it.

The pilot also surfaced harder questions that design decisions alone couldn't resolve. When the AI consistently omits skin tone in portraits, is that a safe default or an act of erasure? When it recognizes one religious figure and not another, what does that reveal about whose cultural knowledge is encoded in the model? Partners didn't just want to know what the tool could do: 7 out of 9 asked us to document what it wouldn't do, and why. That transparency mattered as much as the output.

By the time of this session, the tool will have been live across Bloomberg Connects' full partner network for 5 months. This panel draws on the controlled pilot findings and the real-world launch data together, giving attendees both the structured experiment and the longitudinal test of whether what worked with 9 institutions holds at scale.

The session is structured as a panel of co-presenters, not a product demo. Each presenter brings a distinct perspective and a specific artifact – a real image, a before-and-after alt-text, a moment where they overrode the AI – to ground their contribution in practice. Attendees will leave with frameworks they can apply to their own AI adoption decisions, not as a question of capability, but as a question of institutional fit, governance, and what trust actually requires.

Session structure:

10 min - Bloomberg Connects platform framing: the accessibility problem and the design hypothesis       

10 min - Wolfsonian-FIU's experience what they expected, what surprised them, anchored in a specific example from their collection

10 min - Baltimore Museum of Art's experience: where the tool held up and where it raised harder questions, anchored in a specific example from their collection

15 min - Group discussion & Q&A: building across all 3 perspectives on trust, control, and what they'd do differently

Meet other MCN attendees with some speed networking! A facilitator will guide attendees through a series of breakout conversations. Share with fellow attendees where you're from, what you're curious about, and more—just be quick!

This case study offers a closer look at this year’s wildly successful short-form Museum Rizzler video series, created by the National Gallery of Art’s social media team. We’ll discuss the right way to lean into a trend, balancing humor and art history, and the logistics of delivering content in a nimble and responsive way. The presentation will also address practical considerations including cross-team collaboration, approvals, production timelines, and risk assessment when participating in fast-moving online conversations. By sharing lessons learned, performance insights, and examples from the series, this session offers a framework for museums seeking to participate authentically in internet culture while maintaining institutional values and audience trust.

The brutal reality in 2026 is that there is scant effort being made in the cultural heritage sector to engage with generative systems outside of being simple consumers. Maybe one of the big vendors will give us discounted rates for a limited time and we can achieve "great things". At the end of the day though few, if any, organizations will be in a position to control their own destiny. Nor will they  have done anything to change the power dynamic of surviving on the benevolence of someone else's handouts. We simply don't have the knowledge, skills or means to deploy these systems and little to no collective work is happening right now to change that.

SFO Museum has been developing a suite of open source tools designed to run on consumer-grade hardware (even old and crusty hardware) for producing, storing, querying and visualizing vector embeddings using as many different open-weight large language models as possible. Specifically we are using vector embeddings to implement image similarity features for collections imagery and other image-based artifacts related to museum programming; to offer avenues of suggestion for investigating our various efforts derived from the properties "seen" by different ML models in the images of those works.

This idea of using vector embeddings to "bridge" different aspects of museum programming – collections imagery, photos posted to social media, exhibition and installation photos - has led SFO Museum to publish our vector embeddings for anyone else to use and to encourage the broader cultural heritage sector to do the same. Cross-institutional collections search continues to be something of a “holy grail” in museums and other cultural heritage institutions. Vector-based image similarity, while imperfect, offers a meaningful first step to finally achieve it. It is a messy, or at least fuzzy, solution and tilts more towards the “discovery and surprise” end of the spectrum rather than informed academic research. While it may not be a tool for scholars and experts, it can still provide meaningful avenues for non-experts to investigate and discover the relationship between different collections. This was still the stuff of fantasy a few years ago and now it is within our reach using nothing more than consumer-grade computer hardware.

This presentation will demonstrate the work SFO Museum has done to date. It will discuss the theory practice and gotchas of the work to date and solicit feedback, criticism and hopefully increased participation from the broader cultural heritage sector. The goal is to demonstrate that we have agency beyond a monthly-recurring fee to third-party vendors.

This session rapidly introduces 15 experimental visitor-facing GenAI prototypes we developed and tested at The Met over the course of six months. These sketches are the product of The Met’s inaugural “Technologist in Residence,” a position focused on quickly and iteratively exploring emerging tech with our visitors. The goal of these past six months was to explore the potential for AI in the on-site experience: what’s working, what’s not, and what questions does this work raise—within the organization, and with our visitors.

Our goal is to move beyond theory and provide a practical library of examples that other museums can use to inform their own AI experiments, and that show what is currently possible with GenAI. We’ll cover novel ideas, tracking nascent visitor AI backlash, small successes and outright failures.

The prototypes cover a wide range of use-cases across the museum experience, including physical navigation, tools for close-looking single artworks, collaborative games, and experiments connecting art to the outside world. For each prototype we will share our most important findings, including what visitors found useful, what they ignored, where the technology failed, and where great ideas are butting up with current technical limitations.

We will end our presentation by taking a step back and sharing our large-scale conclusions, open questions, and next steps towards a sustainable implementation of our findings.

As generative AI and emerging “vibe coding” workflows rapidly lower technical barriers, museum professionals with varying levels of software development expertise can expand experimentation with visual methods of data inquiry using creative coding, data visualization, and interactive storytelling. This session explores how artist-centered technologies—particularly the long-running open-source creative coding platform Processing—can help museums uncover new insights, reveal hidden relationships in collections data, and prototype new forms of public engagement.

Bringing together perspectives from the Georgia O’Keeffe Museum, New Mexico Highlands University, and the Processing Foundation, panelists will discuss how creative coding, open-source tools, and AI-assisted workflows can expand experimentation. Through practical examples and case studies, the session will examine how museums can begin working with these tools, evaluate appropriate technologies and AI models, collaborate effectively with developers, and thoughtfully transition from prototype to production. Panelists will also reflect on how these lowered barriers may expand participation in open-source creative technology communities, enabling a wider range of museum professionals, artists, and educators to experiment, contribute, and shape emerging digital practices. The session will also highlight emerging support structures, including mentorship and grant opportunities from the Processing Foundation, that can help sustain creative coding initiatives over time.

At a moment when trust in digital information systems is increasingly fractured, creative coding offers museums new ways to make interpretation, process, and inquiry more visible. Panelists will explore how these approaches can support long-term relevance and trust by encouraging transparency, experimentation, and broader participation in shaping digital cultural experiences.

For the Minneapolis Institute of Art (Mia), the answer is clear: increase in-person visitation and help the museum reach its goal of one million annual visits. But like many institutions, Mia’s website was not originally designed with that level of strategic specificity. It functioned as a broad information resource—useful, but not intentionally structured to drive visits, guide decisions, or build ongoing relationships with audiences.




In this session, Mia and Forum One share how they are approaching the challenge of rethinking the website’s role as part of a broader, cross-functional system. The work began with detailed end-to-end service blueprinting, mapping visitor journeys across digital and physical touchpoints to understand how marketing, content, staff interactions, and technology systems intersect to shape the experience. This process surfaced critical gaps: moments where interest is generated but not converted, and where no single team owns the full journey.




Building on this foundation, the team is applying a Jobs to Be Done (JTBD) approach to focus on what visitors are actually trying to accomplish—such as planning a visit or discovering events. By defining these jobs, the team can better understand the systems required to support them and identify targeted opportunities to reduce friction and improve outcomes.




The session includes an interactive mapping activity where participants will map a visitor journey and the systems that support it, making visible the cross-functional nature of their own organizations. From this shared view, presenters will introduce a practical approach to identifying small, testable improvements tied to specific moments in the journey.




As institutions develop a clearer understanding of user pathways and patterns, they unlock new opportunities to experiment with growth loops—designing experiences that encourage repeat visits, sharing, and deeper engagement over time. Rather than optimizing for one-time interactions, this approach supports more intentional, repeatable audience growth.




Attendees will leave with a framework for approaching their own work: not as a one-time redesign effort, but as an ongoing, iterative process for improving systems that support real-world outcomes.

Following our previous sessions—One Collection to Rule Them All (MCN 2024) and Future-Proofing through Sustainability and Resilience (MCN 2025)—we return with the third chapter in our evolving story of digital transformation at The Huntington. Framed by this year’s themes of trust and longevity, our session explores not just how an organization grows its technology infrastructure and digital capacity, but also how enduring relationships make that growth possible. Centered on the recently launched My Huntington Portal, we’ll share the realities behind the work: aligning multiple vendors around an ambitious technical roadmap to integrate our CMS with our ticketing/membership, retail, and CRM systems; facing critical business decisions; cultivating stakeholder buy-in; and coordinating across diverse internal teams and priorities. We’ll examine how to ensure that what you build remains sustainable—not only for the organization, but for the people responsible for maintaining and evolving it.

In summer 2025, The Huntington began efforts to create an industry-leading integrated customer portal that would simplify visitor and member account management and power a personalized website experience – including tailored calendar listings and other targeted content based on the unique aspects of the visitor’s customer profile. Our goals were for the portal to drive additional earned revenue through targeted marketing and upsell opportunities, increase engagement and member satisfaction through a carefully designed user experience, and maximize operational efficiency through reliable data workflows. This would be a critical strategic cornerstone to our “One Huntington” ethos and revamped brand message – we need to appear as a unified entity to the public and be gracious hosts online, as we are in person, to build and maintain brand loyalty and satisfaction. 

In this session, The Huntington, Co-Curator, and Cogapp will show how the project moved from strategy into implementation without losing alignment across teams, systems, and priorities. Co-Curator will share how the portal was built inside Shopify Customer Accounts, using a reusable custom application layer shaped through this work and now being adapted for other cultural organizations. Cogapp will show how that member context extends into huntington.org through personalized calendar and content experiences, tighter paths into ticketing, and clearer upgrade opportunities. Rather than focusing only on the finished product, we’ll unpack the architecture decisions, handoffs, and governance patterns that made the work sustainable—and increasingly repeatable—for cultural organizations with different systems, teams, and constraints.

At the heart of our project, and our success, is trust: a client-vendor-collaborator partnership built over time and essential to making complex digital change possible.

Building on a history of metadata innovation, the Mead Art Museum at Amherst College has deepened its commitment to digital accessibility following the launch of a new internal and public-facing online collections database. This initiative centers on a strategic collaboration between the museum and the college’s Academic Technology Services (ATS). Utilizing an investigative workflow involving generative AI models, undergraduate students—under the joint supervision of museum and technology staff—produced descriptive narrations for art and material culture objects.

In their roles as coders, editors, reviewers, researchers, and narrators, undergraduate students refined AI-generated outputs, simultaneously developing critical AI literacy. Their application of "Responsible AI" was guided by a human-centered ethic, requiring rigorous fact-checking, vigilance against algorithmic bias, and the calibration of descriptive style to align with established accessibility guidelines. The preliminary results from this student cohort underscore the necessity of "Human-in-the-Loop" strategies. Furthermore, the project demonstrates that expert museum intervention remains essential to ensuring factual accuracy and maintaining social and cultural sensitivity.

This work-in-progress establishes a model for peer institutions where trust in museum metadata and the transparency of automation tools are integrated directly into the professional workflow. Beyond digital discovery and broadened access, these detailed descriptions serve as a vital institutional archive for inventory purposes and as a resilient analog resource. By providing printed or QR-coded visual descriptions, the museum ensures that objects on display remain accessible to low-vision visitors, bridging the gap between digital innovation and physical gallery experiences.

As museums and cultural institutions explore AI-driven discovery tools, a critical question emerges: how do we design generative experiences that enhance discovery while sustaining institutional trust over time? This session shares early exploratory work from the National Gallery of Art rethinking search through the lens of Generative UI (GenUI), an emerging interaction model where interfaces dynamically adapt, synthesize information, and guide users through more personalized discovery journeys rather than relying solely on static keyword-based search results.

Drawing from ongoing cross-collection search initiatives and AI-assisted prototyping work at the National Gallery of Art, this session will explore how generative search experiences may help visitors navigate complex cultural content, begin searching without knowing exact terminology, and engage with collections through more intuitive and exploratory pathways. At the same time, these systems introduce important questions around transparency, interpretive authority, bias, user expectations, and the long-term stewardship of institutional knowledge.

Through a short case study and examples of generative search concepts and prototypes, the session will examine how UX design and human-centered research can help museums experiment responsibly with emerging AI technologies while maintaining clarity, credibility, and public trust. Rather than presenting a finalized solution, this talk offers a framework for how cultural institutions can thoughtfully evaluate and prototype AI-mediated discovery experiences during a period of rapid technological change.

Visiting an art museum often heavily relies on visual perception. For patrons who are blind or low vision, this dependence significantly impedes their experience. By conveying an artwork’s composition and content through a descriptive textual representation, museums can help close this gap. However, most museum collections are too vast to manually develop descriptions for each object, inspiring the question, “how can AI help streamline the writing process?”

Over the past two years, a collaborative, inter-museum working group of US-based art museums has been exploring using generative AI to provide image descriptions and alt- text for artwork. This session will explore how two of these museums, the Cleveland Museum of Art (CMA) and the National Gallery of Art (NGA), implemented comprehensive workflows to make visual descriptions available online for every primary image in their collections.

This session will dive into the technical, practical, ethical, and conceptual challenges inherent in developing generative AI pipelines in production and sharing this content with the public. We will share key decision points and processes put in place to instill confidence both internally and externally in the generated descriptions and maintain that confidence as new images become available and are described moving forward.

We will discuss in depth our respective approaches for developing infrastructure to develop, test, and integrate the descriptions with internal systems, and the strong collaboration with teams across each museum throughout the process. Emphasizing the importance of thoughtfully and responsibly sharing these descriptions, we will also talk through our final steps for publishing the descriptions for the public and continuing to gather feedback post-production.

Finally, each museum will share their next steps on image descriptions and their broader uses of AI that have developed out of this work, including broader cross-collection discovery efforts and accessible in-gallery experiences.

Museums are among the most trusted institutions in our world, but do our digital interfaces earn or erode that trust? Long-lived digital products such as online collections, educational resources, and online exhibitions represent significant investments and access points for museums. Ensuring that these products are easy and enjoyable to use is central to maintaining public trust and institutional longevity. In other words, trust is a UX issue.

This session explores the origin, structure, and impact of the Smithsonian’s User Experience (UX) Lab, a pan-institutional program designed to embed user research into everyday digital decision-making. Launched by the Office of Digital and Innovation as an internal service offering, the UX Lab partners with museums, libraries, and research units to conduct usability studies that generate actionable findings and build a more user-centered culture across a complex organization. 

The presentation will highlight several UX Lab studies, including one focused on the National Museum of American History’s online collections catalog and related discovery experiences. Attendees will learn how key audiences such as researchers, educators, and history enthusiasts interact with museums online, where their expectations break down, and what that reveals about long-term risks and design opportunities for improving digital collections platforms.

The session concludes with practical takeaways from across the 18 UX Lab studies conducted so far that any museum—regardless of size, budget, or technical maturity—can apply to improve digital experiences and support their mission for the long haul.

Robots, fever dreams, and artworks with escape fantasies: for more than ten years, the Harvard Art Museums have been asking what really happens when we trust AI to look at our art. What began as a practical effort to improve search and discovery by augmenting curatorial descriptions with machine‑generated synthetic metadata has grown into a long‑term experiment in co‑creating knowledge with machines.

Over that time, we’ve processed more than 500,000 images (depicting artworks, archival material, and exhibitions and galleries) and amassed over 120 million synthetic annotations to enrich our collections catalogue. Today, new images entering our systems are automatically queued for processing by a “panel” of commercial services: Amazon Nova and Rekognition, Clarifai, Imagga, Google Gemini and Vision, Microsoft Cognitive Services, OpenAI GPT, Anthropic Claude, Meta Llama, Mistral, Qwen, and others. Together, these models tag features, write descriptions, identify colors, read text, detect faces, and more. Their outputs are compared, combined, and surfaced through our public API (hvrd.art/api) and AI website (ai.harvardartmuseums.org) alongside human‑written cataloguing. This processing is not a temporary experiment, but part of how we work. It’s baked into our data pipeline and designed so that new models can be added over time, recognizing that describing collections is a forever project. Opinions, interpretations, and experiences of art are always in flux, for humans and machines alike.

Along the way, we’ve learned that the real questions are not just about accuracy. What happens when humans and machines look at art together? How much does “accuracy” matter for material that is inherently subjective? How can we embrace the inconsistencies, hallucinations, and disagreements between models (and between models and people) to broaden how collections are described and experienced?

This solo session will share concrete examples from over a decade of practice, including short collective looking exercises where attendees attempt to reconcile their own responses to artworks with those of AIs. We’ll explore how this work has changed our thinking about trust, authorship, and longevity in collections data, and how we are designing systems where AI is a long‑lived, transparent tool in the hands of people, rather than a faceless, monolithic black-box of implied authority.

Over the course of more than a year, a cross-functional team from the Getty including data engineers, catalogers, and frontend developers coordinated remotely with our counterparts at the Rijksmuseum in Amsterdam. The remit was simple: How do we surface the ways our collections connect? Given that our collections are both modeled in linked open data, specifically Linked Art, given that our technical stacks are aligned, and given that both institutions promote open collections often and publicly -- what could we actually do that practically demonstrates our shared commitment to open standards? After months of planning, the collaboration culminated with an in-person, hands-on prototyping session. The point was to explore, focusing on what was lightweight, likely ephemeral, and leveraged existing resources and expertise. 

The process ended up helping us shine a light on core institutional concerns: using shared data models in real-life; authority, branding, and UX issues; organizational differences across institutions; and just how collections ought to live outside our own museum contexts. This talk touches on what we can learn (and unlearn) when we go beyond talking about data models and start building a working app from scratch alongside an unfamiliar team.

Many museums are already doing AI engagement work, including exhibits, programs, community conversations. But what's the full range of what's possible, and how do you know where your institution fits? This session introduces a typology of 13 roles museums can play in AI public engagement, organized across four domains: building AI awareness and knowledge, facilitating public input into AI development, strengthening AI-related infrastructure, and exploring AI's social impact and meaning. Developed by the Association of Science and Technology Centers through a cross-sector workshop process, the framework offers a shared language for a field that is moving fast and often in parallel. Come map where your work already lives, and where you might want to go next.

How does a cultural institution position itself as the definitive educational authority on a historical subject — not just today, but for a new generation to come? The generation that lived through World War II and the Truman presidency — that fought in the Pacific, rationed food on the home front, listened to Truman's voice on the radio, and cast ballots in 1948 — is nearly gone. Within a decade, the living memory of these events will be gone. What remains will be collections, documents, oral histories, photographs, and the digital records and experiences institutions build right now to carry these critical histories forward.

This session presents two history museums navigating that transition in real time: the National World War II Museum and the Truman Library Institute. Both are engaged in long-term digital strategy work explicitly designed to answer the same question from different angles: how do you build digital experiences that preserve the weight and truth of history for audiences who have no personal connection to it and who are growing up in an often-chaotic information environment?

The answer both institutions are working toward is not nostalgia. It is education and storytelling. In both cases, that ambition has produced concrete, purpose-built digital foundations designed to meet the next generation where they are.

At the Truman Library Institute, that means a new web presence which intends to surpass the official federal (.gov) site in depth and usability, also doubling down on credibility at a tenuous moment in history, paired with a quote-based AI-driven chatbot, a tool that allows students and general audiences to engage directly with Truman’s words, decisions, and legacy through a conversational interface grounded entirely in the historical record. 

At the National World War II Museum, that means a sustained investment in purpose-built digital architecture: an authoritative infrastructure designed to establish the Museum as the trusted anchor for WWII education and storytelling online. In an era when students are as likely to encounter AI-generated summaries or algorithmically surfaced partial histories as they are to find rigorous scholarship, the Museum’s digital strategy is oriented toward a clear goal: becoming the place where diverse audiences can reliably find research-driven, editorially vetted, and perspectives-inclusive accounts of World War II’s full scope and complexity.

Both institutions reflect the same underlying conviction: that the best response to a fractured information environment is not to retreat from digital engagement, but to build better, more trustworthy digital experiences and to plan for their longevity. The session will trace how each institution arrived at its approach through deep stakeholder engagement, user research, phased implementation, and a sustained commitment to organizational alignment, and then open the floor for discussion of what this work means for the broader museum field.

This session examines the reimagined ArtLens Gallery from the perspective of project management, using the framework of how we divided our responsibilities for a complex and ambitious undertaking involving multiple partners and collaborators. We divided project management roles between the physical space, the app, and the emphasis on making the experiences more inclusive and accessible to counteract the inaccessibility inherent to an art museum for blind or low vision people, while better supporting visitors with a wide range of sensory, mobility, and cognitive access needs.

We’ll share how we managed: 

- Accessible Exhibition Design: The physical design choices we implemented to make the gallery more accessible to blind or low vision visitors, also enhancing the experience for all.

- Developing a Tactile Interface: How we developed an interactive that uses a tactile reproduction of an artwork as a user interface.

- ArtLens App Rebuild: How we rebuilt the ArtLens app to make it easier for visitors to explore, learn, and connect at the CMA, under a tight, inflexible timeline. Prioritized for accessibility and inclusivity for all users, the new app is built with a unified codebase for both iOS and Android and is strategically integrated within the CMA’s digital ecosystem to leverage the existing app technologies and build on what already works.

- Dissecting the Museum Map: Using this page as a case study, we’ll examine key decisions, challenges, and outcomes, to unpack the complexities of the project and highlight the lessons learned.

- Managing App Integration with the Physical Space: Project management strategies used to align cross-functional teams around a shared docking approach that served as the technical bridge between the app and physical space and the foundation for accessibility affordances. 

- Managing Scope, Tradeoff, and Delivery Impacts: How key decisions, such as physical versus proximity docking, were scoped, evaluated, and implemented within real-world constraints, and how those choices impacted timelines, user flows, and accessibility outcomes. 

- Balancing Vision with Reality: What we’d do differently with additional time or resources and how the project continues to evolve beyond launch.

Unlike previous iterations, the reimagined ArtLens prioritizes inclusive experiences that make art matter. Through an integrated approach that combines physical exhibition design and the mobile application, the gallery offers consistent, multi-sensory experiences that reduce barriers and support independent exploration.

What does it take to navigate last-minute resistance on the eve of a collections-wide portal launch after two years of planning and execution? How do you avoid the derailment of an already moving train?

In mid-2025, The Huntington launched a pan-collections portal that combines our three collecting divisions —the Library, the Art Museum, and the Botanical Gardens— into one cohesive discovery platform on our main website.

The objective was straightforward and in-line with our 5-year strategic plan: create a simple, navigable, and accessible online space for casual users to explore all our collections without having to navigate three separate formal research sites. Although the launch of this discovery portal took nearly two years of planning and execution, at the midnight hour, we experienced a near mutiny from our curatorial teams who were unaware of and expressly displeased with the need to consolidate cataloging and metadata practices to a cross-divisional level. They felt like they were losing control over the collections they're responsible for, and they didn’t like that. 

This is a case study of how the discovery portal team had to quell anxieties and problem-solve our way into proceeding with an imminent launch, despite objections.

We will discuss the development and execution process, where things went wrong, and the steps we took to address these last-minute concerns and build trust among our internal users, particularly our curators.

We will also cover what sustainability looks like after implementation: governance, clear decision rights, documentation, and a workable path to raise issues, so problems aren’t solved ad hoc—or by the loudest voice.  Attendees will leave with a fresh perspective on how disagreements, especially at the most critical moments, are opportunities for positive change and encouragement in team building and trust-building.

Museums are being asked to make decisions about AI and take on new roles and practices at a moment when both the technologies themselves and the social expectations surrounding them are evolving rapidly. This session shares the synopsis of the Museums and AI convening funded by the Institute of Museum and Library Services in spring 2026, which brought together museum professionals, technologists, educators, researchers, and institutional leaders to reflect on the current state of AI in the museum field, imagine possible futures, and identify what support museums need in order to engage with AI responsibly and effectively.

Drawing from facilitated discussions, scenario-building exercises, and thematic synthesis conducted after the convening, this session presents what museum professionals currently see as the most promising and most likely trajectories for AI adoption in museums, as well as concerns and ethical issues. Rather than framing AI as either an inevitable solution or an existential threat, the session examines the nuanced perspectives that emerged across the convening.

One theme that emerged was exploring AI use for internal workflow efficiency, particularly where these tools could help address museums’ chronic capacity limitations, in contrast to visitor-facing AI experiences, with concerns about the trust the public has in Museums, hallucinations and misinformation, intellectual property, transparency, and the potential erosion of human interpretation and expertise. The convening also revealed significant concerns about uneven institutional capacity across the field. Leaders raised the issue that AI adoption could widen existing inequities between large, well-resourced museums and smaller institutions lacking staffing, technical expertise, policy guidance, or experimentation capacity. 

Many other themes arose, including AI policies, ethical use, improvements to accessibility, environmental concerns, use of Open Access and other content as AI training sets, complexities in working with AI vendors, AI literacy in the public and in museum staff, rapidly changing legal implications,  leadership skills necessary for meeting the moment, and how funders can best understand and support museums in this moment. 

Finally, participants identified significant needs for shared field-wide support, including ethical frameworks, implementation guidance, professional development, peer-learning networks, and stronger forms of AI literacy grounded in museum contexts and values.

Rather than focusing on what AI is, specific tools, or individual implementations, this session offers attendees a high-level synopsis of how museums across the field are currently thinking about AI, unpacking these themes to document where major tensions and opportunities are emerging, where there was consensus, and when viewpoints differed, and how institutions can approach AI adoption in ways that align with mission, public trust, equity, and long-term institutional values.

How do you modernize critical exhibit systems without disrupting the visitor experience? This session explores how the 9/11 Memorial & Museum is upgrading the backend infrastructure that powers its digital exhibits. From replacing outdated technologies to introducing containerized systems and real-time monitoring, this work ensures reliability at scale while supporting millions of visitors each year. Learn how to approach modernization in a live museum environment, make the case for change, and implement upgrades that improve both operational stability and long-term sustainability.

When the 9/11 Memorial & Museum opened in 2014, its digital exhibit systems were built using technologies that were appropriate at the time but have since become outdated. Over the years, these systems have remained central to the visitor experience, supporting some of the most meaningful and interactive elements of the Museum. However, maintaining reliability and performance at scale has become increasingly challenging. This session focuses on how we are modernizing the backend infrastructure that powers three core interactive exhibits: the Memorial Exhibition interactive, the Signing Steel Kiosks and Projected Map, and the Last Column interactive. These experiences allow visitors to engage deeply with the stories of victims, leave personal reflections, and explore artifacts connected to first responders and recovery workers. The goal of this modernization effort is not just to replace outdated technologies, but to ensure long-term stability, scalability, and ease of management. I will walk through how we evaluated the existing systems, identified risks associated with legacy components, and prioritized upgrades while keeping the exhibits fully operational. A key part of this work involves moving to a containerized architecture using tools such as Docker Compose. This shift allows us to standardize deployments, improve system reliability, and reduce the complexity of maintaining multiple applications. In parallel, we are modernizing our content management capabilities, making them accessible so exhibit staff can more easily manage and update digital content without heavy technical dependency. Another important focus is observability. By integrating modern monitoring and logging tools, we now have real-time visibility into system performance and usage patterns. This not only helps us proactively address issues but also provides valuable insights into how visitors interact with these exhibits. Throughout the session, I will also discuss the practical side of this work—how to build a case for modernization within a museum setting, how to balance risk and continuity, and how to execute technical upgrades in a live, high-traffic environment.

Description coming soon

More than a decade ago, Research Quest was recognized at NMC as a “Best of Show” prototype—an ambitious digital learning experience designed to connect students with real museum collections and scientific data. Ten years later, it has been developed into 15 distinct learning modules in use today by hundreds of educators and thousands of learners across the United States. What does it take for a digital experience not just to launch successfully, but to endure—and continue to earn trust over time?

This session offers a longitudinal case study of Research Quest’s evolution, examining the design decisions, trade-offs, and core commitments that allowed the platform to adapt across shifting technologies, audiences, and expectations without losing its integrity. As digital ecosystems accelerate and trust in information sources becomes increasingly fragile, designing for longevity requires more than innovation—it demands clarity about what should remain constant.

Drawing on close collaboration between the fields of design and the learning sciences, we will explore how foundational principles—such as centering authentic contexts, supporting inquiry-based engagement, and making scientific processes visible—have shaped both user experience and long-term credibility of the content. We will share examples of how scaffolding was refined over time to better support learners exercise data agency as they interprete complex data, understand uncertainty, and engage in evidence-based reasoning – supporting how to think not what to think.

Participants will examine what changed (platforms, interfaces, distribution models) and what did not (commitments to authenticity, learner agency, and scientific integrity), and consider how these decisions contributed to sustained use and trust. The session will also surface tensions between innovation and stability, and the realities of maintaining and evolving a digital product within institutional constraints.

As museums and cultural organizations navigate rapidly changing technological landscapes—including AI-generated content and shifting expectations around authority—this session offers a grounded perspective on designing systems that endure. Participants will leave with practical frameworks for building digital experiences that can evolve over time while maintaining credibility, relevance, and trust.

Jaws drop. Eyes widen. Awe is the feeling of being in the presence of something vast or profound that leads you to see the world in a different way. Regularly experiencing and reflecting on moments of awe can have long-term benefits for our minds, bodies, and social connections. It opens us up to new ways of thinking, shifts perspectives, and increases empathy. And art is the perfect place to start. 

The National Gallery of Art’s learning and engagement and visitor experience teams together with Dr. Dacher Keltner and the Social Interaction Lab at the University of California, Berkeley, have researched how people can cultivate awe through art. But how do we foster that experience online? The museum’s awe and digital content teams have experimented with developing interactive articles that encourage curiosity, wonder, emotional connection, and a deeper engagement with visual art. In this session, we’ll introduce you to the principles of awe, share insights from the National Gallery’s research, and explore how to adapt these findings into content choices—from pacing and tone to visuals and multimedia materials. You’ll leave with tools to help your online visitors pause, look closely, reflect, and find more awe in their lives.

The best exhibit technology disappears. A visitor reaches for a screen, a button, and a story unfolds. That invisibility requires, in practice, a set of architectural decisions that many museum platforms never make — decisions that determine not just who can experience an exhibit today, but whether the system holding it together will still hold up after exhibits rotate, content changes, audience needs shift, staff turns over, and the vendors you launched with are no longer the vendors you have.

At the Obama Presidential Center, we treated accessibility and longevity as architecture problems. The result is a centralized exhibit platform powering the OPC's digital experiences. It spans cloud-based content authoring, a MongoDB-backed exhibit API, on-premises Docker services, and a fleet of devices — touchscreen kiosks and dedicated accessibility UXP devices — all drawing from the same content and event model. Every device, whatever its form, is a client of the same system. The visitor at the touchscreen and the visitor at the UXP station are not having parallel experiences maintained by separate codebases. They are having the same experience, delivered differently. Accessibility decisions in museums are often mistaken for content decisions — alt text, audio descriptions, alternative formats. These matter, but they are downstream of something more fundamental: whether the system itself was designed to serve more than one kind of visitor.

This didn't emerge from the architecture. It is the architecture.

Building the suite of services taught us that the decisions with the deepest impact on accessibility and longevity are rarely the visible ones — and that getting them right early is what makes everything else possible. The unglamorous choices about how content is shared, how devices communicate, and how much the running exhibit depends on live infrastructure turned out to be the choices that had the most impact.

This session is a case study in those decisions — how we made them, what they cost, what they produced, and what we would do differently. The OPC had dedicated engineering resources that many institutions cannot count on. We don't want to paper over that. But the principles that guided us are not proprietary, and the questions they answer — who can access this, and will it last — are ones every institution is already living with, whatever their stack.

I hope to leave attendees with a clearer sense of what trustworthy exhibit infrastructure can look like, and a vocabulary for advocating for it in their own contexts.