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PS26: Opening Keynote
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PS26: Opening Keynote
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Language: EN.
Segment:0 .
SPEAKER: Good morning. On behalf of [INAUDIBLE], thank you for joining us for breakfast. As a company, many of us are parents of young children. So, happy to sponsor a hot cup of coffee for anybody who doesn't get a chance to have one of those when they're at home. Though next year, I'm going to talk to Steph about sponsoring a different weather package. So Steph, if we could do a sunny-with-low-humidity, let me know the pricing on that.
SPEAKER: I'd be interested. Kicking things off, I'm happy to be introducing Wendy Queen. I hope you all did your homework and answered her survey questions that were sent out. She's the Chief Transformation Officer at Johns Hopkins University Press. She spent a decade as the director, of course, of Project MUSE. She's leading the integration of BioOne into Hopkins Press, and has been honored for her work in AI across scholarly publishing.
SPEAKER: Few people have a better vantage point than she will bring to the topics today, so please join me in welcoming Wendy Queen. [APPLAUSE]
WENDY QUEEN: OK, so thank you. Thank you so much for the invitation to be here today. It's lovely to see so many familiar faces, and also looking forward to meeting new people. It's very much an honor for me to be able to kick off this meeting. I'm afraid I'm going to disappoint you, because Will set me up to give you some sort of insights to the stock market. And the only thing I can tell you is I'm single-handedly supporting the trend to keep Diet Coke exceeding its expectations in this market.
WENDY QUEEN: So I'm really looking forward to the day, to the conversations we'll have and what we learn from one another, and especially to hearing where some of my assumptions get challenged throughout the day. When I was thinking about how to open today, I kept coming back to the title of this event-- Signal and Noise. Rather than give you the list of trends I think that matter, and that will very much come from a university press perspective, I thought it would be more useful to begin with all of your answers.
WENDY QUEEN: What did we expect would demand our attention? What is it demanding now? And what are we still trying to understand? And to capture this, many of you responded to a survey sent out a few weeks ago, so I will say thank you for that. Together, your answers give us a very useful place to start. I think we all agree that our problem right now is not a shortage of signals.
WENDY QUEEN: We have more signals and noise than we know what to do with. Another AI announcement, another model, another partnership, another licensing agreement, another prediction about how researchers will work, what libraries will do, or what will become of publishing. Your written responses to the surveys also raised platform costs, accessibility, library budgets, and government funding. The difficult part is deciding which signals deserve action, and just as importantly, which ones don't just yet.
WENDY QUEEN: Through the survey snapshot, I'm most interested in the stories beneath the numbers. I know Will just told us to look at the numbers, and I'm going to say, look at the story-- where expectations met reality, where they did not, and what might tell us about the decisions we have ahead. We first asked you to think back to the beginning of 2026. What did you expect would demand the most attention from your organization?
WENDY QUEEN: Generative AI products and features was the leading expectation. Research integrity and the business, licensing, and rights questions surrounding AI followed close behind. In other words, what should we build? What should we permit? And how do we protect the integrity and value of scholarly work? Then we asked, what is actually demanding the most attention today?
WENDY QUEEN: The center of gravity shifted. AI-mediated research and discovery became the leading answer. Platform modernization and infrastructure also made one of the strongest moves upward. Meanwhile, generative AI products, research integrity, and business and rights questions all moved down the ranking. That does not mean they stopped mattering.
WENDY QUEEN: It means that when you were forced to name one issue-- force is a little strong there, I'm sorry-- one issue demanding the most attention, more of your answers pointed towards how scholarship is being found and what systems need in order to support that change. Across all of your answers, I hear movement from the visible feature to the environment underneath, from asking what AI experience we might add to asking how content, access, trust, and infrastructure need to work when discovery is increasingly mediated.
WENDY QUEEN: The chart gives you the numbers. The narrative I take from it is that our attention is moving outward, beyond the feature on our own page, and towards the larger ecosystem which scholarship now has to travel. I see three connected shifts in this pattern. First, AI is infrastructure. The question is no longer what feature to add to our platform.
WENDY QUEEN: It is also what kind of environment our content will need to work in. Second, we need to think about both our readers and the tools acting on their behalf. The researcher is still the person we're trying to serve, but an AI assistant or agent may be accessing our content for them. That raises different questions for us. Who or what is accessing the content, with whose permission, and how does that interaction help the researcher?
WENDY QUEEN: And third, a conversation I think we've done very well as a community discussing is trust needs to travel. The context that helps someone judge a scholarly work cannot matter only when the person is looking at our own page. That is my interpretation, rather than something the survey establishes on its own. It connects discovery, access, infrastructure, and trust and puts the platform decision in a wider context.
WENDY QUEEN: Here's the distinction that I find useful for today's conversations. AI is no longer just a feature on the page. It is becoming part of the environment in which the content is found, interpreted, and acted upon. Instead of asking, should we have an AI feature? we start asking, how will our content be discovered in an AI-mediated research environment?
WENDY QUEEN: Instead of asking, what do we think about agents? we ask, can our infrastructure support machine-mediated use? And instead of asking only, what is our AI strategy? we ask, what are our users actually doing? That doesn't make features irrelevant. It changes the context in which we evaluate them. We evaluate access rules, better metadata, different workflows, or even a partnership may be as consequential as a new feature.
WENDY QUEEN: For a publisher or platform, those choices have different costs, different dependencies, different implications for the relationship with the researcher. I'm sorry, I have to take a sip of water. I get a little bit passionate up here, and there's no way for me to make it through 21 minutes without it.
WENDY QUEEN: That brings us to the audience. The researcher is still a person we ultimately want to serve, but the interaction with a scholarly object may also involve a librarian, a search service, an assistant, an agent, or a bot. Those are not interchangeable. They can have different intents, different permissions, and different ways of creating or consuming value.
WENDY QUEEN: So more traffic is not by itself an answer. Who is interacting with the content, on whose behalf, with what permission, and what useful result does the researcher get? A machine interaction might help someone find a source they might otherwise have missed. It might also be activity that tells us very little about meaningful use. For me, the strategic issue is the relationship underneath the transaction.
WENDY QUEEN: Who understands the researchers need? Who provides the access? And who can see whether the interaction was useful? And publishing already has signal infrastructure-- peer review, citations, versions, metadata, rights, provenance. The challenge isn't to explain why those things matter. It is to preserve their meaning when the scholarship is encountered outside the environment that originally supplied the context.
WENDY QUEEN: A citation may provide a route back to the work, but what happens when a summary or excerpt or another derivative becomes the main thing a person encounters? That connects directly to the written responses about the creation and storage of AI derivatives of scholarly content. The relationship between the derivative and the scholarly record matters. That is why I would not read the lower attention for research integrity as a reason to separate it from infrastructure.
WENDY QUEEN: Trust still belongs in the design of discovery and access. It's not a concern we leave behind when the conversation moves to technology. Your answers tell us something important about where this room is starting from. We're not standing still. I didn't expect we were standing still. But it's good to have validation.
WENDY QUEEN: Running isolated experiments was by far the most common answer. Offering AI-enabled features came next, followed by using AI in internal workflows. Only a small part of the room described itself as mostly watching and learning. Those descriptions are not a maturity ladder, and most of us probably occupy more than one of them. We may be experimenting in one part of our organization while making a sustained commitment in another part.
WENDY QUEEN: What we share is the harder question that comes after the experimentation. When does a promising result deserve an ongoing organizational commitment? A working demonstration does not settle the question of cost, staff capacity, user demand, governance, or who will maintain the service. So our collective challenge is not whether to engage. We already are.
WENDY QUEEN: It is deciding what should be moved into sustained use, what should remain an experiment, and what should we stop doing before it becomes a permanent claim on resources? Which brings me to the result I find the most interesting-- we asked where your organization's signal-to-noise problem is most acute right now. Understanding changing researcher and user behavior was the leading answer.
WENDY QUEEN: Knowing which technologies matter and deciding what to build or invest in form the next tier. We do not need to ask whether discovery is changing. We know it is. Researchers are beginning in new places, encountering answers before source lists, and moving between AI systems, search services, library environments, and publisher platforms. The harder questions for all of us are how discovery is changing, which changes are durable, and what they require from our organizations.
WENDY QUEEN: Where does a researcher begin? When an AI system provides an answer, do they follow the citation? Do they reach our platform? Does the institution know that its licensed content contributed to that interaction? And, perhaps most importantly, can our current measures even show us what is happening? Can we attribute to the interaction?
WENDY QUEEN: Can we see the actual value created? Your answers connect behavior directly to investment. They suggest what change may matter to our missions and business models before our existing measures make it easy to see. All of your written answers make those questions more concrete. We asked you to finish, "Six months ago, I wasn't sure about something.
WENDY QUEEN: Now I'm increasingly convinced it's real and important." Among the responses were AI integration into standard workflows, AI being an important intermediary between research and scholarly content. Another simply said access rules. Another named accessibility. And a respondent is increasingly convinced that AI can add meaningful insight rather than just save time.
WENDY QUEEN: Each answer reflects one perspective, but taken together, they broaden our discussion beyond the capability of a tool. They point to its place in our workflows, the conditions of access, and the quality of the experience we make possible. Accessibility is important to keep in this conversation. I don't see it as an aside to innovation. If we're considering how scholarship will be discovered and used, the ability of people to use it belongs in that same discussion.
WENDY QUEEN: I'm really trying not to take another water break, so bear with me. Then we asked you all to consider the opposite. "Six months ago, I thought something would matter more than it actually has." LLM licensing for training stood out among the answers, along with publisher-facing generative AI features. But your responses also pointed beyond AI to accessibility, budget cuts to libraries, and US government funding mandates.
WENDY QUEEN: That is not evidence that funding pressures have eased. There are individual assessments of what mattered less than expected, not a finding about the condition of library budgets or public funding. Accessibility appears on both sides, as something increasingly recognized as real and important, and something that mattered less than expected. The brief responses don't explain the contrast, but it's worth noticing.
WENDY QUEEN: An issue can be significant without being newly disruptive. It can be an ongoing responsibility without dominating the current conversation. And the same issue may have very different implications across organizations. And that brings us back to the distinction between attention and importance. The question is not only, what has become more visible? It is also, what still requires resources, whether or not it is generating the most discussion?
WENDY QUEEN: One of the strongest questions you gave us was not about AI at all. Someone in this room asked how smaller publishers can sustain rising platform costs when they have no way to recover comparable amounts from their customers. That is a question about whether the economics work, not simply whether the technology works.
WENDY QUEEN: Something can be technologically valuable and still be economically unsustainable for the organization expected to pay for it. I think that belongs at the center of the conversation about platform strategy, not as an objection to innovation, but as a part of deciding which innovations can be sustained, and by whom. Who can afford to participate, which costs are shared, and which fall on an individual publisher?
WENDY QUEEN: What other work becomes harder to fund when a platform commitment grows? Those are questions I would put alongside future development, discovery, and infrastructure. The survey responses don't answer them. It gives us a reason to bring all of those things into the room and into the conversations today. The ambition isn't simply to build more capable systems.
WENDY QUEEN: It is to sustain systems that publishers can participate in and that researchers can actually use. And taken together, all of your questions make the relationship between capability, demand, and value even clearer. You asked when libraries will start asking for the connections publishers and platform providers are preparing, and whether we may be rushing towards a solution before the need is fully visible.
WENDY QUEEN: You asked how we should position our content and platforms when researchers discover interactive scholarship through AI, rather than directly through journal websites. You asked how much reading may happen away from the journal platform, and why are we not giving data quality more attention before AI adoption? And one of you asked, where would we begin if we were starting a new digital journals program today? That's a useful question for us, even those of us leading programs that have been around for decades.
WENDY QUEEN: It gives us a chance to separate what we would deliberately choose today from what we have inherited. My starting point wouldn't be a particular platform or an AI feature. It would be the community we're trying to serve. What do authors and readers need from us? How will people discover and use the scholarship, and what will help them trust it? And how do we support that work financially?
WENDY QUEEN: Some of our answers might lead back to things we already do well. Others might point towards different infrastructure, services, or partnerships. Most of us aren't starting from scratch. But we can still ask what would we choose again, what would we design differently, and what can we begin changing now? Those questions put different pressures on the same decision.
WENDY QUEEN: We might be technically ready before demand is clear. We might see a change in discovery before we understand its effect on usage or revenue. We might invest in a new experience while still needing to invest in the data and the current experiences underneath it. So technical readiness does not solve strategic or settle strategic timing. Nor does uncertainty, by itself, tell us to wait.
WENDY QUEEN: It depends on what is changing, what we stand to lose, and what kind of commitment we are considering. Sorry, I really do have to get a drink of water now. So sorry. So for me, those tensions come together in three questions for all of us.
WENDY QUEEN: How is behavior changing, and which changes matter? We already know discovery is changing. The question is where the change is becoming durable, how it affects the way researchers interpret and use scholarship, and what responses the evidence warrants. Some changes may justify a focused experiment. Others may require us to rethink access, metadata, or the relationship with the researcher.
WENDY QUEEN: Does it change the flow of value? Who provides access? Who gets cited? Who gets paid? Who has the relationship with the researcher? And who can see the use? An apparently small change in an interface or an approach may matter a great deal if it changes those relationships. And what happens if we wait?
WENDY QUEEN: Waiting may give us better information and a less expensive decision, but it also could mean someone else defines the terms of access or becomes the intermediary between us and our users. And that really is the tension, the risk of acting prematurely against the risk of waiting too long. The difficult part is deciding what the evidence warrants before the picture is complete.
WENDY QUEEN: Evidence of a useful capability is not automatically evidence for a large investment, but a shift in control of access or in a relationship with a researcher may require response before we can fully measure its effects. Those responses do not all have to be new products. They may involve rights, metadata, partnerships, or investment in the infrastructure already supporting our work. So the question isn't simply whether a development is real.
WENDY QUEEN: It's what it changes for us and what we stand to gain or lose by waiting. That's the conversation I hope we can carry into the rest of today. AI is a major part of it. But it's not the whole of it. The platform affordability question belongs alongside discovery.
WENDY QUEEN: Accessibility belongs alongside user experience. And the ability to sustain the work belongs alongside the ambition to change it. We won't all have the same priorities, resources, or even tolerance for risk. The same development may call for different responses in different organizations. What would make today valuable for me is a clearer sense of where those choices connect.
WENDY QUEEN: Where could collaboration make a response more sustainable? Where does delay preserve our options, and where might it narrow them? How is behavior changing? Does it change the flow of value, and what happens if we wait? Because I think we all can agree our problem is no longer a shortage of signals. It's deciding which signals deserve action now.
WENDY QUEEN: So I'll close with that. And thank you for the opportunity to be able to present today. It was really a wonderful experience to get inside your data and form a conversation that included my voice and all of your voices at the same time. So, thank you. [APPLAUSE] I have no concept of time, except that I timed that at least 20 times, and it should be 21.3. [LAUGHTER] But I do think we do have a few moments for questions.
WENDY QUEEN: And Stephanie has a mic. Greg?
GREG FAGAN: Hi, Wendy. Greg Fagin from Aptara. Do you find that, as a high-level person at a university press, that your concerns are aligning with the feedback that you received from the survey? And I'm sure you talked to other people at other university presses roughly at your level or around there. Are they facing the same concerns as you are?
WENDY QUEEN: That's a great question. So I want to give one caveat. We have an incredibly talented and ambitious director at our press. So I think in many ways, our press has led a lot of the AI conversation in the university press community. So we consider it as also having aggregations and services as part of our offerings. We consider it part of our duty to have these conversations and to travel as a group together through this.
WENDY QUEEN: I think that there are many different types of university presses, and there are some that-- it's all over the spectrum. You'll have some that will say, don't you ever let AI touch a single piece of my content. And you're like, oh, well, sorry. Too late. Google did that for you. And then others that are exactly where all of us are today, trying to figure out, what are those next steps, trying to understand it, following the narrative every day to get better clues, better data to how we want to inform that strategy.
WENDY QUEEN: I hope I answered the question. In short, it's all over the spectrum. And I'm just lucky to be at a press that's been on the forefront.
CHRIS ASHER: Hi, Chris Asher. I'm the Senior Managing Editor for INFORMS. So, two important questions that you posed to us. What is the cost of acting too early? What's the cost of acting too late? In your capacity, just from a 50,000-foot-view, because there are going to be a lot more granular conversations about this, I'm sure, later on today, do you have some bullet point guidelines, or maybe just suggestions for evaluating when to act, or just from your own perspective, how do you decide when is the time to act now, when is the time to hold back, wait, and collect more information, just from your personal experience within your role?
WENDY QUEEN: That's a great question. And all I can do is answer it from my personal experience, because I'm really looking forward today to hearing how others in this room make those decisions. I will say personally for us, we've had to keep the conversation at the forefront of the discussions. In my introduction, I was introduced as Chief Transformation Officer. That role was created for a reason.
WENDY QUEEN: The Director of the Press decided this is not a topic that could be secondary to our workings of every day. This isn't a topic that you form a committee that meets once a month, although we do have a lot of committees meeting around it. But it is something that's coming into every single part of the strategic conversation, from building a culture at the press for the people that can experiment in this to, hey, what are our decision points when it comes to a budget?
WENDY QUEEN: How are we going to allocate resources to, in some ways, live in two places at one time, right? There's nothing that we're currently doing that we're necessarily abandoning, right? But we do need to support these two pathways with equal vigor to it.
SPEAKER: Thank you so much, Wendy. And you can find her later for more questions.
WENDY QUEEN: Thank you. [APPLAUSE]
Segment:0 .
SPEAKER: Good morning. On behalf of [INAUDIBLE], thank you for joining us for breakfast. As a company, many of us are parents of young children. So, happy to sponsor a hot cup of coffee for anybody who doesn't get a chance to have one of those when they're at home. Though next year, I'm going to talk to Steph about sponsoring a different weather package. So Steph, if we could do a sunny-with-low-humidity, let me know the pricing on that.
SPEAKER: I'd be interested. Kicking things off, I'm happy to be introducing Wendy Queen. I hope you all did your homework and answered her survey questions that were sent out. She's the Chief Transformation Officer at Johns Hopkins University Press. She spent a decade as the director, of course, of Project MUSE. She's leading the integration of BioOne into Hopkins Press, and has been honored for her work in AI across scholarly publishing.
SPEAKER: Few people have a better vantage point than she will bring to the topics today, so please join me in welcoming Wendy Queen. [APPLAUSE]
WENDY QUEEN: OK, so thank you. Thank you so much for the invitation to be here today. It's lovely to see so many familiar faces, and also looking forward to meeting new people. It's very much an honor for me to be able to kick off this meeting. I'm afraid I'm going to disappoint you, because Will set me up to give you some sort of insights to the stock market. And the only thing I can tell you is I'm single-handedly supporting the trend to keep Diet Coke exceeding its expectations in this market.
WENDY QUEEN: So I'm really looking forward to the day, to the conversations we'll have and what we learn from one another, and especially to hearing where some of my assumptions get challenged throughout the day. When I was thinking about how to open today, I kept coming back to the title of this event-- Signal and Noise. Rather than give you the list of trends I think that matter, and that will very much come from a university press perspective, I thought it would be more useful to begin with all of your answers.
WENDY QUEEN: What did we expect would demand our attention? What is it demanding now? And what are we still trying to understand? And to capture this, many of you responded to a survey sent out a few weeks ago, so I will say thank you for that. Together, your answers give us a very useful place to start. I think we all agree that our problem right now is not a shortage of signals.
WENDY QUEEN: We have more signals and noise than we know what to do with. Another AI announcement, another model, another partnership, another licensing agreement, another prediction about how researchers will work, what libraries will do, or what will become of publishing. Your written responses to the surveys also raised platform costs, accessibility, library budgets, and government funding. The difficult part is deciding which signals deserve action, and just as importantly, which ones don't just yet.
WENDY QUEEN: Through the survey snapshot, I'm most interested in the stories beneath the numbers. I know Will just told us to look at the numbers, and I'm going to say, look at the story-- where expectations met reality, where they did not, and what might tell us about the decisions we have ahead. We first asked you to think back to the beginning of 2026. What did you expect would demand the most attention from your organization?
WENDY QUEEN: Generative AI products and features was the leading expectation. Research integrity and the business, licensing, and rights questions surrounding AI followed close behind. In other words, what should we build? What should we permit? And how do we protect the integrity and value of scholarly work? Then we asked, what is actually demanding the most attention today?
WENDY QUEEN: The center of gravity shifted. AI-mediated research and discovery became the leading answer. Platform modernization and infrastructure also made one of the strongest moves upward. Meanwhile, generative AI products, research integrity, and business and rights questions all moved down the ranking. That does not mean they stopped mattering.
WENDY QUEEN: It means that when you were forced to name one issue-- force is a little strong there, I'm sorry-- one issue demanding the most attention, more of your answers pointed towards how scholarship is being found and what systems need in order to support that change. Across all of your answers, I hear movement from the visible feature to the environment underneath, from asking what AI experience we might add to asking how content, access, trust, and infrastructure need to work when discovery is increasingly mediated.
WENDY QUEEN: The chart gives you the numbers. The narrative I take from it is that our attention is moving outward, beyond the feature on our own page, and towards the larger ecosystem which scholarship now has to travel. I see three connected shifts in this pattern. First, AI is infrastructure. The question is no longer what feature to add to our platform.
WENDY QUEEN: It is also what kind of environment our content will need to work in. Second, we need to think about both our readers and the tools acting on their behalf. The researcher is still the person we're trying to serve, but an AI assistant or agent may be accessing our content for them. That raises different questions for us. Who or what is accessing the content, with whose permission, and how does that interaction help the researcher?
WENDY QUEEN: And third, a conversation I think we've done very well as a community discussing is trust needs to travel. The context that helps someone judge a scholarly work cannot matter only when the person is looking at our own page. That is my interpretation, rather than something the survey establishes on its own. It connects discovery, access, infrastructure, and trust and puts the platform decision in a wider context.
WENDY QUEEN: Here's the distinction that I find useful for today's conversations. AI is no longer just a feature on the page. It is becoming part of the environment in which the content is found, interpreted, and acted upon. Instead of asking, should we have an AI feature? we start asking, how will our content be discovered in an AI-mediated research environment?
WENDY QUEEN: Instead of asking, what do we think about agents? we ask, can our infrastructure support machine-mediated use? And instead of asking only, what is our AI strategy? we ask, what are our users actually doing? That doesn't make features irrelevant. It changes the context in which we evaluate them. We evaluate access rules, better metadata, different workflows, or even a partnership may be as consequential as a new feature.
WENDY QUEEN: For a publisher or platform, those choices have different costs, different dependencies, different implications for the relationship with the researcher. I'm sorry, I have to take a sip of water. I get a little bit passionate up here, and there's no way for me to make it through 21 minutes without it.
WENDY QUEEN: That brings us to the audience. The researcher is still a person we ultimately want to serve, but the interaction with a scholarly object may also involve a librarian, a search service, an assistant, an agent, or a bot. Those are not interchangeable. They can have different intents, different permissions, and different ways of creating or consuming value.
WENDY QUEEN: So more traffic is not by itself an answer. Who is interacting with the content, on whose behalf, with what permission, and what useful result does the researcher get? A machine interaction might help someone find a source they might otherwise have missed. It might also be activity that tells us very little about meaningful use. For me, the strategic issue is the relationship underneath the transaction.
WENDY QUEEN: Who understands the researchers need? Who provides the access? And who can see whether the interaction was useful? And publishing already has signal infrastructure-- peer review, citations, versions, metadata, rights, provenance. The challenge isn't to explain why those things matter. It is to preserve their meaning when the scholarship is encountered outside the environment that originally supplied the context.
WENDY QUEEN: A citation may provide a route back to the work, but what happens when a summary or excerpt or another derivative becomes the main thing a person encounters? That connects directly to the written responses about the creation and storage of AI derivatives of scholarly content. The relationship between the derivative and the scholarly record matters. That is why I would not read the lower attention for research integrity as a reason to separate it from infrastructure.
WENDY QUEEN: Trust still belongs in the design of discovery and access. It's not a concern we leave behind when the conversation moves to technology. Your answers tell us something important about where this room is starting from. We're not standing still. I didn't expect we were standing still. But it's good to have validation.
WENDY QUEEN: Running isolated experiments was by far the most common answer. Offering AI-enabled features came next, followed by using AI in internal workflows. Only a small part of the room described itself as mostly watching and learning. Those descriptions are not a maturity ladder, and most of us probably occupy more than one of them. We may be experimenting in one part of our organization while making a sustained commitment in another part.
WENDY QUEEN: What we share is the harder question that comes after the experimentation. When does a promising result deserve an ongoing organizational commitment? A working demonstration does not settle the question of cost, staff capacity, user demand, governance, or who will maintain the service. So our collective challenge is not whether to engage. We already are.
WENDY QUEEN: It is deciding what should be moved into sustained use, what should remain an experiment, and what should we stop doing before it becomes a permanent claim on resources? Which brings me to the result I find the most interesting-- we asked where your organization's signal-to-noise problem is most acute right now. Understanding changing researcher and user behavior was the leading answer.
WENDY QUEEN: Knowing which technologies matter and deciding what to build or invest in form the next tier. We do not need to ask whether discovery is changing. We know it is. Researchers are beginning in new places, encountering answers before source lists, and moving between AI systems, search services, library environments, and publisher platforms. The harder questions for all of us are how discovery is changing, which changes are durable, and what they require from our organizations.
WENDY QUEEN: Where does a researcher begin? When an AI system provides an answer, do they follow the citation? Do they reach our platform? Does the institution know that its licensed content contributed to that interaction? And, perhaps most importantly, can our current measures even show us what is happening? Can we attribute to the interaction?
WENDY QUEEN: Can we see the actual value created? Your answers connect behavior directly to investment. They suggest what change may matter to our missions and business models before our existing measures make it easy to see. All of your written answers make those questions more concrete. We asked you to finish, "Six months ago, I wasn't sure about something.
WENDY QUEEN: Now I'm increasingly convinced it's real and important." Among the responses were AI integration into standard workflows, AI being an important intermediary between research and scholarly content. Another simply said access rules. Another named accessibility. And a respondent is increasingly convinced that AI can add meaningful insight rather than just save time.
WENDY QUEEN: Each answer reflects one perspective, but taken together, they broaden our discussion beyond the capability of a tool. They point to its place in our workflows, the conditions of access, and the quality of the experience we make possible. Accessibility is important to keep in this conversation. I don't see it as an aside to innovation. If we're considering how scholarship will be discovered and used, the ability of people to use it belongs in that same discussion.
WENDY QUEEN: I'm really trying not to take another water break, so bear with me. Then we asked you all to consider the opposite. "Six months ago, I thought something would matter more than it actually has." LLM licensing for training stood out among the answers, along with publisher-facing generative AI features. But your responses also pointed beyond AI to accessibility, budget cuts to libraries, and US government funding mandates.
WENDY QUEEN: That is not evidence that funding pressures have eased. There are individual assessments of what mattered less than expected, not a finding about the condition of library budgets or public funding. Accessibility appears on both sides, as something increasingly recognized as real and important, and something that mattered less than expected. The brief responses don't explain the contrast, but it's worth noticing.
WENDY QUEEN: An issue can be significant without being newly disruptive. It can be an ongoing responsibility without dominating the current conversation. And the same issue may have very different implications across organizations. And that brings us back to the distinction between attention and importance. The question is not only, what has become more visible? It is also, what still requires resources, whether or not it is generating the most discussion?
WENDY QUEEN: One of the strongest questions you gave us was not about AI at all. Someone in this room asked how smaller publishers can sustain rising platform costs when they have no way to recover comparable amounts from their customers. That is a question about whether the economics work, not simply whether the technology works.
WENDY QUEEN: Something can be technologically valuable and still be economically unsustainable for the organization expected to pay for it. I think that belongs at the center of the conversation about platform strategy, not as an objection to innovation, but as a part of deciding which innovations can be sustained, and by whom. Who can afford to participate, which costs are shared, and which fall on an individual publisher?
WENDY QUEEN: What other work becomes harder to fund when a platform commitment grows? Those are questions I would put alongside future development, discovery, and infrastructure. The survey responses don't answer them. It gives us a reason to bring all of those things into the room and into the conversations today. The ambition isn't simply to build more capable systems.
WENDY QUEEN: It is to sustain systems that publishers can participate in and that researchers can actually use. And taken together, all of your questions make the relationship between capability, demand, and value even clearer. You asked when libraries will start asking for the connections publishers and platform providers are preparing, and whether we may be rushing towards a solution before the need is fully visible.
WENDY QUEEN: You asked how we should position our content and platforms when researchers discover interactive scholarship through AI, rather than directly through journal websites. You asked how much reading may happen away from the journal platform, and why are we not giving data quality more attention before AI adoption? And one of you asked, where would we begin if we were starting a new digital journals program today? That's a useful question for us, even those of us leading programs that have been around for decades.
WENDY QUEEN: It gives us a chance to separate what we would deliberately choose today from what we have inherited. My starting point wouldn't be a particular platform or an AI feature. It would be the community we're trying to serve. What do authors and readers need from us? How will people discover and use the scholarship, and what will help them trust it? And how do we support that work financially?
WENDY QUEEN: Some of our answers might lead back to things we already do well. Others might point towards different infrastructure, services, or partnerships. Most of us aren't starting from scratch. But we can still ask what would we choose again, what would we design differently, and what can we begin changing now? Those questions put different pressures on the same decision.
WENDY QUEEN: We might be technically ready before demand is clear. We might see a change in discovery before we understand its effect on usage or revenue. We might invest in a new experience while still needing to invest in the data and the current experiences underneath it. So technical readiness does not solve strategic or settle strategic timing. Nor does uncertainty, by itself, tell us to wait.
WENDY QUEEN: It depends on what is changing, what we stand to lose, and what kind of commitment we are considering. Sorry, I really do have to get a drink of water now. So sorry. So for me, those tensions come together in three questions for all of us.
WENDY QUEEN: How is behavior changing, and which changes matter? We already know discovery is changing. The question is where the change is becoming durable, how it affects the way researchers interpret and use scholarship, and what responses the evidence warrants. Some changes may justify a focused experiment. Others may require us to rethink access, metadata, or the relationship with the researcher.
WENDY QUEEN: Does it change the flow of value? Who provides access? Who gets cited? Who gets paid? Who has the relationship with the researcher? And who can see the use? An apparently small change in an interface or an approach may matter a great deal if it changes those relationships. And what happens if we wait?
WENDY QUEEN: Waiting may give us better information and a less expensive decision, but it also could mean someone else defines the terms of access or becomes the intermediary between us and our users. And that really is the tension, the risk of acting prematurely against the risk of waiting too long. The difficult part is deciding what the evidence warrants before the picture is complete.
WENDY QUEEN: Evidence of a useful capability is not automatically evidence for a large investment, but a shift in control of access or in a relationship with a researcher may require response before we can fully measure its effects. Those responses do not all have to be new products. They may involve rights, metadata, partnerships, or investment in the infrastructure already supporting our work. So the question isn't simply whether a development is real.
WENDY QUEEN: It's what it changes for us and what we stand to gain or lose by waiting. That's the conversation I hope we can carry into the rest of today. AI is a major part of it. But it's not the whole of it. The platform affordability question belongs alongside discovery.
WENDY QUEEN: Accessibility belongs alongside user experience. And the ability to sustain the work belongs alongside the ambition to change it. We won't all have the same priorities, resources, or even tolerance for risk. The same development may call for different responses in different organizations. What would make today valuable for me is a clearer sense of where those choices connect.
WENDY QUEEN: Where could collaboration make a response more sustainable? Where does delay preserve our options, and where might it narrow them? How is behavior changing? Does it change the flow of value, and what happens if we wait? Because I think we all can agree our problem is no longer a shortage of signals. It's deciding which signals deserve action now.
WENDY QUEEN: So I'll close with that. And thank you for the opportunity to be able to present today. It was really a wonderful experience to get inside your data and form a conversation that included my voice and all of your voices at the same time. So, thank you. [APPLAUSE] I have no concept of time, except that I timed that at least 20 times, and it should be 21.3. [LAUGHTER] But I do think we do have a few moments for questions.
WENDY QUEEN: And Stephanie has a mic. Greg?
GREG FAGAN: Hi, Wendy. Greg Fagin from Aptara. Do you find that, as a high-level person at a university press, that your concerns are aligning with the feedback that you received from the survey? And I'm sure you talked to other people at other university presses roughly at your level or around there. Are they facing the same concerns as you are?
WENDY QUEEN: That's a great question. So I want to give one caveat. We have an incredibly talented and ambitious director at our press. So I think in many ways, our press has led a lot of the AI conversation in the university press community. So we consider it as also having aggregations and services as part of our offerings. We consider it part of our duty to have these conversations and to travel as a group together through this.
WENDY QUEEN: I think that there are many different types of university presses, and there are some that-- it's all over the spectrum. You'll have some that will say, don't you ever let AI touch a single piece of my content. And you're like, oh, well, sorry. Too late. Google did that for you. And then others that are exactly where all of us are today, trying to figure out, what are those next steps, trying to understand it, following the narrative every day to get better clues, better data to how we want to inform that strategy.
WENDY QUEEN: I hope I answered the question. In short, it's all over the spectrum. And I'm just lucky to be at a press that's been on the forefront.
CHRIS ASHER: Hi, Chris Asher. I'm the Senior Managing Editor for INFORMS. So, two important questions that you posed to us. What is the cost of acting too early? What's the cost of acting too late? In your capacity, just from a 50,000-foot-view, because there are going to be a lot more granular conversations about this, I'm sure, later on today, do you have some bullet point guidelines, or maybe just suggestions for evaluating when to act, or just from your own perspective, how do you decide when is the time to act now, when is the time to hold back, wait, and collect more information, just from your personal experience within your role?
WENDY QUEEN: That's a great question. And all I can do is answer it from my personal experience, because I'm really looking forward today to hearing how others in this room make those decisions. I will say personally for us, we've had to keep the conversation at the forefront of the discussions. In my introduction, I was introduced as Chief Transformation Officer. That role was created for a reason.
WENDY QUEEN: The Director of the Press decided this is not a topic that could be secondary to our workings of every day. This isn't a topic that you form a committee that meets once a month, although we do have a lot of committees meeting around it. But it is something that's coming into every single part of the strategic conversation, from building a culture at the press for the people that can experiment in this to, hey, what are our decision points when it comes to a budget?
WENDY QUEEN: How are we going to allocate resources to, in some ways, live in two places at one time, right? There's nothing that we're currently doing that we're necessarily abandoning, right? But we do need to support these two pathways with equal vigor to it.
SPEAKER: Thank you so much, Wendy. And you can find her later for more questions.
WENDY QUEEN: Thank you. [APPLAUSE]
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