John Wiley & Sons, Inc.

Good morning, and welcome to Wiley's first quarter and fiscal 2027 earnings call. As a reminder, this conference is being recorded. After today's prepared remarks, we will host a question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. At this time, I'd like to introduce Wiley's Vice President of Investor Relations, Brian Campbell. Please go ahead.

Good morning, everyone. I'm joined today by Matt Kissner, President and CEO, and Craig Albright, Executive Vice President and CFO. Our comments and responses reflect management news as of today and will include forward-looking statements. Actual results may differ materially from those statements. The company does not undertake any obligation to update them to reflect subsequent events. Also, Wiley provides non-GAAP measures as a supplement to evaluate underlying operating profitability and performance trends. I'll turn the call over to Matt Kissner.

Thank you, Brian, and hello, everyone. Welcome to our Q1 earnings call. If fiscal 26 was our breakout, then this is the year we build on that momentum and scale our new revenue streams. Q1 played out as we expected. Strong momentum in our research and AI growth engines was offset by a prior year AI comparison, which we previously mentioned, and continued soft market conditions and learning. Recall that Q1 is our seasonally smallest period, so our year-over-year comparisons carry some noise. However, nothing in the quarter changes or full your expectations, which Craig will cover shortly. Wiley's trusted content and intelligence are the foundation for the rapid advancement of science and innovation worldwide. As I've stated before, when it comes to high-stakes scientific research, AI will only live up to its promise if it is fueled by current, accurate, and trusted content and data. Wiley has one of the most comprehensive and continuously growing content and data portfolios in the world. You saw that validated twice this quarter in ways I would not have anticipated a year ago. We were invited to be the sole scientific publisher to participate in the U.S. Department of Energy's Genesis mission and a founding data partner for CUSP AI's Global Materials Foundry. In these endeavors, we stand alongside innovators like NVIDIA, AWS, Microsoft, and others. Behind those headlines, the commercial engine kept running. We signed new AI licensing agreements across multiple industries. I'll walk you through the quarter and the momentum we're seeing in our growth engines, and Craig will take you through our financials and outlook. Let me start with the Q1 takeaways and a brief word on how our two growth engines work together. Research is the foundation where our scale, brands, and society relationships enable us to generate proprietary content across a widening share of high demand disciplines. AI and data analytics are built directly on top of that foundation, leveraging our content and data to create research tools for high stakes R&D. The relationship runs both ways. Publishing fuels the AI and data analytics engine with a continuous flow of proprietary content, and AI powers the researcher productivity that increases the flow of publishing. That's the Wiley flywheel. A few highlights from the quarter. We delivered a 12% increase in research publishing, reflecting strong global demand to publish, with submissions at record levels, the Emerald Edition, and AI momentum all contributing. Learning, on the other hand, faced challenges from a prior year comparison, soft market conditions in professional, and a seasonally small quarter in academic. We generated 14 million of AI revenue in the quarter, and our pipeline is expanding across models, channels, and verticals. We remain well on track to deliver our full-year AI revenue goals. Our Spectral Analysis API portfolio launched into the laboratory market. It's another milestone in our evolution towards an AI and data analytics company. I'll explain this advance later in my remarks. We're integrating Emerald to extend our scale advantage in research and content advantage for AI and data analytics. As expected, the fit is strong on all three dimensions, financially, strategically, and culturally. Our teams are working very well together and the integration is ahead of schedule. and we raised our dividend for the 33rd consecutive year, putting Wiley in rarefied company. Turning to the headline numbers, Craig will provide more detail, but performance this quarter was in line with our plan. Two known factors drove the year over year revenue comparison. The $29 million of AI licensing revenue that landed in the prior year quarter and continued soft market conditions and learning, particularly professional. Neither changes how we see the full year. AI revenue was $14 million in the quarter, with a further $14 million already contracted across Q2 and Q3. Emerald contributed $13 million to the top line. On profitability, adjusted EBITDA was down 4% on the year-over-year revenue performance. Adjusted EPS was down 10% further impacted by higher net interest expense related to the Emerald acquisition. Gap EPS was a loss of 23 cents compared to earnings of 22 cents in the prior year, largely due to restructuring charges and acquisition and integration costs. Let's discuss our continuing strong progress in research. Our key metric for research is publishing throughput. Strong demand to publish remains undiminished worldwide, with submissions up 31% and output up 8%, demonstrating both continued growth and a clear focus on quality. This is evident across both rapidly growing and mature markets. We successfully closed our calendar 2026 journal renewal season with customer retention remaining above 99%. On expanding our journal portfolio and leading brands, we launched two new advanced journals, Advanced Immunology and Advanced Brain and published the first papers in Advanced Computing and Advanced Oncology. As a reminder, our advanced portfolio is accelerating as a global top-tier brand across disciplines, with more than 30 journal titles and revenue of $70 million growing at strong double digits. Also, in the recent Industry Citation Index, released annually, 15 Wiley journals were ranked number one in their respective categories, with 248 of our journals achieving top 10 rankings. Wiley now accounts for over 10% of all citations in the index. This is an important quality signal, and quality is what deepens our competitive moat. On driving publishing efficiency and margin expansion, we increased our research-adjusted EBITDA margin by 130 basis points to 29.6% through the addition of Emerald and cost-savings initiatives. We now have 1,600 journals migrated to our Research Exchange publishing platform. On leveraging our IP and relationships for AI and data analytics growth, our clinical outcome assessments growth engine is rapidly expanding. This portfolio grew from 6 million in fiscal 25 to 11 million last year, and we see a strong trajectory ahead. Q1 revenue rose by more than threefold thanks to Wiley's leading differentiated position. As a reminder, clinical outcome assessments are peer reviewed instruments that are used in clinical trials to measure the impact of treatment from the patient's perspective. They've been developed carefully, tested across patient groups, and proven to measure what they claim to measure. Choosing the correct instrument early, licensing it properly, and implementing it effectively can be the difference between a multimillion-dollar trial that succeeds and one that stalls. And that makes them essential R&D infrastructure. This is where we come in. We own and license a broad and growing portfolio of these instruments across disease areas and alongside full implementation services. An important milestone, as I mentioned, is that we launched our transformative spectral analysis APIs for the corporate and academic laboratory markets, delivering the industry's most trusted gold standard chemical reference data directly into automated laboratory software pipelines. For corporate R&D labs, this will replace slow manual analysis with embedded real-time spectral intelligence. said one industry newsletter, the launch of the spectral analysis API portfolio is the clearest signal yet of Wiley's evolution from a legacy publisher into a modern data and technology company. Let's consider why the research engine remains robust. Publishing is the key metric of academic progress, shaping employment, promotions, prestige, and grant acquisition. The need to publish continues to rise alongside global R&D investment and is now further accelerated by AI advancements. Looking at research across the rest of the year, six reinforcing drivers continue to give us confidence. First, our publishing pipeline is robust and our scale advantage is widening, with submissions outpacing an already strong market and researcher productivity set to rise further with AI. Large-scale, high-quality publishers like Wiley have a structural advantage, and our Q1 KPIs say that is continuing. Second, we concluded a solid calendar 2026 renewal season with strong customer retention. Third, open access growth continues to compound at double digits, driven by the must-have dynamics of publishing worldwide and our journal brand expansion. In fact, we closed July with record gold open access output. Fourth, Emerald is off to a fast start, giving us strong confidence in the combination going forward. Fifth, our clinical outcome assessments pipeline of pharma companies is multiplying, our IQ via go-to-market partnership is scaling, and we continue to activate new in-demand instruments to further bolster our leadership position. Separately, our open evidence partnership is deepening with additional content now under agreement. Finally, we're seeing nice and early momentum in audience monetization. As discussed, we are transitioning this business from traditional advertising to an audience analytics platform underpinned by modern ad tech AI-enabled product development and verified research professional audiences. The healthcare advertising market is large and expanding, and our edge is the combination we already hold, proprietary content, deep society relationships, and an emerging corporate customer base in healthcare and the audiences that come with them. Our digital research content and platforms generate billions of user sessions each year. We recently rolled out new, sophisticated ad tech for contextual targeting, along with improved outcomes reporting and agentic tools for audience engagement. The early results are promising with good growth in Q1 billings. Now on to our AI and data analytics growth engine, the second turn of the flywheel. As a reminder, we took total AI revenue from 23 million in fiscal 24 to 40 million in fiscal 25 and 49 million in fiscal 26. Given our pipelines, we remain well on track for over $50 million in fiscal 27 and AI recurring revenue growing two to three times over prior year. In Q1, we realized $14 million of AI revenue ahead of the pace we need for our full-year target. Importantly, the mix is shifting the way we want. Of the 14 million, 10.5 is from model training and 3.5 is recurring. As I mentioned, we've contracted a further 14 million of AI licensing revenue that will be realized across Q2 and Q3 with additional agreements and active discussion. On the corporate side, we've expanded our customer base for subscription knowledge feeds, bringing us to 23 across five industry verticals, life sciences, healthcare, food and agriculture, materials and chemistry, and financial services. A year ago, this was largely a life sciences story. While that continues to be a big focus for us, it's a lot broader than that now. Finally, our Nexus licensing service continues to add more society and publishing partners, bringing the total to 71. As previously discussed, partnerships are foundational to our strategy. This quarter, we were invited to join the public-private partnership supporting the U.S. Department of Energy's Genesis mission alongside some of the world's largest AI innovators. The mission is a nationwide effort to put AI to work on the country's hardest science and technology problems, and we're the only scientific publisher at the table. Our role is substantive. We will make our research intelligence tools available to researchers across all DOE national laboratories, provide thought leadership on how AI models are validated against scientific evidence and how scientific data is managed, and help shape the consortium's foundational knowledge layer. This builds on decades of engagement with the DOE and other federal science agencies. We became a founding data partner in Cusp AI's AI Materials Foundry, a global network comprising over 45 organizations aimed at speeding up new materials discovery. The Foundry focuses on semiconductors, clean energy, and advanced manufacturing, where progress is limited by materials rather than engineering. Our contribution is the data layer. CUSP AI has licensed access to Wiley's material science content to train the platform. This underscores how our content is being integrated into AI systems that will increasingly drive scientific discovery. AI momentum remains broad-based across verticals, products, and channels, and our pipeline is advancing rapidly across model training, commercial licensing, and subscription knowledge feeds. Of note, model training is becoming a proven engine with both new and repeat customers. At the same time, corporate R&D demand is accelerating across chemistry, food and agriculture, and other domains, while healthcare opportunities widen across large corporates and AI startups. And through our Nexus licensing service and our own publishing engine, the content and intelligence available to license keeps growing. We remain well on track with our full-year AI growth targets. Beyond this, what we see forming is bigger than any one year. The world's most important AI systems are being built on trusted scientific knowledge, and Wiley is becoming a foundational supplier and partner in that economy. As discussed in June, our position rests on a remarkably deep reservoir of proprietary data. In addition to published articles and journals, we have structured metadata and linked domains, and validated research protocols and methods, how studies were designed, not just what they found. We have the peer review and editorial record behind that work and credibility accumulated over many decades. We have citation networks and reference graphs, effectively a map of how knowledge in one discipline draws on another. And we have relationships with both authors and institutions, who is researching what and where. Wiley holds leading content positions in the disciplines that matter most in the AI economy. 150-plus therapeutic areas in life sciences and healthcare, 100-plus areas in chemistry and spectral data, 50-plus in engineering and material science, 45-plus in agriculture and food science topics, along with the leading crops disease database, and now with Emerald, a leadership position across all key areas of economics, business, and finance. Our advantage isn't only breadth, it's depth, where corporate R&D is tackling its most consequential problems and where the next breakthroughs will come from. This depth is now showing up as a widening set of use cases and markets. As a reminder, we're pursuing three organic growth pathways around AI and data analytics, database solutions, applied research intelligence, and audience monetization, each drawing on our existing IP. What this slide shows is where those pathways are landing commercially today. Our structured data is relevant across each, from dermatology instruments for clinical outcome assessments with IQVIA to medical content at the point of care with open evidence. We're working directly with decision makers inside of corporations, institutions, and government bodies, deploying our IP for LLM development, corporate AI applications, and academic labs. We'll lay out our full roadmap at our fiscal 27 investor day scheduled for Thursday, March 11th at our headquarters in Hoboken, New Jersey. We hope to see you there. A few words on our critical role in ensuring responsible AI. By grounding AI in evidence-based knowledge, Wiley helps close the trust gap in AI while enabling innovation that benefits many. This mission has made us an AI thought leader worldwide. Here's the distinction I draw. Most companies approach responsible AI from the model outward, guardrails and policies bolted onto the technology. We start a layer deeper. Responsible AI depends on the quality of the knowledge that fuels it, and that's what Wiley has spent two centuries building. You cannot make an unreliable model reliable with policy alone. You have to fix what it learns from. And we are protecting the scientific record as AI use surges among scholars. Our approach rests on four commitments. One, human oversight. We ensure that judgment stays with people, not models, and that peer review remains a human endeavor. Two, trust and transparency. We protect intellectual property and set the integrity standards for how our content is used. Three, safety and fairness. We ensure it through strict data privacy and active bias mitigation. And four, good governance. We ensure clear internal controls and constructive engagement on smart regulation rather than resistance to it. The market is asking for exactly this. We answered it in October with comprehensive AI guidelines for authors, editors, and peer reviewers covering disclosure, reproducibility, and confidentiality. We've built citation and attribution requirements directly into our technical integrations, including our work with Anthropic. And we've stood up AI oversight across the company. All this speaks to the central role of the research publisher in enabling the global scientific ecosystem and ensuring the quality and impact of high-stakes AI models. The last point I'd make is about posture. We're setting the agenda here, not reacting to it. We were the only publishing sponsor at the United Nations AI for Good Global Summit in Geneva this year. And that leadership is commercially load-bearing. When the Department of Energy, or CUSP AI, chooses a data foundation, the standards behind the content are part of what they are buying. Trust is the product. With that, I'll hand it over to Craig to take you through the financials.