John Wiley & Sons, Inc.

Good morning and welcome to Wiley's second quarter and fiscal 2026 earnings call. As a reminder, this conference is being recorded. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star one again. At this time, I'd like to introduce Wiley's Vice President of Investor Relations, Brian Campbell. Please go ahead.

Good morning, everyone. On the call with me today are Matt Kisner, President and CEO, Craig Albright, Executive Vice President and CFO, and Jay Flynn, Executive Vice President and General Manager of Research and Learning. Note that our comments and responses reflect management views 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. These measures do not have standardized meanings prescribed by US GAAP and therefore, may not be comparable to similar measures used by other companies, nor should they be viewed as alternatives to measures under GAAP. We will refer to non-GAAP metrics on the call and variances are on a year-over-year basis and will exclude divested assets and the impact of currency. Additional information is included in our filings with the SEC. A copy of this presentation and transcript will be available at investors.wiley.com. I'll now turn the call over to Matt Kistner.

Thank you, Brian. Hello, everyone, and welcome to our Q2 earnings update. Before I get into results, which were highlighted by strength and momentum in research and AI, but also declines in learning, let me briefly touch on our agenda. I'll start by outlining what's happening in learning and how we're addressing it. Next, I want to address the questions we've gotten from prospective investors about the unique durability and resilience of the research business and the positive role AI is playing. As you will see, we believe AI is an accelerator for our research core. Building on this, investors naturally want to learn more about our AI growth strategy, so we're going to spend a little time this morning addressing those topics in more detail. I'll also talk about how we're executing on our full year commitments and walk through our overall growth drivers. Craig will review our performance, operational excellence, and margin expansion initiatives, as well as our outlook for the year. Now on to our purpose, which is to unleash the power of science. It means transforming trusted scientific knowledge into practical tools and intelligence that solve real problems. We're moving with urgency to integrate scientific research into new technologies to revolutionize R&D across corporate, academic, and government markets. It's a paradigm shift, and we're at the center of it. never has the trust and accuracy of information mattered more. Our customers range from Nobel laureates to early career researchers, from Fortune 500 innovation teams to government research bodies, all relying on us to ensure scientific excellence and turn scientific knowledge into competitive advantage. Let's turn to the quarter. We saw a mixed revenue picture. with strong growth in research and good momentum in AI, offset by market challenges in our learning segment. I'll dive into learning in more detail on the next slide. Research publishing delivered strong 7% growth on worldwide demand to publish, read, and license. Volume remains at record levels worldwide. We executed another AI licensing project for an existing LLM customer this quarter, putting us close to 100 million of AI training revenue in less than two years. Our corporate expansion is accelerating with new subscription customers and a strong pipeline. We continue to advance our strategic partnerships with AWS, Anthropic, and Perplexity. and added mistrial AI during the quarter. We delivered strong earnings growth as we continually address our overall cost base, reduce our corporate expenses, and drive disciplined capital allocation. Our Q2 adjusted operating margin was up 250 basis points to 18.8%. We increased our share repurchases by 69% this quarter to 21 million. We see our shares trading well below our assessment of true value, which positions buybacks as an efficient use of capital. Through the half, we've returned 73 million to shareholders in buybacks and dividends, and our current yield is around 3.9%. Finally, we expect to drive leverage materially lower this year. Our strong balance sheet is expected to get even stronger. I want to acknowledge our challenges in learning before getting into the positive developments this quarter. Those of you who know me know that I'm not one for spin. Let me just say it's been an unusual year for learning, driven by a set of external factors which began in the first quarter. First, Across the industry, we've seen a significant change in inventory management from Amazon. We've seen this before, and it's an abrupt challenge to manage through. Second, consumer spending is soft and professional books are somewhat cyclical. It's the only consumer cyclical part of our business. Third, we've seen enrollment challenges in select Wiley disciplines, namely computer science, down 8% in the fall semester. Computer science has been an important growth area for us, particularly with digital courseware. Fourth, corporate spending and hiring is soft, and that means lower consumption for our personality assessments and team development programs. Many of these factors are macro related, and we'll be watching how these trends play out for the balance of the year. From a mitigation standpoint, we're ruthlessly prioritizing to where we see upside, including inclusive access and other digital offerings, and instituting pricing strategies, category optimization, and targeted marketing campaigns. We expect learning declines to moderate in the second half as inventory actions stabilize, although revenue is expected to be down for the full year. Cost actions will help offset any top line impact. Let's turn to our key strategic priorities and value creators and the execution of our fiscal 26 commitments. As always, our first objective is to lead in research. It was a strong quarter for research, with 7% revenue growth in research publishing and 220 basis points of EBITDA margin improvement. We continue to drive above-market growth in submissions and output, up 28% and 12% respectively. Remember that 80% of our volume comes from outside the U.S., and strong demand is evident across all regions with double-digit submissions growth in China, India, Japan, the UK, Germany, and the U.S. Higher volumes are leading to both double-digit growth in author-funded open access and compounding growth in our recurring revenue models. Our second commitment is to deliver growth in AI and adjacent markets. We executed another licensing project for LLM training with 6 million realized in the quarter and 35 million year to date. On the innovation side, we're now at 30 plus publisher partners for our Nexus content licensing service, and we're in active discussions with others. As a reminder, this is where we combined our content with that of our publishing partners and licensed it to AI model and application developers. We also launched our AI gateway, an interoperable content enrichment and delivery platform in partnership with AI ecosystem players like Anthropic and AWS. Our corporate expansion continues with eight customers subscribing to our knowledge feeds with strong interest across multiple verticals. Our third commitment is to drive operational excellence and discipline across the organization. Craig will run through this in more detail, but we've made terrific progress in reducing our corporate costs and improving our research margin. We still have work to do, but we're pleased with our progress so far. Let's talk about our resiliency across economic cycles and AI as a tailwind. What makes research different? First, Peer-reviewed publishers set the global standard for scientific excellence, distinguishing solid research from world-changing discoveries. At the center of this ecosystem are wily journals, independently rated and widely recognized, forming a lasting competitive moat. Tens of millions of researchers worldwide know and trust these journals, and peer review is at the heart of it. An industry survey found that 94% of the researchers who participated believe peer review is essential for maintaining control and quality in scientific research. Second, peer reviewed content is must have for institutions and increasingly corporations through both good times and bad. Research is the core of a university. Over 10,000 research universities around the world subscribe to our portfolio of journals. Researchers at these institutions must have unfettered access to these journals, and they get it through multi-year digital licenses. Today, institutional customer retention is above 99%. In addition to universities, R&D-centric corporations are now exploring integrated feeds of this content for their AI models and applications. Third, publishing is essential for a researcher's career and for global recognition of scientific achievement. For example, tenure often requires seven to nine publications, and a strong publication record is key when applying for academic positions. Publishing in a top-tier journal brings international acclaim while also serving as the main way to demonstrate the impact of research and secure additional funding. Fourth, research output is ever-increasing, driven by global R&D spend. Remarkably, article output has grown every year since 1944, with the exception of a slight dip in 1971. Moreover, the rate of research output is expected to accelerate given the increasing importance of science and the rise of AI. Our analysis found that 84% of researchers are now using AI in their work, up from 57% last year. Another study showed a threefold increase in the number of papers by researchers who use AI. Fifth, research evolves constantly. An estimated 14,000 new articles are published daily worldwide, making recency critical for AI accuracy. In high-stakes fields like life sciences, AI systems must continuously incorporate the latest findings to remain reliable and effective. Finally, published research is protected under IP copyright law and its use must be authorized. We've talked about the Anthropic Copyright Settlement, the largest in US history. Beyond this, approximately 60 copyright lawsuits are currently underway involving AI. Let me run through our key differentiators as we transition to an AI economy. Why do we consider it a long-term tailwind and a growth engine? First, we provide access to much of the world's trusted scientific, technical, and medical content through our own portfolio and that of our publisher partners. We are a big three global publisher at a time when quality and scale matter most. We are further differentiated by our top position, in fast-growing knowledge domains, chemistry, material science, oncology, technology and engineering, food science, and finance and economics. We have strong, long-standing relationships with researchers, institutions, societies, and funders across the globe. We're the society partner of choice in the industry, and our platforms host nearly 50% of the world's English language journals. We're a first mover with LLM developers and corporations building out AI models and applications, so much so that other publishers want to be part of our licensing network. We're a pioneer in securing strategic relationships with the world's most advanced AI innovators, the first research publisher to be on the AWS marketplace and Claude for Life Sciences. Finally, rather than develop and compete through closed platforms, we're partnering with others through a CapEx Lite and open platform approach. This strategy allows us to leverage existing infrastructure and expertise while enabling broader collaboration across the research ecosystem. An open platform accelerates innovation by allowing multiple partners to contribute and build upon shared capabilities reduces our capital requirements, and creates network effects that benefit all participants, ultimately delivering more value to researchers than any single organization could achieve alone. Let me walk through our three growth factors, content, platforms, and markets, and the drivers underneath them. As you can see here, some of our drivers are enabled by lasting trends in our core research business, and some enabled by the use of AI. In content, we're expanding our journal portfolio and brands into fast-growing STM fields, as with our advanced brand. We continue to license our proprietary content and others for LLM models and corporate applications. In platforms, we have our research exchange publishing platform, our AI Gateway, and future growth opportunities with data products. I'll talk to the first two in the coming slides. On the third, we see proprietary data as a competitive mode over time as we deeply embed ourselves into the workflows of our corporate customers. For example, we have the most comprehensive spectral database collections in the world for chemists and other researchers. In markets, there are two growth drivers. The first is geographic, where we see a targeted opportunity to expand globally as China, India, and Brazil invest to become superpowers in science and technology. China is now the number one source of research output in the world. India and Brazil are showing strong double-digit submissions growth and expansive nationwide agreements. The second growth driver is building a significant presence in high stakes corporate research through the use of AI and data analytics. As noted, corporate makes up 80% of total U.S. R&D spend, but is only 10% of our revenue base today. Although it's early days, corporate R&D represents a substantial future growth opportunity for us. Let's take a step back and review our content licensing models. We think about the market in two ways. The first is licensing archival content to train large language models. This quarter we realized $6 million of licensing revenue with an existing LLM customer and $35 million year to date compared to approximately $40 million in fiscal 25. We continue to have active discussions with model developers, although these opportunities remain hard to project. The second wave is in licensing a knowledge feed of our content for vertical specific AI applications. R&D intensive corporations are then able to integrate this knowledge into workflows to identify breakthroughs, speed up product development, and lower costs. As noted, we currently have eight customers, including the European Space Agency, Novartis, and Regeneron, among others. We expect this number to ramp up as these vertical applications advance. Today we're in active discussions with companies ranging from energy to pharma to consumer staples. An example of our corporate expansion is our recent agreement with IQVIA, a leading provider of clinical research services to the life sciences industry. IQVIA will bundle our clinical outcome content with their clinical research capabilities to deliver one-stop solutions for pharmaceutical companies. It's an important example of the corporate R&D opportunity for Wiley as we turn knowledge into real-world impact. During the quarter, we continued to add partners to our Nexus licensing network and launched our AI Gateway content enrichment and distribution platform. On Nexus, we generated 16 million of revenue year-to-date, all of it in Q1, and continued to build out our partner network of 30-plus high-impact book and journal publishers with more in the pipeline. On to our AI Gateway. which is complementary with large language models. You can think of this service as a Wiley content repository that can be accessed by an API connector through platforms like AWS Marketplace and Claude for Life Sciences. Users with a subscription can run queries through the connector to retrieve highly relevant information from our platform. Importantly, as these involve retrieval augmented generation or RAG models, our content supplements the model to provide more accurate, trustworthy results, but is not absorbed in the model. Unlike closed ecosystems that require researchers to adopt proprietary tools, Wiley's AI Gateway is differentiated for its openness, partnerships, and interoperability. We also envision it for other publishers who want to leverage our technology and infrastructure to make their content available for corporate and other AI applications. We're currently in user trials with corporate R&D researchers and academic institutions. I'll turn to our research exchange platform where 65% of our journals are now live. The main point I want to emphasize is that this transformative publishing platform goes beyond efficiency and lowering our cost to publish. It's also about driving incremental revenue growth. As an example, the platform will deliver a best in class user experience from submission to acceptance, enabling us to attract new authors, drive more volume, and manage it more efficiently. With AI incorporated across the platform, we will improve submission capture, automate refer and transfer, and improve our turnaround times. As a reminder, about 70% of articles submitted to Wiley are rejected mainly due to improper fit. Through the AI functionality we introduced, we can now transfer these articles to more appropriate journals within our portfolio. We are rapidly scaling delivery of these new features and services. We believe that researchers and other professionals want trusted content that integrates with their own tools and their LLM of choice. And so we're partnering with AI ecosystem players, remaining agnostic and carving out our own critical niche. Recently, we added Mistral AI to our base and became the first research publisher to list a full-text agent knowledge base with AWS, enabling AI agents and applications on the AWS marketplace. We have won new corporate customers through the marketplace and are in active dialogue with others for our own subscription knowledge feeds. Also note, we are the first research publisher to have our connector featured on CLAWD. All good momentum. To summarize, I hope you can see why we're fully confident in our research core and excited about the expanding AI opportunities in front of us. I'll now turn the call over to Craig.