Peer-Reviewed Research Tackles Some of the Hardest Technical Challenges in Enterprise AIRecent Findings Reveal What It Takes to Ensure Agents Retain Only What Matters, Collaborate for Greater Accuracy, and Delete

<p xmlns="http://www.w3.org/1999/xhtml" class="prntac"><i xmlns="http://www.w3.org/1999/xhtml">Peer-Reviewed Research Tackles Some of the Hardest Technical Challenges in Enterprise AI</i></p><p xmlns="http://www.w3.org/1999/xhtml" class="prntac"><i xmlns="http://www.w3.org/1999/xhtml">Recent Findings Reveal What It Takes to Ensure Agents Retain Only What Matters, Collaborate for Greater Accuracy, and Delete Without a Trace</i></p><p xmlns="http://www.w3.org/1999/xhtml"><span xmlns="http://www.w3.org/1999/xhtml" class="legendSpanClass">PLEASANTON, Calif.</span>, <span xmlns="http://www.w3.org/1999/xhtml" class="legendSpanClass">Aug. 19, 2026</span> /PRNewswire/ -- <a xmlns="http://www.w3.org/1999/xhtml" href="https://www.workday.com/en-us/homepage.html" target="_blank" rel="nofollow">Workday, Inc</a>. (NASDAQ:<a class="ticker" href="https://www.benzinga.com/quote/WDAY">WDAY</a>), the enterprise AI platform for HR, finance, and IT, today announced Workday AI Research, a dedicated technical research team focused on advancing reliable, trustworthy, and efficient AI for the enterprise. Workday AI Research findings help shape AI development at Workday and contribute new evidence, methods, and evaluation practices to the broader research community.</p>
    <div xmlns="http://www.w3.org/1999/xhtml" class="PRN_ImbeddedAssetReference" id="DivAssetPlaceHolder1">
                <p xmlns="http://www.w3.org/1999/xhtml">
                    <img xmlns="http://www.w3.org/1999/xhtml" src="https://mmx.prnewswire.com/media/MS1321030/Workday-Logo-1.jpg?id=OA2895874" title="Workday" alt="Workday"></img>
                </p>
    </div>
<p xmlns="http://www.w3.org/1999/xhtml">Workday researchers have produced a growing body of work on challenges central to enterprise AI, including persistent agent memory, explainability, multi-agent orchestration, reward overoptimization in AI training, recommendation systems, and adaptive resource control. Recent work has been accepted by top conferences including the International Conference on Machine Learning, the International Conference on Learning Representations, the ACM Web Conference, and the Association for Computational Linguistics.</p><p xmlns="http://www.w3.org/1999/xhtml">&#34;As AI agents evolve to remember context and take action on behalf of employees, enterprises are facing complex challenges around privacy, auditability, efficiency, and enterprise-grade accuracy that off-the-shelf models simply cannot solve,&#34; said Gerrit Kazmaier, president, product and technology, Workday. &#34;Workday AI Research is dedicated to solving these exact problems, delivering the rigorous science needed to build intelligent, reliable systems that organizations can actually trust and deploy at scale.&#34;</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Developing the Next Generation of Enterprise AI Researchers</b></p><p xmlns="http://www.w3.org/1999/xhtml">To help fuel this research and deepen Workday&#39;s collaboration with the academic community, the company is also introducing the Workday AI Research PhD Fellowship to support exceptional doctoral students working at the intersection of AI and enterprise software. Fellows receive $50,000 in annual research funding through an unrestricted gift to their university, dedicated mentorship and direct collaboration with a Workday AI researcher, and early access to relevant career opportunities at Workday. Interested PhD candidates can find more details at <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/ai-research" target="_blank" aria-invalid="true" rel="nofollow">workday.com/ai-research</a>.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Recent Breakthroughs from Workday AI Research</b></p><p xmlns="http://www.w3.org/1999/xhtml">Workday AI Research is exploring some of the most important questions organizations face as they adopt AI:</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Can AI agents remember the right things without storing everything? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers developed a more selective approach to agent memory that helps AI keep useful information while filtering out outdated, duplicate, or unreliable details. In testing, the method delivered 12% higher precision and approximately 8% better overall memory quality, while retaining 97% of the memories that mattered. It also ran about 31% faster than the leading AI-driven comparison—showing that better memory can be both more useful and more efficient.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Can multiple AI agents make better decisions than one? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers found that splitting complex work among specialized agents improved both answer quality and compliance. In the study, one agent explored options, another focused on following the rules, and a coordinating agent directed their work. The approach improved accuracy by 5.8%, and every final answer met the study&#39;s defined constraints. The finding suggests that organizations do not have to choose between higher-quality AI recommendations and strong guardrails.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Does asking an AI agent to forget something actually make it forget? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers found that deleting information from an AI agent&#39;s memory does not always remove it for good. When researchers asked an agent to forget something, a copy of it was still recoverable from an old summary about one in five times. Fully erasing the information meant also deleting every summary that mentioned it—showing that &#34;forgetting&#34; in AI agents requires clearing every copy, not just the original record.</p><p xmlns="http://www.w3.org/1999/xhtml">While AI is quickly changing how businesses operate, organizations need systems they can trust to retain the right context, explain their recommendations dependably, and follow clear guardrails. By connecting rigorous AI science with real-world enterprise needs, Workday AI Research is helping build a new generation of AI tools that are useful, efficient, transparent, and ready for work.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">For More Information</b></p><ul xmlns="http://www.w3.org/1999/xhtml" type="disc"><li xmlns="http://www.w3.org/1999/xhtml">Visit <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/ai-research" target="_blank" aria-invalid="true" rel="nofollow">workday.com/ai-research</a> for a complete list of Workday AI research papers.</li><li xmlns="http://www.w3.org/1999/xhtml">Read our blog posts spotlighting recent Workday AI research:<ul xmlns="http://www.w3.org/1999/xhtml" type="circle"><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/what-makes-ai-dependable.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;What Makes AI Dependable? New Workday Study Puts This Question to The Test&#34;.</a></li><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/better-ai-results-split-work-across-agents.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;For Better AI Results, Split The Work Across Agents&#34;</a></li><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/research-shows-best-ai-memory.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;Research Shows The Best AI Memory Isn&#39;t Bigger. It&#39;s More Selective.&#34;</a></li></ul></li></ul><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">About Workday</b></p><p xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://www.workday.com/en-us/homepage.html" target="_blank" rel="nofollow">Workday</a> operates at the heart of the enterprise – HR, finance, and IT – where the margin for error is effectively zero. By tightly coupling AI with the context, guardrails, and trusted processes that run the business, Workday goes beyond AI that assists with work to agents that are capable of driving measurable outcomes. More than 11,500 organizations worldwide, including more than 65% of the Fortune 500, trust Workday to deliver. For more information about Workday, visit <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/" target="_blank" rel="nofollow">workday.com</a>.</p><p xmlns="http://www.w3.org/1999/xhtml">&#xA9; 2026 Workday, Inc. All rights reserved. Workday and the Workday logo are trademarks of Workday, Inc. All other brand and product names are trademarks or registered trademarks of their respective holders.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Forward-Looking Statements</b></p><p xmlns="http://www.w3.org/1999/xhtml">This press release contains forward-looking statements including, among other things, statements regarding Workday&#39;s plans, beliefs, and expectations. These forward-looking statements are based only on currently available information and our current beliefs, expectations, and assumptions. Because forward-looking statements relate to the future, they are subject to inherent risks, uncertainties, assumptions, and changes in circumstances that are difficult to predict and many of which are outside of our control. If the risks materialize, assumptions prove incorrect, or we experience unexpected changes in circumstances, actual results could differ materially from the results implied by these forward-looking statements, and therefore you should not rely on any forward-looking statements. Risks include, but are not limited to, risks described in our filings with the Securities and Exchange Commission (&#34;SEC&#34;), including our most recent report on Form 10-Q or Form 10-K and other reports that we have filed and will file with the SEC from time to time, which could cause actual results to vary from expectations. Workday assumes no obligation to, and does not currently intend to, update any such forward-looking statements after the date of this release, except as required by law.</p><p xmlns="http://www.w3.org/1999/xhtml">Any unreleased services, features, or functions referenced in this document, our website, or other press releases or public statements that are not currently available are subject to change at Workday&#39;s discretion and may not be delivered as planned or at all. Customers who purchase Workday services should make their purchase decisions based upon services, features, and functions that are currently available.</p>



<p xmlns="http://www.w3.org/1999/xhtml" id="PURL"><img xmlns="http://www.w3.org/1999/xhtml" title="Cision" width="12" height="12" alt="Cision" src="https://edge.prnewswire.com/c/img/favicon.png?sn=LA29269&amp;sd=2026-08-19"></img> View original content to download multimedia:<a xmlns="http://www.w3.org/1999/xhtml" id="PRNURL" rel="nofollow" href="https://www.prnewswire.com/news-releases/workday-introduces-ai-research-team-dedicated-to-advancing-reliable-trustworthy-and-efficient-enterprise-ai-302854831.html" target="_blank">https://www.prnewswire.com/news-releases/workday-introduces-ai-research-team-dedicated-to-advancing-reliable-trustworthy-and-efficient-enterprise-ai-302854831.html</a></p><p xmlns="http://www.w3.org/1999/xhtml">SOURCE Workday Inc.</p>

WDAY

Workday Introduces AI Research Team Dedicated to Advancing Reliable, Trustworthy, and Efficient Enterprise AI

Workday launches AI Research arm with enterprise AI reliability breakthroughs

<section class="insight" data-version="1">
  <section data-block="information">
    <h3>Information</h3>
    <p>Peer-Reviewed Research Tackles Some of the Hardest Technical Challenges in Enterprise AIRecent Findings Reveal What It Takes to Ensure Agents Retain Only What Matters, Collaborate for Greater Accuracy, and Delete</p>
  </section>

  <section data-block="ai-summary-paragraph">
    <h3>AI Summary</h3>
    <p>Workday announced the formation of Workday AI Research, a dedicated team to advance reliable, enterprise-grade AI. The release cites memory selectivity, multi-agent collaboration, and forgetfulness studies, plus a $50,000 annual PhD fellowship and a broad enterprise footprint. While near-term earnings impact is unclear, the initiative could strengthen product differentiation and support longer-term ARR growth.</p>
  </section>

  <section data-block="ai-summary-bullets">
    <h3>Key Points</h3>
    <ul><li>Workday launches Workday AI Research, a dedicated enterprise AI team.</li><li>Memory selectivity yields 12% higher precision, 97% essential-memory retention, 31% speed gain.</li><li>Multi-agent orchestration boosts accuracy by 5.8% with guardrails; forgetting study shows full erase needed.</li><li>PhD Fellowship offers $50,000/year; 11,500+ customers and 65% Fortune 500 exposure.</li></ul>
  </section>

  <section data-block="companies-mentioned">
    <h3>Companies Mentioned</h3>
    <ul><li><strong>Workday, Inc. (WDAY)</strong>: Initiating Workday AI Research; potential for long-term product differentiation and ARR uplift.</li><li><strong>Workday AI Research (WDAY-AR)</strong>: Internal program; not a public issuer but signals deeper AI roadmap and research pipeline.</li></ul>
  </section>

  <section data-block="category">
    <h3>Corporate Developments</h3>
    <p>Category: Corporate Developments. The content describes a strategic AI-focused initiative and talent development program that could influence Workday’s competitive positioning and future financials, albeit with no immediate revenue guidance.</p>
  </section>

  <section data-block="market-moving">
    <h3>Market-Moving</h3>
    <ul><li>AI research leadership may enhance Workday’s product differentiation and long-term revenue trajectory.</li><li>Reported metrics imply higher ROI for AI-enabled features, potentially supporting pricing power.</li><li>PhD fellowship and expanded talent pool could elevate innovation but add modest SG&amp;A in early years.</li><li>Large installed base (11,500+ customers; 65% Fortune 500) provides upside for AI-driven upsell.</li></ul>
  </section>

  <section data-block="key-facts">
    <h3>Key Facts</h3>
    <ul><li>Date of press release: Aug 19, 2026.</li><li>Company: Workday, Inc. (NASDAQ: WDAY).</li><li>Announcement: Workday AI Research established with dedicated research team.</li><li>Memory result: 12% higher precision; ~8% better memory quality; 97% memories retained.</li><li>Performance: AI memory method ran ~31% faster than leading AI-driven comparison.</li><li>Multi-agent result: 5.8% higher accuracy with specialized agents working together.</li><li>Forgetting finding: 1 in 5 recoverable copies; complete erase requires clearing all copies.</li><li>PhD Fellowship: $50,000 annual research funding; mentorship and early Workday opportunities.</li></ul>
  </section>

  <section data-block="trading-thesis">
    <h3>Trading Thesis</h3>
    <p>Long-term positive; AI leadership could boost ARR and retention over the next 12–24 months.</p>
  </section>
</section>


<p xmlns="http://www.w3.org/1999/xhtml" class="prntac"><i xmlns="http://www.w3.org/1999/xhtml">Peer-Reviewed Research Tackles Some of the Hardest Technical Challenges in Enterprise AI</i></p><p xmlns="http://www.w3.org/1999/xhtml" class="prntac"><i xmlns="http://www.w3.org/1999/xhtml">Recent Findings Reveal What It Takes to Ensure Agents Retain Only What Matters, Collaborate for Greater Accuracy, and Delete Without a Trace</i></p><p xmlns="http://www.w3.org/1999/xhtml"><span xmlns="http://www.w3.org/1999/xhtml" class="legendSpanClass">PLEASANTON, Calif.</span>, <span xmlns="http://www.w3.org/1999/xhtml" class="legendSpanClass">Aug. 19, 2026</span> /PRNewswire/ -- <a xmlns="http://www.w3.org/1999/xhtml" href="https://www.workday.com/en-us/homepage.html" target="_blank" rel="nofollow">Workday, Inc</a>. (NASDAQ:<a class="ticker" href="https://www.benzinga.com/quote/WDAY">WDAY</a>), the enterprise AI platform for HR, finance, and IT, today announced Workday AI Research, a dedicated technical research team focused on advancing reliable, trustworthy, and efficient AI for the enterprise. Workday AI Research findings help shape AI development at Workday and contribute new evidence, methods, and evaluation practices to the broader research community.</p>
    <div xmlns="http://www.w3.org/1999/xhtml" class="PRN_ImbeddedAssetReference" id="DivAssetPlaceHolder1">
                <p xmlns="http://www.w3.org/1999/xhtml">
                    <img xmlns="http://www.w3.org/1999/xhtml" src="https://mmx.prnewswire.com/media/MS1321030/Workday-Logo-1.jpg?id=OA2895874" title="Workday" alt="Workday"></img>
                </p>
    </div>
<p xmlns="http://www.w3.org/1999/xhtml">Workday researchers have produced a growing body of work on challenges central to enterprise AI, including persistent agent memory, explainability, multi-agent orchestration, reward overoptimization in AI training, recommendation systems, and adaptive resource control. Recent work has been accepted by top conferences including the International Conference on Machine Learning, the International Conference on Learning Representations, the ACM Web Conference, and the Association for Computational Linguistics.</p><p xmlns="http://www.w3.org/1999/xhtml">&#34;As AI agents evolve to remember context and take action on behalf of employees, enterprises are facing complex challenges around privacy, auditability, efficiency, and enterprise-grade accuracy that off-the-shelf models simply cannot solve,&#34; said Gerrit Kazmaier, president, product and technology, Workday. &#34;Workday AI Research is dedicated to solving these exact problems, delivering the rigorous science needed to build intelligent, reliable systems that organizations can actually trust and deploy at scale.&#34;</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Developing the Next Generation of Enterprise AI Researchers</b></p><p xmlns="http://www.w3.org/1999/xhtml">To help fuel this research and deepen Workday&#39;s collaboration with the academic community, the company is also introducing the Workday AI Research PhD Fellowship to support exceptional doctoral students working at the intersection of AI and enterprise software. Fellows receive $50,000 in annual research funding through an unrestricted gift to their university, dedicated mentorship and direct collaboration with a Workday AI researcher, and early access to relevant career opportunities at Workday. Interested PhD candidates can find more details at <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/ai-research" target="_blank" aria-invalid="true" rel="nofollow">workday.com/ai-research</a>.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Recent Breakthroughs from Workday AI Research</b></p><p xmlns="http://www.w3.org/1999/xhtml">Workday AI Research is exploring some of the most important questions organizations face as they adopt AI:</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Can AI agents remember the right things without storing everything? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers developed a more selective approach to agent memory that helps AI keep useful information while filtering out outdated, duplicate, or unreliable details. In testing, the method delivered 12% higher precision and approximately 8% better overall memory quality, while retaining 97% of the memories that mattered. It also ran about 31% faster than the leading AI-driven comparison—showing that better memory can be both more useful and more efficient.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Can multiple AI agents make better decisions than one? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers found that splitting complex work among specialized agents improved both answer quality and compliance. In the study, one agent explored options, another focused on following the rules, and a coordinating agent directed their work. The approach improved accuracy by 5.8%, and every final answer met the study&#39;s defined constraints. The finding suggests that organizations do not have to choose between higher-quality AI recommendations and strong guardrails.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml"><i xmlns="http://www.w3.org/1999/xhtml">Does asking an AI agent to forget something actually make it forget? <br xmlns="http://www.w3.org/1999/xhtml"></br></i></b>Workday researchers found that deleting information from an AI agent&#39;s memory does not always remove it for good. When researchers asked an agent to forget something, a copy of it was still recoverable from an old summary about one in five times. Fully erasing the information meant also deleting every summary that mentioned it—showing that &#34;forgetting&#34; in AI agents requires clearing every copy, not just the original record.</p><p xmlns="http://www.w3.org/1999/xhtml">While AI is quickly changing how businesses operate, organizations need systems they can trust to retain the right context, explain their recommendations dependably, and follow clear guardrails. By connecting rigorous AI science with real-world enterprise needs, Workday AI Research is helping build a new generation of AI tools that are useful, efficient, transparent, and ready for work.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">For More Information</b></p><ul xmlns="http://www.w3.org/1999/xhtml" type="disc"><li xmlns="http://www.w3.org/1999/xhtml">Visit <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/ai-research" target="_blank" aria-invalid="true" rel="nofollow">workday.com/ai-research</a> for a complete list of Workday AI research papers.</li><li xmlns="http://www.w3.org/1999/xhtml">Read our blog posts spotlighting recent Workday AI research:<ul xmlns="http://www.w3.org/1999/xhtml" type="circle"><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/what-makes-ai-dependable.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;What Makes AI Dependable? New Workday Study Puts This Question to The Test&#34;.</a></li><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/better-ai-results-split-work-across-agents.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;For Better AI Results, Split The Work Across Agents&#34;</a></li><li xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://blog.workday.com/en-us/research-shows-best-ai-memory.html" target="_blank" aria-invalid="true" rel="nofollow">&#34;Research Shows The Best AI Memory Isn&#39;t Bigger. It&#39;s More Selective.&#34;</a></li></ul></li></ul><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">About Workday</b></p><p xmlns="http://www.w3.org/1999/xhtml"><a xmlns="http://www.w3.org/1999/xhtml" href="https://www.workday.com/en-us/homepage.html" target="_blank" rel="nofollow">Workday</a> operates at the heart of the enterprise – HR, finance, and IT – where the margin for error is effectively zero. By tightly coupling AI with the context, guardrails, and trusted processes that run the business, Workday goes beyond AI that assists with work to agents that are capable of driving measurable outcomes. More than 11,500 organizations worldwide, including more than 65% of the Fortune 500, trust Workday to deliver. For more information about Workday, visit <a xmlns="http://www.w3.org/1999/xhtml" href="http://workday.com/" target="_blank" rel="nofollow">workday.com</a>.</p><p xmlns="http://www.w3.org/1999/xhtml">&#xA9; 2026 Workday, Inc. All rights reserved. Workday and the Workday logo are trademarks of Workday, Inc. All other brand and product names are trademarks or registered trademarks of their respective holders.</p><p xmlns="http://www.w3.org/1999/xhtml"><b xmlns="http://www.w3.org/1999/xhtml">Forward-Looking Statements</b></p><p xmlns="http://www.w3.org/1999/xhtml">This press release contains forward-looking statements including, among other things, statements regarding Workday&#39;s plans, beliefs, and expectations. These forward-looking statements are based only on currently available information and our current beliefs, expectations, and assumptions. Because forward-looking statements relate to the future, they are subject to inherent risks, uncertainties, assumptions, and changes in circumstances that are difficult to predict and many of which are outside of our control. If the risks materialize, assumptions prove incorrect, or we experience unexpected changes in circumstances, actual results could differ materially from the results implied by these forward-looking statements, and therefore you should not rely on any forward-looking statements. Risks include, but are not limited to, risks described in our filings with the Securities and Exchange Commission (&#34;SEC&#34;), including our most recent report on Form 10-Q or Form 10-K and other reports that we have filed and will file with the SEC from time to time, which could cause actual results to vary from expectations. Workday assumes no obligation to, and does not currently intend to, update any such forward-looking statements after the date of this release, except as required by law.</p><p xmlns="http://www.w3.org/1999/xhtml">Any unreleased services, features, or functions referenced in this document, our website, or other press releases or public statements that are not currently available are subject to change at Workday&#39;s discretion and may not be delivered as planned or at all. Customers who purchase Workday services should make their purchase decisions based upon services, features, and functions that are currently available.</p>



<p xmlns="http://www.w3.org/1999/xhtml" id="PURL"><img xmlns="http://www.w3.org/1999/xhtml" title="Cision" width="12" height="12" alt="Cision" src="https://edge.prnewswire.com/c/img/favicon.png?sn=LA29269&amp;sd=2026-08-19"></img> View original content to download multimedia:<a xmlns="http://www.w3.org/1999/xhtml" id="PRNURL" rel="nofollow" href="https://www.prnewswire.com/news-releases/workday-introduces-ai-research-team-dedicated-to-advancing-reliable-trustworthy-and-efficient-enterprise-ai-302854831.html" target="_blank">https://www.prnewswire.com/news-releases/workday-introduces-ai-research-team-dedicated-to-advancing-reliable-trustworthy-and-efficient-enterprise-ai-302854831.html</a></p><p xmlns="http://www.w3.org/1999/xhtml">SOURCE Workday Inc.</p>

Workday announced the formation of Workday AI Research, a dedicated team to advance reliable, enterprise-grade AI. The release cites memory selectivity, multi-agent collaboration, and forgetfulness studies, plus a $50,000 annual PhD fellowship and a broad enterprise footprint. While near-term earnings impact is unclear, the initiative could strengthen product differentiation and support longer-term ARR growth.

News insight

Workday Introduces AI Research Team Dedicated to Advancing Reliable, Trustworthy, and Efficient Enterprise AI

AI summary

Sentiment rationale

Key facts

Corporate Developments