Workday has launched Workday AI Research, a dedicated AI research team focused on developing reliable, trustworthy, and efficient AI for the enterprise.
The new team is tasked with addressing some of the technical challenges emerging around AI agents. Some of its researchers have already produced work accepted by major AI research conferences.
The launch comes as enterprises enter a more challenging phase of AI adoption, with businesses increasingly looking beyond experimentation and asking what is required to deploy AI agents reliably at scale.
Workday Targets Enterprise AI's Toughest Problems
Workday said its research will focus on technical problems that become increasingly important as AI agents gain the ability to retain context, make decisions, and act on behalf of employees.
One area of research is agent memory. Workday researchers developed a more selective approach designed to retain useful information while filtering out outdated, duplicated, or unreliable details. The method delivered 12% higher precision and around 8% higher overall memory quality in testing, while retaining 97% of the memories judged important. It also operated around 31% faster than the AI-based comparison used in the study.
The research also examines whether multiple specialized agents can produce better outcomes than a single agent. Workday found that dividing complex tasks between agents with different responsibilities improved accuracy by 5.8%, while ensuring that every final answer in the study met its defined constraints.
The findings also raise questions about how enterprises will govern information held by AI agents. Workday investigated whether an AI agent can genuinely forget information when instructed to do so, finding that information remained recoverable from an old summary around one in five times after the original memory had been deleted. Completely removing the information required the summaries containing it to be deleted as well.
To fuel further research, Workday is establishing a PhD fellowship to deepen its links with academia. The program will provide $50,000 in annual research funding through an unrestricted university gift, alongside mentorship from Workday researchers and opportunities to collaborate with the company.
AI Vendors Face a New Adoption Problem
The launch comes at a difficult point for the enterprise AI market. Businesses and technology providers are increasingly focused on whether AI agents can deliver enough value, reliability, and control to support wider deployment.
Gartner's forecast that more than 40% of agentic AI projects could be canceled by the end of 2027 highlights the uncertainty surrounding the market. The research firm attributes the cancellations to escalating costs, unclear business value, and inadequate risk controls.
That creates a problem for the companies selling enterprise AI. The commercial opportunity depends not simply on organizations experimenting with AI, but on them deploying it deeply enough to generate sustained value. For Workday, which is increasingly positioning AI agents across its HR and finance platform, making those systems reliable enough for enterprise use could therefore be critical to turning AI interest into sustained adoption.
