How AI and ML Are Powering the Future of Work

At Workday, we’ve embedded AI and ML into the very core of our platform—delivering unrivaled business adaptability and competitive advantage to our customers. Here’s how.

Workday’s Unique Approach to AI and ML

Workday thinks about and implements AI and ML differently than any other enterprise software company in the world. From a capabilities perspective, Workday takes a platform-first approach that embeds AI and ML into the very core of our technology platform. Why does this matter? It matters because it allows us to rapidly deliver and sustain new ML-infused capabilities into our applications. ML gets better the more you use it, and by having millions of users constantly using dozens of applications on the same platform, it improves at a faster rate.

Workday’s other differentiator is the data we have and the special care we take of it. The sheer quantity of customer data we have access to is enormous—over 60 million users representing about 442 billion transactions a year. But quantity means nothing without quality, which we enforce with our comprehensive single data model. This data model allows us to maintain clean and coherent data in a way our competitors—who rely on multiple integrations of different data repositories—cannot. We also use a tenanted model to structure our data, which uniquely allows us to build tailored models for customers in a specific region or industry through federated learning, all while maintaining the necessary privacy and regulatory rules. And lastly, we can bring in third party data with Workday Prism Analytics and merge it with Workday’s unparalleled data set to create unique models no one else can.

In ML, practitioners talk about the “3 Vs” of data needed to drive positive outcomes: sufficient volume, velocity, and variety. Workday has all three. The combination of Workday’s unique data and technology capabilities allows us to deploy AI and ML solutions with high performance and better tailored use cases, quickly delivering rapid and differentiated outcomes for our customers.

Enabling the Future of Work with AI and ML

A great example of how our unique approach comes to life is Workday Skills Cloud, our ML capability for enabling the future of work. As we reach the limits of traditional career trajectories, credentials, degrees, and formal resumes, the future economy must be much more dynamic, flexible, and capable of allowing people with nontraditional backgrounds to participate effectively. Skills Cloud uses AI and ML to analyze the way skills are used in human language, understanding their relationship to each other, and mapping that to a skills-centric workforce at scale.

Workday Skills Cloud, and the ML engines that power it, are essential to enabling our customers to live in this new world. So much so that over half of our core Workday Human Capital Management (HCM) customers are using it. Workday’s Skills Cloud has processed over five billion uses of skills since its launch five years ago. There’s simply no way for companies to adopt skills at scale without ML.

Applying AI and ML is equally essential to the future of finance. With AI and ML, finance teams can get help managing risk and eliminating inefficiencies by reducing what used to take months or weeks down to just hours or minutes.

For example, finance teams spend an inordinate amount of time gathering information and reconciling transactions throughout the month and at quarter close. Workday AI and ML help them quickly identify financial patterns, trends, and anomalies—enabling teams to complete the financial close process more quickly and efficiently.

Unlimited Possibilities for Generative AI

There are unlimited possibilities to how AI and ML will impact the future of work, especially now with Generative AI. Workday was an early adopter of large language models (LLMs), the technology that has enabled Generative AI, and we use them in production today. We have started adopting Generative AI at Workday to solve a host of additional customer challenges. A canonical case for LLMs is content creation, and we can see how drafting performance reviews, job descriptions, and a host of other documents will be transformed by this approach. We’re going to continue to identify key use cases where Generative AI can add value to our customers and develop unique models that leverage both Workday data and external data sets.

Delivering Confident Decisions With Trustworthy AI

We believe that for AI and ML to really deliver on the possibilities it offers, it must be trustworthy and it must augment humans, not displace them. In order for AI and ML to be trustworthy, trust must be designed into the very foundation. As one of the world’s most ethical companies, we’re committed to responsible AI. We provide our customers with a clear understanding of how our ML products are developed and assessed in order to help mitigate any risks associated with their use. Our key ethical AI and ML principles serve as the cornerstone of our work in this space, and guide us in the development of AI and ML technologies that drive positive societal outcomes and expand growth opportunities for our customers and their employees.

With a guiding principle to keep humans at the center, no decision is fully automated by Workday’s AI and ML technology, and our practices ensure that people are the final decision-makers. We commit to maintaining our human-in-the-center approach, using AI and ML to make people more productive, better informed, and enabling them to solve problems they didn't think they could solve before.This is the promise of AI and ML, and we’re just getting started with imagining how it will shape the future of how we work.