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 has long believed that artificial intelligence (AI) and machine learning (ML) will power the future of work. While recent advancements in AI and ML – mainly with Generative AI, specifically OpenAI and ChatGPT – are causing everyone to jump on the AI and ML bandwagon, Workday has been building and delivering AI and ML capabilities to our customers for nearly a decade.
Workday’s Unique Approach to AI and ML
Workday has a unique perspective on how AI and ML can be implemented. 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 how we take care of it. The sheer quantity of customer data we have access to is enormous – more than 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: 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 resumés, the future economy must be much more dynamic, flexible and capable of allowing people with non-traditional backgrounds to participate effectively. Skills Cloud uses AI and ML to analyse 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 more than half of our core Workday Human Capital Management (HCM) customers are using it. Workday’s Skills Cloud has processed more than 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 faster and more efficiently.
By embedding AI and ML natively into our platform, Workday Financial Management enables intelligent automation to process high-volume transactions faster – further improving accuracy while delivering measurable business impact.
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 augment humans, not displace them. 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 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 centre, 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-centre approach, using AI and ML to make people more productive, better informed and able 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.
