How Workday Uses AI to Power Employee Development

As organizations grapple with integrating artificial intelligence into their talent strategies, some companies are already leading the charge. Standing out among organizations is Workday, an HR platform using AI to transform its employee development. In a recent Udemy Business webinar, Workday Chief Learning Officer, Chris Ernst, shared three practical use cases that demonstrate how the company is combining AI and skills data to drive measurable business outcomes. In the article below, HR and L&D leaders will gain insights from Workday’s practical AI use cases in talent management that they can adapt for wherever their companies are in their own AI adoption journeys.

In the discussion with Udemy Chief Learning Officer, Melissa Daimler, Chris set the stage for understanding the connection between a company’s key business priorities, how skills can help address those priorities, and how AI can help bridge any skill gaps. He emphasized that skills data serves as a critical bridge between the capabilities of AI technology for HR purposes and talent development at Workday. Just as ingredients make up a recipe, skills provide the common data language of work that AI can understand and interpret. Once “skills ingredients” are provided, AI can then analyze skills relationships mapping them to employee aspirations like career growth, learning, and internal mobility, as well as job role requirements created by the company’s leadership.

Use case 1: AI-powered career mobility through gig work

Workday identified that employees who left the company were three times more likely to be dissatisfied with career growth opportunities. To reverse the trends in attrition, Chris’s team launched an AI-enabled internal gig marketplace to boost employee engagement by allowing employees to flex their skills on projects they typically wouldn’t work on in their-day-to-day role. 

With the internal gig marketplace, Workday created short-term project opportunities that used AI to match employee skills and interests to available projects. Team leaders were encouraged to not see gigs as a distraction for their employees, but rather a chance for their teams to become more skilled as well as opening their own projects to the gig marketplace.  

In addition to the scale AI brought to the program, the key to success was focusing on three personas: gig owners, gig workers, and people leaders, with targeted enablement for each group. In the first six months of the program, Workday hosted 5,000+ gigs across 20,000 employees. The company saw a 42% increase in internal mobility among gig participants, and higher employee retention one year after the gig was completed. 

“Start simple and soon,” advises Ernst. “Find a business need. Secure a sponsor. Run a pilot. Nothing builds momentum like early success.”

Use case 2: AI-accelerated skills validation

Thanks to the boost from AI, Workday spent just five months on a skills validation project that typically takes years. Now, 99% of jobs within Workday have a set of confirmed skills critical for the role, as validated by executives. The team accomplished what can be a time-consuming and highly manual project in four steps:

1. Used AI to generate initial sets of 30-40 relevant skills per job
2. People leaders rated and prioritized skills through quick surveys
3. Executives confirmed the final 10-12 critical skills per role
4. Validated skills were then integrated back into Workday talent systems

This AI-driven approach flipped the process from a typical 80% manual work to 80% of the work being automated, accelerating the project while maintaining quality.

Use case 3: Skills-based hiring transformation

When faced with an urgent need to hire account executives to sell new products, Workday piloted a skills-based hiring approach that delivered impressive results without heavy reliance on technology. The company filled its hiring needs quickly using its Workday Skills Cloud powered by AI. 

The technology allowed leaders to simplify account executive role requirements from 38 competencies to nine core skills. They then standardized the entire hiring process from sourcing to interviewing around the nine skills. In total, over 500 account executives were hired quickly thanks to the focused skills profile.

By acting fast with a novel approach to hiring, the sales team realized impressive results including a 32% decrease in time-to-hire, 11% increase in offer acceptance rates, and 51% higher candidate experience scores than its benchmark.

Learnings for companies at every stage of the AI journey 

Even organizations that don’t have AI as deeply integrated into its systems as Workday can learn from the use cases Chris highlighted in the webinar. When considering how to leverage AI across talent management stages, keep the following lessons from Chris and the Workday team in mind. 

1. Start with business problems: Focus on specific business challenges that skills and AI can help solve, rather than implementing technology for its own sake.
2. Take an iterative approach: Begin with pilots, secure executive sponsors, and demonstrate measurable results before scaling.
3. Prioritize data quality: Use every initiative as an opportunity to improve skills data quality. Remember: it’s an ongoing journey.
4. Build cross-functional alignment: Success came when Workday moved beyond HR-only implementation to engage all business functions in its skills strategy.

Looking ahead, Workday is focusing on democratizing AI skills across its workforce, with every employee setting “everyday AI” goals for the coming year. Their experience shows that combining AI with a skills-based approach can create a powerful engine for employee development and organizational agility.
For more AI insights from Workday CLO, Chris Ernst, and Udemy CLO, Melissa Daimler, watch the full discussion on-demand. View Udemy’s own in-product AI features to discover how we can help you create more engaging learning programs that skill up learners faster.