Agentic AI will be everywhere at Workday Rising 2026. But which conversations can move your AI strategy forward?

For leaders responsible for AI, analytics, finance, HR, IT, or the data connecting all of them, the most useful sessions will not talk about what AI could do. They will show what organizations are already doing, what it took to get there, and what they learned along the way.

Three areas stand out in Workday Intelligence this year: enterprise AI strategy, Workday’s growing agent ecosystem, and the data foundation required to make all of it work. 


1. AI strategy: the operating model behind the AI 
Where do agents belong in the org, and how do you get past a handful of pilots? How do you balance enterprise governance with departmental self-service? Should you Build or Buy? Several sessions at Rising will give leaders a chance to hear those answers from organizations already working through them.

• Anthropic on running finance with Workday and Claude during hypergrowth. 

• Highmark Health on using agents to fill 10,000 roles a year.

• Carlyle and Baird comparing two different ways of adopting AI in financial services.

• FactSet’s CIO on why AI results depend on the data behind them.

• FlexGen Power Systems with real savings numbers from Contract Intelligence.

2. Workday agents: the mechanics
For the past few years, “agentic AI” has been one of the industry’s favorite phrases. 
At Rising 2026, the conversation will become much more concrete. 

• Agent System of Record (ASOR). Once dozens of agents are acting across your processes, you need to know who approved each action, what data it touched and which policies applied.

• Developer Agent, including Workday’s own finance team building a custom Financials agent.

• Dr. Kelly Trindel, Workday’s Chief Responsible AI Officer, on governance for agents.

• Connecting Claude or another LLM to Adaptive through MCP. Most companies will run more than one model, so how those models connect to Workday safely matters.
  
  

3. Workday Data Cloud: the track that deserves more attention 
Agents are only as good as the data they can reach. If your AI roadmap is ahead of your data strategy, adding more agents just shows the gap sooner.

It is to put the right strategy, data, and operating model behind AI so it can deliver meaningful outcomes.