Workday is making a dramatic strategic shift toward becoming the central platform for AI agent management in enterprises, according to CTO Peter Bailis in an exclusive interview at Workday Rising US 2025. The company’s ambitious vision extends far beyond traditional HR and finance applications, positioning itself to compete directly with tech giants like Salesforce, ServiceNow, and SAP in the rapidly evolving AI platform space.
The Agent System of Record vision
Bailis introduced Workday’s concept of an “agent system of record” – a natural extension of their existing role as the system of record for people and money. Just as Workday currently manages employee data, organizational structures, and financial information, the company now aims to govern AI agents with the same level of control and security.
“The same construct you have for people, for the people system of record, extending that to agents is actually quite nice,” Bailis explained. “What department is this agent a part of? I can assign it an ID through Workday or through a service like Microsoft Entra ID. The protocols for authenticating people already exist, so being able to have a system of record for agents is really convenient.”
Strategic acquisitions fuel platform ambitions
Workday’s platform strategy is being accelerated through three major acquisitions, each targeting different aspects of the AI agent ecosystem. The most significant is Sana, acquired for $1,1 billion, which brings enterprise search capabilities and what Bailis calls “an amazing UI for AI.”
Flowise, an open-source toolkit with 40,000 GitHub stars, provides drag-and-drop agent building capabilities for less technical users. Meanwhile, Paradox adds recruiting automation, processing 31 million candidate screens annually, or “one per second,” as Bailis noted.
Bailis believes, they are laying the foundation for a radically different way of working. AI will change how people are working. These acquisitions help them get the right technology and talent to build this new platform and a different way of working. About the acqusitions he says: “recognized there’s some great talent where they can accelerate our vision by 12, 18, 24 months and by the way, you know, bring that founder mode energy to this company.”
The acquisitions create a comprehensive toolkit spanning low-code (Flowise), pro-code (Extend), and enterprise search (Sana) capabilities.
Taking on the tech giants
Bailis acknowledges the ambitious nature of competing with established enterprise platforms but argues Workday has unique advantages. With 75 million monthly users and wall-to-wall presence in organizations, Workday touches every employee through payroll, time off, promotions, and performance reviews.
“We’re not like a narrow SaaS application. We are wall to wall inside of an organization,” Bailis emphasized. “When you have HCM and finance, you have the full system of record, the general ledger of the company […] the most important part of the company, the employees of the company and the money for the company that’s in Workday.”
The company’s efficiency advantages also play a role in their competitive strategy. Bailis notes that while competitors may have larger teams, “the future of software is built by cracked teams of software engineers running on the latest coding AI.” Workday has doubled the number of developers building on their platform via customers and partners while keeping internal development teams lean and highly productive.
Open Data Strategy
Recognizing that customers need flexibility, Workday announced Workdata Data Cloud, an open data lake built on Iceberg format with zero-copy architecture. This enables customers to query Workday data directly, eliminating the need for data extraction and addressing long-standing integration challenges.
“Workday’s never had an open platform like that,” Bailis admitted, acknowledging past customer frustrations with data access. The new approach maintains security while enabling real-time analytics and AI applications. Launch partners include Snowflake, Databricks and Salesforce, demonstrating Workday’s commitment to ecosystem collaboration even with competitors.
The future of enterprise search
Bailis believes enterprise search will become the “new browser tab” for knowledge workers, replacing traditional communication platforms as the primary work interface. This vision drives the SANA acquisition, which Bailis considers the best enterprise search and knowledge management platform available.
“Pre-LLMs, enterprise search was dead on arrival due to lack of training data and query ambiguity,” Bailis explained. “But now with foundation models, you can bridge that gap on smaller, per-customer data regimes. The category that VCs wouldn’t touch is suddenly wide open.”
Technical foundations and protocols
On the technical side, Workday is working with emerging agent protocols like MCP (Model Context Protocol) while advocating for more sophisticated standards. Bailis compared the current state to “IP-level networking” and expressed excitement about developing “the HTTP for enterprise SaaS in the AI era.”
Key technical innovations include delegate permissions for agents using OAuth standards and integration with identity providers like Microsoft Entra. This allows organizations to maintain security and governance as AI agents operate on behalf of human users.
Execution challenges ahead
Despite the bold vision, Bailis acknowledges the challenges ahead in execution. The strategy represents a significant departure from Workday’s traditional supporting role in enterprise IT, positioning the company as a primary platform for AI development rather than just an integration partner.
“The ambition we have as a management team at Workday is massive. We’re going to run the table, and it all comes down to execution”, Bailis concluded. “If we can build the best product, the best product experience, and we can distribute it, I think it’s incredible.”
With this ambitious roadmap, Workday is betting that its unique combination of organizational data, user reach, and AI-first acquisitions can establish it as a major platform player in the enterprise AI revolution. The success of this strategy will largely depend on their ability to execute against well-funded and much bigger competitors while maintaining their core strengths in people and financial management.