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Workday co-founder and CEO Aneel Bhusri called Oracle and SAP “dinosaurs” in a Digit.in report published October 14, 2026, arguing that their technology is outdated. The remark is competitive rhetoric, not an independent technical assessment. Bhusri’s underlying case is that enterprise AI must be tied to a unified, permission-aware system of record and deterministic workflows—an architecture he says Workday is building with its Sana agents.
What Bhusri said
Digit.in attributed this statement to Bhusri: “I have a lot of respect for SAP and Oracle, but I do think they’re dinosaurs. So I’ll just leave it there. I mean, they’ve built their businesses, but their technology is outdated.” The wording targets the companies’ legacy architecture and product history. It does not establish that either vendor lacks artificial-intelligence products, nor does it prove that Workday has broadly displaced either platform.
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No direct Oracle or SAP response to this specific characterization is established here, so the line should be read as Bhusri’s positioning of Workday against two long-standing enterprise-software rivals.
Why the comment matters now
Workday announced on February 9, 2026 that Bhusri would return as chief executive immediately, succeeding Carl Eschenbach. The company framed his return around its next phase in the rapidly changing AI era. In the same release, Bhusri said, “AI is a bigger transformation than SaaS — and it will define the next generation of market leaders.”
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Workday says it serves more than 11,000 organizations and more than 65% of the Fortune 500. Those are company-reported figures, useful for indicating scale but not independent proof of product superiority.
The architecture behind Bhusri’s argument
In an ITPro report dated March 18, 2026, Bhusri described enterprise applications as deterministic systems paired with probabilistic reasoning. His formulation was: “AI only works in the enterprise when it’s connected to trusted, deterministic systems, and that hybrid architecture is exactly what Workday is building.”
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Deterministic components enforce rules, permissions, policies and repeatable transactions. A payroll calculation, expense policy or schedule change must produce the permitted result every time. Probabilistic models are useful for interpreting a request, finding relevant information and proposing the next action, but they can generate different answers to the same prompt and can be wrong.
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Bhusri made that boundary explicit: “You can’t get it mostly right, you have to get it right every time. AI, for all of its power, is really a probabilistic and reasoning engine, and it will help to come up with solutions and answers on what step to take next.” His thesis is therefore less “Workday has a smarter chatbot” than “the AI is embedded in governed business processes.”
What Sana can do
Sana Self-Service Agent
ITPro reported that Workday’s Sana Self-Service Agent can use live data to automate tasks such as filing expenses, verifying pay cheques and changing worker schedules. These examples matter because the agent is not limited to drafting text: it can initiate or complete actions inside HR and finance workflows, subject to the underlying system’s controls.
Sana Enterprise
Sana Enterprise extends the conversational layer to third-party applications, including Salesforce, ServiceNow, Slack and Zoom, according to ITPro. That cross-application reach is intended to reduce the need for employees to switch systems, while Workday remains the source of governed workforce and financial data for relevant actions.
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Investment in the technology
ITPro reported that Workday’s November 2025 Sana Labs acquisition was worth approximately $1.1 billion. The transaction signals that Workday views conversational and agentic AI as a core product capability rather than a short-lived add-on.
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What adoption evidence Workday has disclosed
On its Q2 fiscal 2027 earnings call transcript dated August 27, 2026, Bhusri said Workday’s AI products generated more than $100 million in new annual contract value (ACV), representing over 25% of all new ACV in that quarter. He also said more than 5,500 customers were using one or more “organic agents.”
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| Measure | Figure | How to interpret it |
|---|---|---|
| AI-product new ACV | More than $100 million | Workday-reported new annual contract value in Q2 fiscal 2027 |
| Share of quarterly new ACV | More than 25% | Workday-reported proportion for that quarter, not a recurring run rate |
| Customers using organic agents | More than 5,500 | Workday-reported usage of at least one native agent; the disclosure does not establish depth, frequency or production outcomes |
These figures show commercial momentum and reported customer reach. They do not independently verify accuracy, return on investment, automation rates or whether deployments are running critical processes without human review.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is Workday actually ahead of Oracle and SAP?
The available evidence supports a narrower conclusion: Workday has articulated a coherent enterprise-AI strategy and disclosed substantial early adoption. It does not support a definitive ranking of the three companies across product capability, reliability, market share or customer outcomes.
| Comparison area | Workday’s stated position | What can responsibly be concluded |
|---|---|---|
| Data and application architecture | A unified context and data model connected to governed workflows | This is Bhusri’s characterization; no independent, apples-to-apples architecture test is provided |
| AI operating model | Permission- and policy-aware agents combined with deterministic transactions | A clear design principle, not proof that every agent performs reliably |
| Adoption | More than $100 million of AI new ACV and over 5,500 agent-using customers in Q2 fiscal 2027 | Company-reported traction; independent validation is not established |
| Workflow scope | HR, finance, payroll, recruiting and related service tasks, with third-party connections through Sana Enterprise | Documented examples show breadth, but not comparative coverage or outcomes versus rivals |
| Migration reality | Workday presents its architecture as a modern alternative | Oracle and SAP remain major enterprise platforms; the material does not show broad displacement |
What enterprise buyers should take from the dispute
- Check the system of record. An agent’s usefulness depends on current, permissioned data and clearly defined business rules.
- Separate advice from execution. Ask which actions the model may suggest, which it may execute, and where human approval is mandatory.
- Measure production outcomes. Customer counts and ACV indicate adoption, but buyers should also require error rates, auditability, time saved and rollback procedures.
- Account for integration costs. Cross-application agents can simplify work for employees, yet identity, permissions and data-governance projects still determine deployment difficulty.
- Do not equate “legacy” with unusable. Established platforms can remain valuable because of installed processes, controls, integrations and switching costs.
Bottom line
“Dinosaurs” is Bhusri’s deliberately provocative label for what he sees as Oracle’s and SAP’s older enterprise-application architecture. His substantive argument is that reliable enterprise AI needs probabilistic reasoning anchored to deterministic, governed systems. Workday’s Sana products and the company’s reported Q2 fiscal 2027 ACV and agent-usage figures show a serious push in that direction, but they are not independent proof that Workday is already ahead of Oracle and SAP in every dimension.
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