Workday used its EMEA AI Innovation Event in Dublin to outline its vision of the impact of AI for enterprises. Essentially, the company outlined its view that AI isn’t a bolt-on feature, it’s becoming the front door to work. Furthermore, the technology must be grounded in trustworthy enterprise data, rigorous security, and ‘Responsible AI.’

Over two days, Workday leaders, customers, and partners gathered to explore how AI and agents are reshaping HR, finance operations. The event highlighted Workday’s investment in Ireland, its expanding European footprint, and a rapidly maturing AI platform centred on Sana, Workday’s unified AI layer for work.

Ireland as a Strategic AI Centre

Workday’s Ireland operation began 16 years ago with the acquisition of Cape Clear and has since grown from 26 employees to more than 2,200, with around 80% working in product and technology roles.

In October, it announced an AI Centre of Excellence in Dublin, alongside a significant new investment of $175m to accelerate growth and innovation in Europe. “We have deep, meaningful relationships with the ecosystem here, especially with nearby universities,” said Graham Abell, Workday’s VP Software Engineering.

“That’s not just about workforce development and AI and Machine Learning skills. It’s also about bringing local European perspectives into how we build and govern AI,” he added.

Workday also confirmed plans to relocate its Dublin teams to a new EMEA headquarters beside Trinity College Dublin. The relocation will effectively double its current office footprint.

AI strategy: Deterministic enterprise data meets powerful models

Workday’s product and AI leaders framed this moment as significant as the shift from on-premises to cloud. However, with far higher stakes for trust, compliance, and accuracy.
“We were there for the transition from on premise to cloud over 20 years ago. As a result, we take this moment just as seriously,” said Kathy Pham, Workday’s VP, AI.

“Generic AI knows what’s on the public internet. It doesn’t know your financial records, your HR information, your planning processes. Our job is to bring a deterministic perspective to what is probabilistic in AI.”

Workday’s AI strategy is built on four pillars:

1. Front Door to Work – An intelligent entry point where employees can ask questions, get answers, and complete tasks.
2. Transforming Core HR and Finance – Embedding AI into Workday’s foundational HR and finance products.
3. Unleashing the Ecosystem – Enabling customers, partners, and developers to build on Workday’s AI and data platform.
4. Driving Market Excellence – Continuing to lead in cloud HR and finance while meeting evolving regulatory and trust requirements.

“These agents need to understand real work – trusted business processes, security, permissions, and audit trails.

“You don’t want any AI agent seeing information it’s not supposed to. That’s what enterprise systems must design for,” Pham added.

Sana: AI as the front door to work

At the heart of Workday’s agentic strategy is Sana, described as the unified AI platform for work. The “front door” to enterprise workflows.

“Today, work is more complex than it should be. Too many systems, too much toggling between tools, too much time figuring out how to get work done instead of doing it,” Pierre Gousset, VP Solution. “Think of Sana as the unified AI platform for work – the intelligent entry point that makes everything else in the platform accessible and actionable.”

Sana enables four core capabilities:

• Find – Ask questions and get contextual answers grounded in trusted Workday data (e.g., “What is my PTO balance?”)
• Act – Take actions across systems, such as updating Salesforce directly from a Microsoft Teams meeting transcript.
• Build – Generate dashboards, reports, and documents instantly from live data.
• Automate – Create and execute multi-step workflows that run autonomously, such as automated expense creation and approvals.

“This is the new type of experience where AI is the UI,” said Gousset. “You replace thousands of different systems with a conversational experience that not only answers questions but truly executes work end-to-end. Execution grounded in your context, your teams, your processes, and your tools.”

Enterprise-grade agents for HR and finance

Workday highlighted several domain-specific agents that are already delivering measurable impact for customers:

• Recruiting Agent: Streamlines recruiter workflows, screens and prioritizes candidates, and “rediscovers” past applicants. The company says this results in a 17% decrease in time-to-fill and a 54% increase in recruiter capacity.
• Payroll Agent: Unifies pay data, context, and compliance logic, reducing the time to answer complex payroll questions to under a minute. The solution delivers 75% faster analysis of minimum wage changes.
• Frontline Worker Agent: Conversationally fills shifts via channels such as SMS, achieving 90% reduction in time finding replacements and significantly cutting understaffed hours.
• Sana Self-Service HR Agent: Provides personalised, always-on HR support, reducing HR case volumes by up to 25% and improving employee experience.

“Being inaccurate is not an option for us,” said Claire Hickie, CTO in EMEA. “You can’t be 95% accurate in payroll or in compliance – that’s not ‘mostly right,’ it’s wrong. Everything we deliver must be precise, compliant, and trusted.

“We have a uniform data model, configurable business processes, and a security and privacy framework that everything leans on,” Hickie added. “From an AI perspective, we have both the data and the context – our agents understand skills, approvals, decision lines, and where the real friction points are.”

Unified foundation, regulation, and EU Sovereign Cloud

In Europe, regulatory shifts such as the EU Pay Transparency Directive are accelerating demand for trustworthy, integrated data platforms. Workday emphasised that its AI capabilities sit atop a unified HR and finance platform.

Workday’s Pay Transparency Analyzer leverages company data and loads external data into Workday. Any external data can be linked to job architecture and HR data. The solution helps organisations identify pay gaps, ensure compliance with regulations like the EU Pay Transparency Directive, and foster equitable compensation practices. It consolidates pay, performance, and demographic data to analyse discrepancies and recommend corrective actions.

“You can’t meet these new transparency expectations if your data is fragmented across silos,” said a Workday product leader. “We’re turning complex legal requirements into an opportunity to be talent-first, not just compliance-first,” said Gousset.

To address growing sovereignty expectations, Workday has introduced the Workday EU Sovereign Cloud, designed for customers who require Workday to run under EU-only controls and operations, while still leveraging the scale of AWS infrastructure.

“Trust is the currency today,” Gousset adds. “Sovereignty now means more than just where data is stored. Customers want to know exactly who operates the infrastructure and who can access their data.”

Workday build and Sana Agent Builder: opening the ecosystem

Workday is also expanding its developer ecosystem through Workday Build. The solution allows partners, customers, and developers to create applications and AI agents on top of Workday’s platform.

“It’s built on top of the Workday cloud, with zero-copy, bi-directional data sharing,” said Pham. “You get AI-ready data at scale with Workday’s governance and security, and real-time connectivity back into HR and finance,” she added.

The Sana Agent Builder is built on top of the open-source Flowise project and offers:

• A low-code interface where HR and finance leaders can design agents by dragging and connecting visual components.
• Model-agnostic orchestration, using the best underlying models for each task (e.g., from providers like Google, Anthropic, OpenAI).
• Connectivity to 3,000+ external platforms across the Workday ecosystem.

“We want to empower developers who’ve never touched Workday before to build on our technology, governance, and security,” Pham explained. “This is about unleashing a whole new wave of enterprise AI capabilities.”

Responsible AI: A non negotiable requirement

Closing the event, Workday leaders stressed that Responsible AI is foundational, not optional.

“It’s probably the most important part of this process, because without responsible AI, we simply wouldn’t have customers,” said Hickie.

Workday defines Responsible AI as aligning AI systems to human values – ensuring they are ethical, transparent, fair, and safe. Furthermore, aligning AI systems to laws and regulations – so risk can be measured, managed, and mitigated.

Workday’s Responsible AI

• Clear principles (amplifying human potential, data privacy, positive societal impact, fairness, transparency).
• Robust practices, including adherence to the NIST AI Risk Management Framework and publishing fact sheets for each AI capability describing data usage and testing.
• Dedicated people, including a Responsible AI Officer, Dr. Kelly Trindle, a Responsible AI Advisory Board, and Responsible AI champions across the company.
• Strong policies, such as explicit refusal to develop certain high risk capabilities.

“We were asked a few years back to build surveillance technology to monitor employees during COVID, and the answer was no,” Hickie said. “There are areas we simply will not go. Every capability we ship goes through a NIST-based risk framework, and some ideas never make it out of that process – by design.”

What this means for businesses

Workday’s Innovation Event in Dublin underscores the company’s commitment to shaping the future of enterprise AI through a blend of technological advancement, responsible governance, and local investment.

By unveiling its AI strategy, expanding its Irish operations, and emphasising the importance of trustworthy data and compliance, Workday demonstrated its leadership in transforming HR and finance processes for the modern workplace. The introduction of unified platforms like Sana, the development of domain-specific agents, and the prioritisation of Responsible AI principles illustrated Workday’s holistic approach to innovation.

This event not only reinforced Dublin’s role as a strategic hub for AI excellence but also highlighted Workday’s vision for an ethical, secure, and user-centric future of work. Hopefully this approach can be adopted by all other tech players in the market place, embracing AI and agentic AI in particular.

While Workday’s approach to AI is robust—emphasising trustworthy enterprise data, rigorous security, and a strong Responsible AI framework—it is not without potential gaps. The company’s focus on deterministic enterprise data and compliance is commendable, yet as AI applications diversify and regulatory landscapes evolve, Workday may face challenges in maintaining agility and transparency.

For instance, although fact sheets and adherence to frameworks like NIST are in place, there is limited public access to outcomes from AI audits and impact assessments, which could hinder broader stakeholder trust. Additionally, the reliance on internal governance and refusal to pursue certain high-risk technologies might not fully address emerging ethical concerns or societal expectations, particularly as new risks arise.

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