If they lack the necessary systems in place to support agentic artificial intelligence (AI) workflows, enterprises likely will have to deal with rogue agents and hallucinated responses, and risk eroding trust in their AI deployments.
Without the right context, guided compliance, and sanctioned execution, AI agents can run loose and “lawless”, said Shan Moorthy, Workday’s Asia-Pacific CTO.
Organisations’ underlying business processes are deterministic by design, so that they can deliver consistent and predictable outcomes. This is essential particularly for HR and finance systems, which need to be accurate at all times and where there is zero margin for error.
Current iterations of AI, however, is probabilistic by nature, giving it the ability to reason, predict, and recommend actions based on patterns in the data on which it is trained.
While this makes AI powerful tools, it also makes the technology unpredictable and fundamentally lawless, Moorthy said, on the sidelines of Workday’s Elevate 2026 Singapore.
The lack of predictability presents tremendous risks for finance, HR, and legal teams, where hallucinations can result in inaccurate financial reports, unauthorised transactions, and misinformed decisions, he noted.
And when AI agents have limited context from which to draw, with controls and policies that lack a proper framework, organisations run the risk of having agents that do not operate consistently in compliance.
To achieve the precision and accountability they need for critical workflows, businesses need an AI infrastructure that is embedded within a trusted architecture.
This will ensure they have a probabilistic AI platform capable of delivering deterministic outcomes, Moorthy said.
He pointed to solutions such as Workday’s Agent System of Record, integrated with its agentic AI platform Workday Sana, that are built to help companies plug gaps in governance and risk compliance when they deploy AI agents.
The Workday Agent System of Record lets businesses manage their AI agents on the same platform on which they manage their employees, providing a unified agent analytics infrastructure that is touted to deliver full visibility of the organisation’s hybrid agentic workforce.
Businesses need an AI architecture that gives them 100% explainability and 100% observability, Moorthy said, especially as a growing number of AI agents are deployed to handle tasks and take actions on behalf of employees.
Workday Sana provides an infrastructure that ensures agents run on the necessary guardrails and within trusted business processes, including approvals, access controls, and data security policies.
Sana can generate answers that are personalised and “policy-aware”, said Wong Pei Woan, Workday’s Asean senior director of solution consulting.
It understands context and is able to look at an employee’s calendar and company policies, for instance, and generate a monthly expense report that is compliant, Wong said Elevate Singapore.
The Workday Agent System of Record also provides a dashboard that indicates the number of AI agents that have been deployed within the organisation as well as agents that are the most active. This spans all agents, regardless of whether they were built by Workday, the enterprise customer, or its partners.
It also enables users to choose which skills to activate for each agent and set up the necessary security profile for the agent, Wong said. The agent then will automatically inherit the access policies required for it to perform its task.
The dashboard further shows the value of each agent, so the organisation can decide whether to shut down underperforming agents or double down on those delivering high value.
Organisations need to move from AI that assist, to AI that actually do the work, said Jess O’Reilly, Workday’s Asean general manager.
They need context-aware AI assistants that operate not only autonomously, but also safely, O’Reilly said during her opening address at Elevate Singapore.
AI needs context to be useful, she said, noting that general-purpose LLMs (large language models) can help create tasks and automate routine work at scale and speed, but do not have context on how an enterprise operates.
“They can’t, and won’t know how your work gets done,” she said.
This is where Workday aims to help its customers with their agentic AI deployments, she added.
Unified platform for better visibility, faster response
And when done right, AI can yield significant gains in speed-to-market and power impactful decision-making.
Australia’s RMIT University roped in Workday to replace its fragmented legacy HR, finance, and procurement systems.
It integrated more than 60 systems and now runs a unified cloud and intelligent digital infrastructure, providing real-time data access and richer AI-powered user experience.
The transformation has helped RMIT cut its turnaround time for key HR processes by 50% and enabled faster and more predictable monthly closing cycles.
By automating routine tasks and gaining real-time visibility into transactions, the university has empowered its leaders to make smarter, data-driven decisions, while freeing staff to focus on higher-value work.
Manish Pandey, RMIT University’s director of enterprise technology services, said: “Workday aligned with our digital transformation priorities by enabling a more intuitive, AI-enabled user experience, and a low-maintenance, simplified technology landscape.”
Korean Air, driven by its goal to become a leader in the global aviation industry, also partnered Workday to replace its legacy HR systems with a unified cloud-based AI platform.
With Workday Human Capital Management, the airline streamlined its people processes to provide a single source of truth for employee data across its global operations.
The Workday platform enables self-service capabilities and mobile access, empowering Korean Air employees and managers to handle tasks more efficiently, while gaining real-time visibility into workforce trends.
The carrier is further able to leverage AI-powered insights to optimise talent management and drive more agile, strategic decision-making across the organisation.
“With Workday, we can consolidate all our data onto one platform,” said Choi Heejung, Korean Air’s managing vice president and CIO. “This is our foundation for moving to AI materialisation.”
Fellow airline, Scoot, also tapped Workday talent acquisition and development tools to consolidate its employee data onto a unified cloud platform.
With Workday Extend, Scoot’s HR team is able to create tailored, concierge-style applications on-demand, allowing employees to take ownership of their own career development.
It provides the airline with an accurate view of employee sentiments and needs, and ensures all HR strategies are supported by data-driven insights rather than intuition.
“Workday’s product roadmap was a big plus for Scoot. It demonstrated that there was another forward-looking organisation, always looking beyond the ‘now’,” said Ivan Chuah, Scoot’s HR director.
Customise AI to your business requirements
JLL Singapore also was able to build custom applications, such as “Easy HR”, by tapping Workday Extend.
It allows JLL employees to generate complex reports quickly using natural language.
The real estate company also integrated Workday’s HiredScore AI for Recruiting to optimise its recruitment pipeline, boosting quarterly hiring by 64% while reducing the average time-to-fill.
The AI-powered HR automation solution is designed to deliver actionable insights across workflows specifically for hiring activities.
For instance, it identifies the most relevant candidates with unbiased, AI-driven candidate grading and automatically surfaces relevant, likely-to-apply leads from the organisation’s existing databases and partner networks.
“With HiredScore AI for Recruiting, we have transformed our hiring processes, dramatically increasing recruiter productivity while also improving candidate quality,” said Ajay Pimpalshende, JLL Singapore’s director of product management.
“We’re at an intersection where organisations have access to the tools, but not necessarily a strategy about what they’re doing with the tools,” Moorthy said. “Most are still in the experimental stage and trying to get AI to operational.”
To add to that challenge, they now have to expand their AI deployments to include agentic in a significant way.
CIOs have been tasked to figure out their organisation’s AI strategy even amidst a lack of use cases from which to draw and build on, he noted.
And when there are use cases, these do not necessarily have the regulatory and compliance frameworks and controls that their organisation needs, he added.
There are big gaps businesses must resolve if they want to transition from experimentation to production, Moorthy said.
Workday designed its solutions to meet such requirements, he noted, including providing the guardrails that enterprises need to ensure their AI agents remain “lawful” by nature, while still delivering the operational efficiencies and value that probabilistic AI models promise.
