Workday Doubles Down on AI: Opportunities, Risks, and What to Do Next
- Kendria Countee
- Nov 7
- 5 min read
This year’s Workday Rising brought leaders in finance, HR, and technology around a common theme: a more flexible Workday platform powered by AI. Major announcements included Workday’s acquisition of Sana and launch of Workday Data Cloud, Workday Build, and Workday Flex Credits—all reinforcing the platform’s “Power of One” philosophy by further integrating HR and Finance through AI.
Many organizations are eager to take advantage of Workday’s evolving ecosystem, but this is easier said than done. Having guided companies through major tech transformations, we see potential challenges and complexities organizations must factor into their plans.
What’s New With Workday
Before we dive into the implications, let’s recap Workday’s biggest announcements:
Workday Data Cloud
Workday Data Cloud provides a secure environment where HR and Finance data can be accessed in real time and connected to customer, market, and operational data for richer insights and stronger governance. This “zero-copy” approach allows external systems to access real-time Workday data without the hassle of copying and moving it into separate databases.
Sana Acquisition
Since 2016, the AI company Sana has developed knowledge tools to help teams, including AI agents and an enterprise learning platform. Once integrated with Workday, companies can leverage AI agents to summarize insights, draft documents, and guide employees through complex processes by pulling data from Workday as well as external systems. This can reduce manual effort and improve process efficiency.
Workday Build
The introduction of the developer platform Workday Build means developers and customers can now create custom apps and agents within the Workday platform. Low-code tools will make it easier to automate and customize workflows to customer needs.
Workday Flex Credits
With Workday Flex Credits, organizations can flexibly enable AI features and/or build new agents. Flex Credits’ pay-for-what-you-use model means companies can easily control costs and scale their usage as needed.
How These Changes Impact Workday Customers
Workday’s new solutions offer organizations the potential to move faster and with greater confidence, specifically by:
Providing access to real-time data inside and outside the system for enhanced decision-making
Reducing transaction cycle times and increasing resource capacity for strategic work through the use of AI agents
Creating more room for experimentation with flexible pricing
Instead of waiting for biannual release updates, past Brainstorms to be realized, or Idea Hub suggestions to be roadmapped, businesses will be better able to tailor Workday to their unique needs.
The Cost of AI Value Realization
With new technologies come new responsibilities. According to a global study by IBM:
More than half (52%) of CEOs surveyed say they’re realizing value from AI. However, only 25% report that AI initiatives have delivered expected ROI over the last few years.
Nearly two-thirds (64%) of CEOs acknowledge that the risk of falling behind drives investment before they understand the value new technologies bring to their organization.
Surveyed CEOs perceive organizational silos, risk aversion, and the lack of expertise as the top three barriers to innovation at their organizations.
Given the challenges of implementing AI solutions for practical results, organizations must be thoughtful about how they prepare. FOMO around new technologies could mean moving too fast without the right infrastructure, governance, and skills in place—preventing organizations from fully maximizing the ROI of their AI investments.
Key Considerations for Organization Leaders
Though exciting, Workday’s acceleration towards AI comes with new trade-offs. Keep these factors in mind as you plan ahead:
Cost complexity: Flex Credits bring flexibility but can make spending harder to forecast. Monitoring usage closely will be essential to capturing the total cost of ownership.
Overreliance on a single platform: As more core processes and AI tools are tied to Workday, the cost and complexity of switching platforms will rise.
Skill building: Building AI agents is different from building business processes. Not all teams have the skills to immediately leverage Workday’s new offerings.
Data security: Real-time integrations mean strong policies around data governance, privacy, and compliance are crucial for security purposes.
Data quality: AI agents are only as reliable as the data they’re fed. You’ll need a plan to address existing data problems (like inaccurate records) to prevent larger issues down the road.
Environments, Social and Governance (ESG) implications: Because AI is so resource-intensive, companies with strong ESG commitments and regulatory requirements must consider its environmental footprint.
Who Risks Falling Behind?
Organizations with robust infrastructure, governance, and change management practices are set up for success with new technologies, from Workday and beyond. Meanwhile, organizations that check one or a few of the following boxes may struggle to adapt:
Smaller customers/Workday Support teams: Because their focus is on day-to-day operations, they may struggle to justify the cost of experimenting with new AI-enhanced features.
Data governance and quality gaps: Building automation on top of broken data leads to incorrectly trained and deployed solutions.
Highly regulated industries: Strict regulations may prevent or slow organizations in adopting AI, allowing competitors to get ahead.
Missing executive ownership: Companies lacking executive alignment across HR, Finance, and IT will struggle to integrate these areas with or without new tech.
Heavy reliance on AMS support: AMS providers work on open tickets; they don’t typically provide strategic thought partnership. Without internal strategy driving the implementation, organizations miss out on taking full advantage of all of Workday’s new developments.
In short, when an organization has strong leadership, clearly established systems, and a culture that embraces change, they’re more likely to successfully adopt new tech.
How to Prepare: 5 Moves to Adapt
To prepare your team for Workday’s push into AI, focus on these five key areas:
Establish a data readiness baseline. Run data quality reports in Workday to understand the big picture of current platform usage: incomplete/conflicting worker data, unposted journals, and where business processes are being manually corrected/reassigned/rescinded regularly.
Establish governance around existing and new features. Clarify ownership across HR, IT, and Finance. Set up a change control process, approvals, and how to handle escalations so that compliance, risk, and ROI for new AI features are all considered.
Start small with one high-value use case. Find one pain point to tackle first. Track current processing times and time savings after implementation to better understand the potential of a wider rollout.
Build on your team’s skillsets. Don’t assume your team members have the know-how to immediately leverage Workday’s latest developments. Take into account the time and monetary investment for building their technical and non-technical skills. You should also consider how your AMS partner currently works and what Workday’s new changes mean for them.
Evaluate ESG implications. Understand your organization’s requirements around ESG so that you can track and report AI usage appropriately.
Make Workday’s New AI Features Work for Your Business
As Workday’s platform evolves, so do its configuration possibilities for your organization. Yet integrating AI into your current Workday setup also presents new challenges. For the best results, prioritize clean, trustworthy data and getting all stakeholders from HR, Finance, IT, and AMS aligned.
Need support weaving AI into your Workday implementation? Reach out to us at info@abnormallogic.com to get started.
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