Cracking the ROI Code: How to convert ideas into value with Workday AI

Workday has evolved its solution to become an enterprise AI platform designed to manage people, money, and agents. This isn’t merely a rebranding; it is a strategic pivot to an open platform approach, backed by the introduction of a whole new slate of AI capabilities, including:

• Workday AI Reimagined, which offers AI agents for HR, finance, and industry that take on important processes such as performance reviews, workforce planning, and financial close.
• Workday Build, which helps enable a new level of customization, giving organizations the ability to create AI tools that meet their personal business needs.
• Workday Data Cloud, a new architectural data layer that helps to empower organizations to unlock the strategic value of their HR and finance data by integrating seamlessly to leading cloud platforms, partner data lakes, existing analytics environments and operational systems.

Workday has additionally made significant investments in Paradox, Sana, Flowise, Evisort and Pipedream—AI-focused solutions that extend the Workday platform and provide even broader capabilities (See Figure 1.)

Yet, despite these advancements and numerous successful use cases, the path to ROI from AI-enabled solutions remains unclear for many enterprises. To address the value gap, Deloitte has developed an approach for cracking the ROI code. With it, organizations can get on the path to developing a sound value case and roadmap—and ultimately to seeing a direct benefit from adopting Workday AI.

FIGURE 1: OVERVIEW OF WORKDAY AGENTIC AI COMPONENTS

Gain insight into the key Workday Agentic components that help drive intelligent, automated HR experiences—transforming how organizations and employees interact with leave management processes.

Understanding the Value Gap
Last year, a report from MIT revealed that despite spending US$30- US$40 billion on Generative AI, only 5% of organizations saw a return on pilots. The report cites hypotheses for why this is so, including brittle workflows, infrastructure constraints, and talent limitations. However, one of the largest obstacles could be failing to integrate AI adoption with the organization's strategic aspirations and the specific outcomes it seeks to achieve. For example these sort of aspirational outcome based objectives include: Chief Human Resource Officers (CHROs) aspiring to improve talent acquisition and mobility with AI-driven decisioning; Chief Financial Officers (CFOs) playing a more strategic role through advanced planning and scenario modeling capabilities; to reduce risk through AI-assisted variance analysis and narrative reporting; or to enhance both productivity and the employee experience through self-service AI agents that execute important transactions via a familiar chat interface.

However, absent clear aspirations, organizations often focus on how the technology can automate a process within a given function, without formulating use cases with tangible outcomes or doing the preparatory work needed to deliver the expected value in a scalable and consistent way. Consequently, deployments are often piecemeal, siloed, and disconnected from how work actually gets done, further impeding value realization.

In our view, deployment of AI should focus on outcomes, not automation. AI is more likely to drive value when thought of in a broader context such as how it can enable processes across multiple solutions, leverage multiple data sources, and scale and adapt to meet the evolving needs of the enterprise. Agentic AI departs from traditional serial processes by allowing agents to perform multiple steps simultaneously, pausing for human input only when most important.

With these principles in mind, the market is likely moving toward a more extensible AI platform and ecosystem, rather than a collection of disparate point tools. With Workday, you can leverage multiple agents, manage them through Workday's Agent System of Record orchestration layer, communicate via Model Context Protocol (MCP), access Workday Data Cloud, and scale capabilities across the enterprise IT landscape.

Where to Start: Ambition and Strategy

While it is important to understand the AI capabilities Workday offers, adopting AI is much more than a technology decision. Developing a roadmap for deploying and realizing value from AI begins with defining ambition and strategy. This often means consulting with stakeholders to explore:

• What business and human outcomes do you want to achieve?
• What is your future vision for HR and finance powered by Workday-enabled AI?
• What is the new “art of the possible” in light of Workday AI strategy and product announcements?

Once you get a sense of what you want to accomplish with Workday-enabled AI, you can identify “what must be true” to enable the workforce to make it happen. For instance, the organization may need to develop a culture of innovation or people may need to be upskilled or reskilled to work with AI agents. Also, it is highly likely that teams may need to prepare for new ways of working, including training for AI fluency, role redesign, and behavior shifts.

There is also a trust factor that needs to be established. People need to be aware of the objectives of AI deployment, the outcomes the organization seeks, and how they can be achieved and measured. Transparency is important throughout deployment and beyond. Accordingly, a structured adoption and change plan is important for driving engagement and minimizing resistance, along with a clear governance framework of policies, roles, responsibilities, and processes to help ensure compliance with laws, ethical principles, and internal standards—while maintaining transparency, accountability, and continuous risk monitoring.

Overall, AI ambition and strategy should be rooted in a hard-nosed value-rooted thesis rather than generic aspirations. The thesis should articulate where Workday-enabled AI is supposed to create value in the next 12–24 months and how you intend to measure it. Value metrics are not solely centered on time savings and productivity enhancements. Value can also come from elevating the employee experience, increasing team member satisfaction, improving decision-making, reducing risk, enhancing quality compliance, and leading the enterprise in advancing AI maturity.

What Comes Next: Prioritization and Solution Alignment

With AI use cases emerging quickly, surveying the market for demonstrated and new applications is very useful for informing the “how” of your ambition and strategy. This step can be accelerated by leveraging continuously updated tools and repositories from trusted market leaders. For instance, Deloitte offers an expanding repository of use cases derived from its extensive market experience, along with a collection of next-gen, AI-infused business workflows. These workflows consider the potential of Agentic AI and how it can seamlessly be infused into existing processes within the Workday framework to deliver value.

With stakeholder input, you can then prioritize the identified workflows and use cases by area while making sure they align with the organization’s overarching goals. At a high level, this can be done by examining the potential impact (value) that AI-enabled processes would generate, cross-referenced with the feasibility of execution. (See Figure 2.)

FIGURE 2: DEVELOP PRIORITIZATION CRITERIA: THE AI AGENT PRIORITIZATION FRAMEWORK

The framework below is a sample prioritization tool that can be customized to prioritize AI workflows based on their specific goals. Evaluate each workflow for it’s potential impact and the feasibility of execution given available resources. This ensures AI initiatives are sequenced to deliver maximum value and are practical to implement.

Last Stop Before Buy-in: Value Case and Roadmap

Once key workflows and enabling capabilities have been identified, building a value case and a roadmap becomes important for gaining leadership buy-in and investment. Key factors to consider include:

• How does the proposed pilot create capacity, enhance experience, or generate cost savings? 
• How does it support the overall investment in Workday as the organization’s central AI solution for HR and finance?
• What are the risk and compliance factors, and how can they be mitigated?
• Can a greater up-front investment help fund and accelerate future waves?

The answers can be incorporated into a value narrative, metrics, and key performance indicators to measure future success and to gain support from key stakeholders. The following high-level examples provide a sense of what an AI value case should include:

Human Capital Management — The organization can utilize Workday, combined with embedded AI capabilities provided in HiredScore, Paradox, and Workday Skills Cloud. It may also develop a specialized Flowise Recruiter Agent to handle seasonal high volume recruiting needs. These capabilities can reduce time-to-fill for priority roles by ~30–40%, decrease recruiter administrative work by ~30%, and significantly increase internal talent mobility into key open roles. This is designed to be achieved by AI-driven candidate ranking, rediscovery of past applicants, conversational screening for high-volume roles, and skills-based matching from the Workday talent pool. The intended result is faster hiring, a higher quality slate, lower agency spend, and a better candidate and hiring manager experience.

Financial Management — The organization can utilize Workday’s AI capabilities in Financial Management and Adaptive Planning to reduce the financial close by 2–3 days, decrease manual variance analysis effort by 30–40%, and enhance forecast accuracy. Deloitte can accomplish this by developing an external agent registered in Workday’s Agent System of Record that works across Workday Adaptive Planning, Workday Financial Management, and Workday Data Cloud, to automatically summarize variances and anomalies, draft commentary for management and board reports, and surface likely drivers based on historical patterns. This can help enable finance analysts to shift their time from data wrangling and developing report first drafts to scenario analysis and providing the business with strategic insights.

To align your actions toward realizing the value case, the next step is to develop a high-level roadmap for reimagining HR or Finance, including Workday capabilities, workforce enablement, and operating model shifts. The roadmap should include activities to define the reimagined roles, processes, and services with illustrative examples of what machine and human collaboration may look like. (See figure 3.)

In defining your roadmap and the underlying value case, it’s important to:

• Fund against a hard value case, not a vision statement. You’ll likely get—and keep—funding if the AI story looks like a real business case, not a glossy storyboard.
• Treat the roadmap as the guardrails for the deployment, not a feature wish list. You can get ROI from a small number of well-chosen, scaled use cases, not from turning on every feature Workday just shipped.
• Budget as much for people, data, and the operating model as you do for technology. If the plan is to “switch on Workday AI and send a comms email,” it may fail. Successful programs treat “human + machine” design, data readiness, and the operating model as leading deliverables.

FIGURE 3: REIMAGINING HR - “PROCESS” FOCUS (COMPLEX EXAMPLE)

We can analyze data patterns to detect signals and initiate workflows with tailored insights that Managers may not realize needed or valuable without the help of AI.

Deloitte as a Guide

While it is possible for an organization to consider the aforementioned factors on its own, attaining one’s AI ambitions can be much easier with an experienced guide who brings the very latest knowledge and equipment in the form of methodologies, tools, functional know-how, Workday AI experience, and industry-specific leading practices.

With a deep understanding of people, process, and technology, Deloitte is well qualified to serve as that guide through its Reimagine Work sprint approach. Over the course of 6-8 weeks, Deloitte can assist you in defining your ambition and strategy, prioritizing and aligning solutions, and developing a value case and road map. Key outputs include:

• A North Star vision for Agentic AI with Workday at the center.
• An HR or Finance AI maturity diagnostic and gap list.
• Prioritized AI process heatmap showing where to focus.
• A CFO-ready Workday AI value case and investment thesis.
• A pragmatic Workday AI roadmap and operating model that suggest exactly how to move from concepts to scaled deployment.

Contact Us

While Workday AI adoption is a journey, you don’t have to wait until the last leg to realize value. By taking a structured approach to defining your ambition and strategy, prioritizing and aligning solutions, and developing a value case and roadmap, you too can crack the ROI code—and start realizing value sooner than later. To schedule a Workday Reimagine Work sprint or to learn more about how to accelerate value realization within your organization, contact us today.