AI will not make work more inclusive by default. HR leaders play an important role in redesigning work to create opportunity for all.
Sara Braun
Editorial Strategist, HR
Workday
AI is usually discussed as a productivity story: how much faster people work, how much is automated, how much time teams get back. But often those productivity gains are concentrated among employees who already have the best tools, the clearest workflows, and the greatest access to career-building work.
AI will not make work more inclusive by default, but with intentional design, HR leaders can enable employees to focus on the strategic and creative work that will allow them to grow.
As Stacey Romero, Director of VIBE (Value, Inclusion, & Belonging for Everyone) Programs at Workday, argues, the goal of leaders should be making sure every employee has fair and consistent access to opportunity. That reframing—from a technology rollout to a question of who might be left out—sits at the center of her work.
Without intentional design, AI will enable some employees to gain access to strategic, creative work, while others are left with more fragmented, monitored, or automated roles.
With intentional AI design, HR leaders can enable employees to focus on the strategic and creative work that will allow them to grow.
Many organizations are moving quickly to experiment with AI, yet access to tools, training, and guidance is not evenly distributed. When asked what limits the value of AI in an organization, the largest share of respondents reported uneven skills, training or access to tools.
This can result in a two-tier workforce. One group uses AI to reduce friction and take on more strategic work. Another group carries the coordination burden around disconnected systems and low-agency tasks—or watches peers innovate while waiting for permission and confidence to catch up.
That is not simply a technology-adoption problem. It is an inclusion problem. As Romero puts it, technology is only as effective as the humans using it, and if organizations are not inclusive in how they adopt it, AI will amplify issues that already exist.
But the problem is not only about inclusion. According to Romero, it is also about trust and psychological safety. “There’s a potential divide not just in who has access to AI, but who feels empowered to experiment with it and who's afraid to touch it because they're afraid it might make their role redundant,” she says.
27% of global employees say uneven skills, training, or access to AI tools limit the value of AI in their organization.
Giving employees access to AI tools is important, but access alone does not guarantee a better experience—or that people will actually use what they are given. Romero is direct: people need time, space, and psychological safety to learn. That permission often comes from managers. She describes a colleague who knew she should use AI but had not found the time. But once leaders reinforced that leaning in should eventually free up time, the upfront investment felt worth it.
Without runway and explicit permission, individual contributors—especially in non-technical roles—can inadvertently be left behind. For HR, that means treating AI access like other drivers of opportunity: learning, mobility, and developmental assignments.
If AI tools are not built with universal design principles, many people simply cannot use them. Romero, who also leads Workday’s Disability Inclusion Program, highlights the risk for employees using assistive technology such as screen readers. She urges addressing this early, because it becomes more difficult to fix accessibility gaps down the road.
Neurodivergent employees can also be left out. For someone with ADHD, task initiation can be a barrier, and if they are already overwhelmed, it’s less likely that they will lean in to learning a new tool.
An AI strategy built with a single lens can exclude large parts of the workforce. Romero warns against a U.S.- or headquarters-centric approach that favors a more direct communication style, which may not resonate across regions. Time zones matter too: when live enablement is scheduled around working hours in one office, employees elsewhere may have no choice but to watch a recording. Her guidance is to offer asynchronous learning, or synchronous learning across multiple time zones.
An AI strategy built with a single lens can exclude large parts of the workforce.
In a survey of 6,100 professionals in HR, finance, IT, and operations, we found: 82% spend significant time coordinating or translating work between teams or systems, 81% spend time moving information between tools, 77% focus their energy on reconciling conflicting data, and 70% spend extensive time on administrative tasks that create friction.
If AI is layered on top of broken workflows, it may accelerate unequal conditions. That is why HR needs to help redesign work itself, starting with the tasks people dislike. Romero suggests meeting people at their baseline and starting with simple, everyday tasks like recurring status updates rather than complex engineering work.
Responsible AI conversations often focus on privacy, security, and bias. Romero adds inclusion-focused questions: Is the tool accessible by design? Does it account for global nuance? And are we using AI to increase access to growth for everyone—or just reinforcing existing barriers? AI is already helping many people move faster—54% of global employees say it has accelerated work productivity—but speed alone does not guarantee opportunity.
The bigger opportunity here is to embed AI into core systems. Only 27% of employees say AI is deeply enmeshed in their organization’s core systems for managing people, money, and plans, yet those in organizations with embedded AI are 1.7x more likely to report meaningful time savings. AI strategy and workforce strategy need to be connected; the goal is not more tools, but better work.
“The best way to minimize potential impact is by leaning in, using the tools, and developing skills — not just in AI but in things like systems thinking that are hard for AI to replicate, like the judgment involved in difficult human questions,” Romero says. “That's setting our people up for success.”
HR leaders can:
audit who actually has access to AI tools and training across roles and geographies
redesign fragmented, low-agency work
connect any time savings to learning, mentorship, and stretch assignments
measure inclusion outcomes alongside productivity
The mistake to avoid is a one-size-fits-all approach because what works for one may not work for everyone. If organizations are not intentional, Romero warns, they risk creating an environment where people feel overwhelmed or excluded.
The two-tier workforce is not inevitable, but avoiding it requires leaders to define AI success not only by what the technology can do, but by who feels empowered to use it—and who gets to grow because of it.
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