Workday's People-First AI Strategy Drives 79% Employee Adoption

Workday: Why People-Centric AI Adoption Drives Success

Most enterprises say they use AI. Far fewer put tools in employees' hands. Recent surveys show the gap clearly: many CEOs report AI in workflows, yet only a third say their teams have access to AI at work. Workday took a different route-start with people, not platforms-and now 79% of its employees use AI on the job.

The takeaway for executives: adoption is a behavior problem before it's a technology problem. Workday's approach shows how to remove friction, build momentum, and translate AI from concept to consistent practice across the business.

The barrier wasn't tools-it was timing and confidence

Internal research at Workday surfaced a simple insight: employees weren't sure when AI was appropriate. That hesitation stalled usage more than access or training content ever could.

To address this, Workday launched "Everyday AI," a company-wide program focused on real work, real use cases, and peer-led momentum. The goal: make AI a normal part of daily execution, not a special project.

Start from the top-then hand it to employees

Workday kicked off the campaign with a company meeting in April. CEO Carl Eschenbach shared how he uses AI and where it already delivers value across the company. Then the floor opened for employee examples and questions.

Chief People Officer Ashley Goldsmith emphasized the focus on employees: less theory, more practice. Within weeks, adoption beat expectations. By June, more than a quarter of the company was using AI. Continued momentum pushed usage to 79%.

Goldsmith described the sentiment as "huge adoption and real enthusiasm." She also outlined practical incentives like peer recognition for AI use and resources that help managers activate AI on their teams.

Proof of value: HR puts AI to work

Workday's HR team moved fast. Their "Workday recruiting agent" streamlined sourcing and shortlisting, reducing recruiter workloads by 12% while improving candidate quality. Interviews felt more worthwhile because input was captured and used.

The team also deployed Peakon to analyze employee comments at scale and surface insights. Goldsmith called the impact significant, noting that trust depends on listening well and acting quickly.

What leaders can copy: a three-pillar adoption model

• Build clarity and excitement: Set a clear baseline of what AI can and cannot do. Share practical examples from leaders and peers. Encourage small, frequent experiments tied to everyday tasks.
• Enable AI champions: Don't just provide access-develop internal guides who coach teammates on prompts, use cases, and quality checks. Peer support beats top-down directives.
• Make it functional and responsible: Move from awareness to targeted use in specific workflows. Define guardrails, data policies, and approved tools. Keep iterating based on results.

Executive playbook: how to drive 70%+ adoption in a quarter

• Set a visible goal: For example, "80% of employees use AI weekly by Q4." Make progress public.
• Lead by example: Have the CEO and executive team share actual prompts, outputs, and decisions accelerated by AI.
• Codify 10 core use cases: Drafts, summaries, email rewrites, meeting prep, interview guides, data clean-up, job descriptions, customer notes, QA checks, and SOP creation.
• Activate managers: Provide toolkits with prompts, checklists, and metrics. Ask each manager to run a team challenge with a clear before/after result.
• Create recognition loops: Highlight wins in all-hands. Reward measurable time savings, quality gains, and reduced rework.
• Build the guardrails early: Clarify acceptable use, data handling, review steps, and escalation paths.
• Measure what matters: Track weekly active users, tasks automated, cycle-time reductions, and error rates. Publish a simple dashboard.

Why this works

Workday treats AI adoption like behavior change. The company lowers friction, shows proof inside real workflows, and creates social incentives. Leaders set the tone, managers activate teams, and champions keep the engine running.

As CIO Rani Johnson has emphasized in public statements, AI is most effective when it improves meaningful work for people. That philosophy keeps the focus on outcomes employees care about-clarity, speed, and better decisions-rather than abstract potential.

Next step

If your teams need structured enablement, consider role-based learning paths and internal certifications. For curated programs by job function, see Complete AI Training: Courses by Job.

Key numbers

• 79% of Workday employees now use AI at work.
• 12% reduction in recruiter workload after deploying the Workday recruiting agent.
• Company-wide momentum driven by a people-first program: "Everyday AI."

Bottom line for executives

AI adoption scales when you make it safe, simple, and social. Put leaders in the arena, equip managers, celebrate wins, and focus on functional use cases with clear guardrails. Do that, and usage follows-along with measurable performance gains and stronger employee engagement.