As companies race to prepare their workforces for AI-driven operations, FedEx Corp. announced it will train its workforce through an enterprise-wide AI education and literacy program that includes personalized, role-based training for team members worldwide.
The initiative, part of FedEx’s multi-year transformation into what CEO Raj Subramaniam calls “an AI-powered enterprise,” taps Accenture to provide customized AI education programs through its AI-native training platform LearnVantage. The platform will deliver tailored, scalable training with skill recognition and interactive live sessions to drive adoption.
The program aims to build common AI fluency and skills across FedEx’s global workforce of more than 500,000 employees, helping team members develop capabilities to apply AI responsibly and effectively.
Personalized learning pathways are aimed at enabling FedEx team members to build AI literacy tailored to where they are in their professional growth journey. The training will create a shared technology understanding across the company, according to FedEx. Employees will learn to apply AI responsibly within their functions and leaders will gain knowledge to embed AI into their work.
A phased approach to AI upskilling
For HR leaders looking to implement similar AI education programs at their own organizations, Stephen Wroblewski, talent strategy and development lead at Accenture, outlines how to prioritize workforce segments for AI training.
“Equipping individuals with the right AI skills establishes the foundation for innovation and confident leadership in a changing world,” Wroblewski said. “Sustained success requires a commitment to continuous co-learning, enabling teams to adapt, grow and lead effectively alongside advancing technology.”
For many organizations, the goal isn’t to train everyone at once but to identify who needs which level of AI capability, in what sequence, in order to drive business impact and embed AI into workflows.
Wroblewski recommends a three-phase approach:
- Phase 1: targets leaders, planners and customer-facing teams who influence decisions, adoption and day-to-day behaviors. Building their AI confidence first creates momentum across the organization.
- Phase 2: focuses on technical experts, core operations and support teams, where AI skills drive operational efficiency and innovation.
- Phase 3: addresses the broader frontline workforce with practical, task-level AI tools that enhance safety and productivity.
“HR doesn’t need a complex model to map skills,” Wroblewski said. “What matters is a clear, consistent view of the AI fluency required in each role—from basic awareness to advanced design and oversight.” He says when expectations are set, learning can be tailored based on the real work employees do, not a “one-size-fits-all curriculum.”
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Integrating AI literacy into talent systems
Wroblewski emphasized that AI literacy data should function as a new signal in the talent stack, not just learning and development metrics.
“This information is not just learning and developing (L&D) metrics and hours of training or courses taken,” he said. “It is actually a good indicator of what someone needs to do to develop in their job.”
The shift for HR involves treating AI literacy as a meaningful talent signal that informs performance, mobility and career development. This starts with creating a connected view of skills across the enterprise. When learning data such as courses, simulations and usage patterns is consistent and connected, HR can see emerging strengths, identify gaps and personalize opportunities at scale.
“The value comes when these skills provide insight into the systems and conversations that people utilize every day: internal job opportunities, workforce planning and performance conversations,” Wroblewski said. “It helps employees understand where they can grow, and it helps leaders make more confident talent decisions.”
Measuring impact beyond completion rates
Accenture recommends a stacked KPI model that includes adoption, application and impact. Traditional L&D milestones such as completions and quiz scores are necessary but not sufficient, according to Wroblewski.
An early KPI might track the percentage of leaders and planners who have completed AI training and the number of workflows redesigned to embed AI support, he suggests.
“Early on, you’ll see more employees using AI naturally in their work, more managers reinforcing responsible use, and more teams designing workflows that embed AI from the start,” Wroblewski said. “Over time, those behaviors translate into tangible improvements, including faster decisions, fewer manual steps and better accuracy in the work that matters most.”
HR doesn’t need a long list of metrics, he added, but rather a clear line of sight between learning, adoption and better outcomes for the business and its people.
Julie Sweet, chair and CEO of Accenture, said in a statement that FedEx is putting its people at the center by providing the training they need to thrive in the age of AI. “Together, we can help unlock the full value of AI across the company,” she said.
FedEx, which reported annual revenue of $89 billion, stated the org is working to make supply chains smarter through AI-powered solutions as part of its broader transformation journey. “The future of business is being shaped by data and AI more than ever before,” said Raj Subramaniam, president and CEO, FedEx Corporation, in a statement.
