How Mastercard’s Leaders Are Building an AI-Powered Workforce

In a world racing toward AI transformation, most companies are asking: What should we automate? But Mastercard’s leaders are asking deeper questions: What is the work really made of? What’s the responsible way to redesign it? And how do we bring our people with us?

In a recent Reejig webinar, Siobhan Savage was joined by Mastercard’s JoAnn Stonier (Fellow of Data & AI) and Michael Fraccaro (Fellow and former Chief People Officer) to explore how leading companies are boldly, but responsibly, creating AI-powered workforces.

Here are the key takeaways.

Reinvention Starts With the Right Question

The AI journey isn’t about jumping on the latest tool. According to JoAnn, it begins with business and data strategy:

“AI transformation isn’t just about the tech. It’s about your people, processes, and what kind of company you want to become.”

Leaders need to rethink their entire operating models—from legal and HR to product, finance, and beyond. It’s not one big transformation; it’s a continuous series of micro-transformations across the enterprise.

Efficiency Comes First. But It’s Just the Start.

Most organizations begin with efficiency, the “defensive” use of AI:

• Streamlining internal processes
• Running pilots behind the scenes
• Learning quietly before going public
  
  

But that’s just phase one. The real value comes when AI is used to personalize services, extend product capabilities, and fuel innovation. This journey requires:

• Governance councils that cut across HR, tech, legal, and business
• Strong AI/data leadership
• Prioritized experimentation
  
  

HR + AI = Transformation at Scale

One of the strongest messages from both JoAnn and Michael: HR and AI teams must work together from day one.

“If your AI team isn’t thinking about people, who do you think is going to create the value?”

HR is critical to:

• Building foundational AI literacy across the org
• Designing skilling journeys for different job families
• Re-architecting roles around people–agent collaboration
• Leading the change management effort

JoAnn added: “We need to train managers to supervise AI agents—because they’re not just leading people anymore.”

From Curiosity to Capability: Managing the People Side

While headlines focus on job loss fears, Mastercard sees more curiosity than anxiety.

“Our people are asking, ‘How will this help me do my job better?’” – Michael

To channel that curiosity, leaders must:

• Be transparent about the roadmap
• Involve employees in the change
• Train for both tool usage and agent supervision
• Make change feel normal, not overwhelming

Michael emphasized HR’s role as a translator between AI strategy and workforce planning: “There’s no playbook—but we can co-create one.”

Think in Tasks, Not Titles

Traditional org charts and job titles don’t reflect how work actually gets done. That’s why Mastercard and other leading companies are:

• Breaking jobs into discrete tasks
• Identifying which tasks are ripe for automation
• Reallocating people toward higher-value work

This task-level visibility also enables smarter reskilling, better internal mobility, and more meaningful conversations with leadership.

“Jobs don’t transform. Tasks do. That’s where the real opportunity is.” – Siobhan

The Emotional Layer of Change

JoAnn closed with an important reminder: transformation is also emotional.

“Everyone is going through change. Leaders need to acknowledge that and bring empathy into the process.”

Whether employees are curious, overwhelmed, or excited, it’s the company’s responsibility to create space for learning, experimentation, and community.

What Organizations Can Learn from Mastercard

• Start with clarity, not just code. AI needs work intelligence, not just data.
• Make HR a co-pilot. They own the people systems that make transformation stick.
• Build for evolution. Your org design must flex as agents, tools, and tasks evolve.
• Lead with humanity. The right transformation honors people, not just productivity.

The Bottom Line

Mastercard is showing what responsible AI-powered transformation looks like: not just adopting tech, but rethinking how work is done—and why.

By focusing on the intersection of people, data, and strategy, they’re not just building a future-ready workforce. They’re building trust.

“This isn’t just about skilling. It’s about shaping the future of work.”