How Visa Puts AI at the Center of Its Talent Strategy

Global payments technology company Visa is trusted by millions around the world to move money securely and seamlessly. And with over 34,000 employees and nearly $40 billion in revenue, Visa isn’t just moving money — they are moving at the pace of people and technology everywhere.

Visa is navigating the evolving payments landscape, where customers across more than 200 countries and territories expect the company to keep up with every way to pay, whether they are clicking, tapping, swiping, or entering card numbers online. That complexity requires Visa to combine technical innovation, adaptability, and security to safeguard its customers and their data.

Visa’s leadership recognized that staying ahead meant investing in its people as much as in its technology.

Read on to learn how Visa scaled AI adoption through peer-to-peer learning, role-specific AI upskilling, and a culture of experimentation to drive meaningful business outcomes — and what other companies can learn from their approach.

Empowering employees to scale AI innovation

Visa has been an AI leader for decades, using AI models to strengthen identity verification and fraud detection. But when generative AI emerged in 2022, the company saw an opportunity to empower every employee to use AI in their day-to-day work.

“AI is in our DNA as a company,” says Jeremy Broome, global head of talent at Visa. “We’ve always worked with big models, data and algorithms. That meant we had to stay at the forefront of scaling and leveraging AI as quickly as possible.”

To advance their AI maturity, Visa focused internal transformation on two key areas: empowering employees to write better AI prompts and develop AI agents. To enable this transformation, Visa needed to shift employees’ view of AI from a future skill to a present-day capability.

Shifting employee mindsets about AI

Visa’s talent team started by reframing AI from a niche technical skill to a core capability for every employee. The goal wasn’t to turn everyone into engineers, but to help people see how AI could amplify their impact, no matter what their role.

“Where does human capability add value now?” Jeremy asks. “AI enables us to get faster answers, but to succeed, we need people to ask the right questions. We need to maximize the unique contributions our people make to Visa.”

To accelerate human capability, Visa leaned on clear leadership commitment to AI, plus setting organization-wide goals for adoption.

Visa’s top executives model regular AI use in their own work. “I’ve been in meetings where our leaders have said, ‘Come and sit here. I'll show you the prompt I'm writing to get this information,’” Jeremy says. In addition, Visa’s most senior leaders are leading the charge on AI adoption, encouraging Visa employees to explore, experiment, and apply AI to their roles.

Visa also has created a required, organization-wide generative AI certificate-based program leveraging LinkedIn Learning, including courses like Prompt Engineering for Generative AI and Responsible AI: Principles and Practical Applications, with a goal of certifying 90% of employees in generative AI skills by the end of 2026.

Advancing AI literacy across talent, sales, and product

Visa tapped departments to lead in both innovation and change management. In particular, three departments — talent, sales, and product and tech — each led the way in showing how AI could drive performance and growth.

Talent team: Visa has leveraged AI to help employees discover internal opportunities, personalize learning paths, and solve real business problems. To do so, they focused on building a companywide skills plan, role‑based learning pathways, and AI‑powered skills agents that surface gaps and recommend actions. In parallel, employees are taking the initiative to build their own agents — both code and no‑code — to solve workflow problems and align with business goals. Examples include agents that align business OKRs with day‑to‑day work, resource‑finder agents that guide employees to the right content and experts, learning‑assist agents that coach employees through new skills, and answer bots that help teams safely adopt new generative AI tools.

The company is also modernizing its approach to talent management. Visa’s move from the traditional, static job architecture to a more dynamic, AI-enabled talent architecture is allowing their talent and L&D teams to proactively find and address skills gaps, better align recruitment and career development with the organization’s open roles, and create more internal pathways for employees.

Sales team: AI has helped the sales team shift from selling a single value proposition to more than 200 tailored pitches that reflect Visa’s diverse product portfolio. Sales teammates can now practice their pitches in a safe space, receive automated, AI-driven feedback, and build confidence without fear of judgment.

Jeremy also sees an opportunity for AI to improve client care and customer success. Visa is exploring how using AI agents can help customer success managers provide more timely, accurate answers to customer questions and help clients get more value from Visa products.

Product and tech teams: Visa’s product and tech teams partnered with talent and learning functions to improve employee development. They are experimenting with internal AI-powered objective and key result (OKR) agents — digital assistants designed to track progress, set goals, and simplify performance management. These agents look to help employees track progress, set goals, and stay aligned with business priorities. Managers will get real-time data and insights for better conversations, while learning teams use agents to proactively spot and close skill gaps before they slow employees’ growth. 

By developing AI fluency internally, Visa positioned itself to innovate faster for customers externally. The company recently introduced agentic commerce, enabling customers to make purchases and resolve payment disputes through emerging channels like chatbots and digital agents. Behind the scenes, every Visa engineer is leveraging generative AI tools to write code more efficiently and accelerate the development of AI agents that power these new agentic commerce experiences.

The company’s AI rollout across the talent, sales, product and tech teams has provided a roadmap for empowering employees to apply AI skills within their daily work and create real business outcomes, no matter where they sit in the organization.

Peer learning and manager enablement

Visa’s AI success wasn’t just about investing in tools but investing in its people. The company invested in systems and practices that made learning scalable, social, and strategic, including:

• Peer-to-peer learning: Employees were encouraged to share what they learned within their functional departments and scale what worked. Many built their own AI agents and shared them with colleagues. “When people both have AI tools and examples of colleagues using AI within their functions, they find a path very quickly,” Jeremy says.
• Embedded enablement: Learning was delivered in the flow of work and department-specific upskilling, not in isolated L&D programs. This helped employees apply new skills in real time.
• A safe sandbox: Visa provided controlled environments for experimentation, including mini hackathons and internal events to encourage learning and cross-functional collaboration. “It's vital to get employees excited about how they can use AI to more efficiently and effectively achieve results. That helps them get over any AI paralysis or fear,’” Jeremy says.
• Manager support: Using OKR agents and other generative AI tools, leaders were equipped to better understand their team’s current skills and identify and close capability gaps. This helped align AI upskilling with both individual career growth and broader business strategy.
• Strong governance: Visa took a security-first approach to AI. Compliance training, keeping a human in the loop, and using a governance committee to validate data, security, and Visa’s AI models ensure employees use the technology safely. “Humans make decisions. AI doesn't make decisions, it makes recommendations,” Jeremy says. “AI can help, but ultimately human accountability is absolutely critical.”

Together, these practices have created a foundation for responsible AI adoption — one that empowers employees to lead, learn, and innovate.

Measurable outcomes

Visa’s investment in AI upskilling has delivered tangible results:

• Sales performance: Visa’s use of AI-powered coaching has led to a 78% increase in seller confidence when pitching Visa products, with 83% of sales leaders reporting a clear value when their teams used AI-powered practice tools.
• Enhanced productivity: Product and tech teams are more productive: AI has improved output per person, lines of code generated, and accelerated project delivery – examples include 84% of its coders using generative AI to write code and realizing nearly 20% efficiency gains in tech operations.
• Talent assessment: Visa has leveraged AI to evolve how they evaluate early-career candidates to a more skills-based and data-driven approach, focusing on lateral thinking, critical assessment, and the ability to ask good questions.
• AI use: Nearly 90% of Visa employees with AI access use it every week — and many employees use it several times a day — with functions like sales, product, finance and technology leading the way.
• Learning engagement: Employees are actively building skills in generative AI, prompt engineering, and data science — alongside leadership and communication — showing a balanced focus on technical and human-centered growth.
• Increased employee confidence leveraging AI: Early data shows that since Visa began their targeted push around AI upskilling, they have seen a 2x increase in employee confidence using AI.

These outcomes reflect Visa’s holistic approach to AI not just as a technology, but as a catalyst for performance and innovation.

Final thoughts

For organizations beginning their own AI journey, the first step isn’t about having all the answers, but setting up the right systems and conditions for continuous AI upskilling. Start by asking:

• What tools are already available?
• Where are employees already using AI in their workflows?
• How can managers support learning and experimentation?
• How can AI create efficiencies and results in each specific department in our organization?

One of the most powerful ways to scale AI is through peer learning, giving employees the space and support to share knowledge. “That is a place where every organization can start,” Jeremy says.

Visa’s story proves that progress in AI starts with people: confident, capable employees who know how to turn technology into business results and serve Visa cardholders everywhere. The companies that succeed in this new era of work won’t only do so because of technology, but by empowering employees to leverage AI to both grow their careers — and drive meaningful business outcomes.