Stefanie Khan is Director of Business Intelligence & Advanced Analytics at UPS, where she leads data and AI initiatives at the intersection of technology, analytics, and human-centered decision-making. Her career began in hands-on analytical roles, where she built a strong technical foundation before moving into senior leadership positions focused on scaling enterprise data capabilities and guiding complex transformation efforts.
Over the years, Stefanie has led the development of modern data platforms, advanced analytics programs, and emerging AI initiatives, partnering closely with executive and cross-functional stakeholders. Navigating ambiguity, aligning innovation with business priorities, and confronting the practical limits of automation have shaped her view that data and AI only deliver sustained value when supported by trust, governance, and ethical clarity.
As a leader, Stefanie places equal weight on translation and execution. She is known for making complex technical concepts accessible, fostering collaboration between technical and non-technical teams, and building cultures that treat data as a strategic asset rather than a byproduct. A committed advocate for women in technology, she also works to expand pathways for leadership and representation within the field.
Her perspective is grounded in pragmatism and responsibility. Stefanie advances sophisticated AI capabilities while remaining attentive to people, context, and long-term impact. She sees AI not as an end in itself, but as a tool to enable better decisions, stronger accountability, and more sustainable business outcomes.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“I believe that the most effective data and AI leaders combine technical credibility with strong judgment, humility, and the ability to operate across organizational boundaries. While technical fluency remains essential, the traits that matter most are those that enable scale and trust: clear communication, disciplined prioritization, and a deep respect for the operational realities of the business. Effective leaders must know when to push innovation forward and when to slow it down to ensure reliability, safety, and adoption.
“At UPS, these traits are particularly influential because of the company’s operational complexity, global scale, and mission-critical dependence on precision and reliability. Data and AI initiatives do not exist in isolation; they directly affect drivers, aircraft, customers, and service commitments. As a result, leadership demands an acute understanding of how analytical decisions translate into physical-world outcomes. The ability to translate sophisticated models into simple, actionable guidance has proven far more impactful than technical novelty alone.
“Equally important is stewardship by setting clear standards for data quality, governance, and ethical AI use while empowering teams to innovate within well-defined guardrails. At UPS, this balance has enabled faster adoption without compromising trust.
“I have seen that leaders who build credibility through consistency, operational empathy, and follow-through create environments where data and AI are embraced rather than resisted. Ultimately, the most influential skills are those that align advanced capabilities with the company’s culture of execution, accountability, and service excellence.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Get comfortable with being uncomfortable. The most consequential leadership moments rarely come from technical problem-solving; they emerge in situations marked by ambiguity, resistance, and imperfect information. Progress often requires making decisions before all the data is available, challenging entrenched assumptions, and standing firm when outcomes are uncertain or unpopular.
“Throughout my career, I have learned that discomfort is not a signal to retreat, and it is often an indicator of growth, influence, and responsibility. Whether navigating organizational change, redefining accountability for AI systems, or translating complex insights to skeptical stakeholders, effectiveness depends on the ability to remain grounded under pressure. Leaders who avoid discomfort tend to optimize safety rather than impact.
“Getting comfortable with discomfort builds resilience, sharpens judgment, and strengthens credibility. It allows leaders to engage in difficult conversations, accept measured risk, and operate confidently at the edge of their expertise. Ultimately, the path to the C-suite is less about technical mastery and more about developing the composure and courage required to lead when clarity is scarce and the stakes are high.”