Robert Yue is Vice President of Data Intelligence at AARP Services Inc., where he leads data and AI initiatives to deliver scalable, business-driven outcomes. His career has been shaped by a strong multidisciplinary foundation, combining expertise in business, statistics, and computer science. Robert holds three master’s degrees across these fields, enabling him to integrate quantitative rigor with technological depth in addressing complex challenges.
Throughout his career, Robert has alternated between consulting and client-side leadership roles, developing a balanced and pragmatic perspective on data and AI. This experience has given him a deep understanding of both strategic business needs and the practical realities of implementation.
Robert has focused on designing and operationalizing data and AI solutions that are not only innovative, but also scalable and aligned with real-world outcomes. His ability to bridge technical capability with business priorities has been central to his leadership approach.
How do you expect the data and AI leadership role to evolve over the next 12–24 months?
“Generative AI and Agentic AI are rapidly transforming how we work and live. As data and AI leaders, many of us have rolled up our sleeves to identify use cases, design pilots, and explore how to harness this technology to reimagine work and drive business impact and productivity.
“Now we’re moving past isolated pilots. The future focus will be on operationalizing AI at scale, embedding it into core business processes and customer journeys, with strong governance, reliability, and clear, measurable ROI.
“Scaling AI will also require stronger cross-functional leadership across business, technology, risk, legal, and operations. In this environment, influence, stakeholder alignment, and change management will be just as critical as technical depth.
“Last but not least, as regulatory and reputational scrutiny increases, data and AI leaders must embed responsible AI practices (governance, explainability, fairness, and privacy) throughout the entire AI lifecycle, rather than treating them as an afterthought.”
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?
“As data and AI leaders, I would highlight four key traits:
“Business Acumen: Ability to identify business opportunities and translate data and AI capabilities into measurable outcomes. Strong leaders anchor their work in tangible impact such as revenue growth, cost efficiency, or customer experience.
“Organizational Leadership: Ability to navigate complex, matrixed organizations, connect priorities across teams, and mobilize the right resources to drive data and AI-enabled transformation. Strong leaders build alignment among stakeholders and ensure execution from strategy through delivery.
“Data-Driven Storytelling and Influence: Ability to translate complex analyses into clear, compelling narratives that drive decision-making across the organization. Effective leaders turn insights into action by shaping how stakeholders interpret and prioritize information.
“Technical Depth: While not necessarily the deepest technical expert, strong leaders maintain sufficient breadth across data engineering, ML, AI, and digital technologies to stay current, set direction, ask the right questions, attract top talent, and build credibility with technical teams.
“At AARP Services Inc., organizational leadership is especially critical given its deeply people-centered culture that values relationships and collaboration. If you want to go fast, go alone; but if you want to go far and achieve larger initiatives, go together. Driving meaningful data and AI impact here requires not only strong strategy, but also the ability to build trust, align stakeholders, and move forward collectively.”
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?
“I feel it’s the ability to improve decision-making under uncertainty. At the executive level, strategic decisions about where to compete and how to win rarely come with complete, clean, or fully validated data. Waiting for perfect information often leads to inaction, slowing the organization in fast-paced environments.
“C-suite data and AI leaders must shape how decisions are made in the absence of complete information, enabling fellow executives to move forward with confidence, clarity, and speed despite uncertainty.”