REPLACE Big Data Show logo
April 30 - May 1, 2025
North Javits Center | New York City

From Theory to Practice: NYU Professor Bridges the Gap with AI and Data in Business Education

Dr. Jose Mendoza is an experienced marketing executive who has made the leap to academia, teaching a new generation of students how to leverage data and AI in a new business environment. Mendoza teaches graduate students at NYU about artificial intelligence marketing and data science for business among other topics. Another role he has taken on is Data Universe advisory board member. He recently sat down with us to talk about how data and AI are being introduced to today’s students and what is most important as they prepare for careers in an AI- and data-driven business world.

Data Universe: As a teacher of graduate students, can you describe the evolution of data science and AI-related subjects as an academic pursuit? Are incoming undergraduates more prepared now to tackle these subjects than they were in years past?


Dr. Jose Mendoza: The evolution of data science and AI-related subjects at the university level reflects these fields' growing importance and ubiquity in solving real-world problems and driving innovation across industries. That growth has resulted in several key developments over the past few years:


  • Increased enrollment in analytics-related courses and concentrations.
  • Increased program offerings with new degrees, certificates, and engagements.
  • Availability of industry-relevant training, such as internships and problem-based learning.
  • Rise of online learning platforms, including massive open online courses (MOOCs).
  • An interdisciplinary approach with data science and AI-related subjects in areas such as Human Resources, Finance, Management, Strategy, Marketing, and more.
  • Early exposure through high-school courses around data science and AI, as well as pre-college programs


However, it is a mixed bag when it comes to how prepared the incoming undergraduates are to tackle these subjects. For example, there is still much work to do to ensure that undergraduate students have a minimum level of data literacy with a good foundational knowledge of mathematics and statistics.


DU: Do students in your program understand what is important in the data and AI space?


JM: Students, like most people, are aware of the hype around data and artificial intelligence. However, developing around key areas such as data management, data processing, critical thinking, problem-solving, ethics, and responsibilities is very important. Moreover, we also look at developing their skills around foundational knowledge in statistics, business analytics, and data visualization. To capture the potential of data analytics and artificial intelligence, students must be able to analyze data effectively, derive insights, and make informed decisions in various business contexts.


DU: What topic or challenge in the data universe engages you most?


JM: I am particularly interested in ethics and artificial intelligence for several reasons. First, artificial intelligence and its related technologies have a considerable influence on our lives, which raises many ethical, social, and legal questions. There is still work to do to understand the social and psychological impact of the technology. Secondly, reasonable concerns about bias, fairness, security, accountability, and transparency around AI technologies open many opportunities for academics, legislators, and practitioners to work together. Moreover, the question of global governance brings up the need for international cooperation on standards and regulations. Finally, artificial intelligence is continuously evolving, which requires still working on understanding its impact on society.


DU: So much discussion of data-related topics is centered around AI. Are we currently putting too much emphasis on it at the expense of other technologies or challenges? If so, what needs more attention?


JM: It is understandable, given the potential of artificial intelligence. However, there are areas where we should bring a more active discussion. For example, how to deal with a digital divide in which some communities have disproportionate access to resources and technologies and the lack of universal access to technologies for some population groups. Data literacy and education are also important topics, as we must prepare the future workforce to work effectively with these technologies. Emerging technologies such as quantum computing and virtual reality will deserve more attention.


DU: How do we get the key decisions about AI's impact on society right?


JM: It’s important to continuously dialogue with the many stakeholders involved and impacted by artificial intelligence. However, we are going in that direction. An example is the inclusion of the track on Ethical AI at this conference.


DU: In addition to content like that, what do you think this new event will deliver that others don’t provide today?


The most impressive part of the event is the number of participants, topics, sponsors, and tracks. The event certainly has the potential to stimulate big ideas and collaborative thinking. The variety of topics, from digital transformation to data lakes, data science, governance, and ethics, it is certainly a key differentiation point.