By Zoë Billington, UX Research & Customer Insights, Los Angeles, California, zbillington@gmail.com
This quarter, I met with Maria Bezaitis, a humanities-trained UX researcher and former Intel Fellow who brings social insight to business and technology innovation. She has led research programs on personal data, AI and decentralized computing, risk and adoption in security, and the changing nature of ownership. She started her post-academic career at E-Lab, a small consultancy that pioneered the use of ethnographic research for consumer product development, brand strategy, and work processes. She was also vice president of experience modeling at Sapient. Bezaitis then joined Intel from 2006 to 2024 to run its R&D investment in human-centered innovation.
Zoë Billington: Let’s start off with the 10,000-foot view of your career. How do you tell the story of how you got to where you are today?
Maria Bezaitis: I describe myself as a humanities-trained research leader. I know how to build organizations that center on understanding meaningful shifts in human behavior to identify new business opportunities that matter to people.
In many respects, my career story is an immigrant’s story—meaning I got into the applied ethnographic research space initially because I was leaving academia rather than going toward something I knew. When I finished my PhD in French literature in the mid-’90s, there was nothing called UX research. Doctoral-level training in literature didn’t feed into industry jobs. I wasn’t interested in spending a career working on academic publications in the context of a single university that I might have zero control over selecting. So, I left academia.
I ended up finding a set of like-minded people who were building a startup called E-Lab, which developed research and design methodologies for consumer products, packaged goods, and work processes. From a research standpoint, E-Lab based its offering on ethnography, but its differentiator wasn’t the ethnography alone. What E-Lab really specialized in was the development of research-informed frameworks for design and then the planning work to address business opportunities.
Despite not having a background in ethnography, I found a connection between my academic training and work at E-Lab: I was reading texts, which is what I had been doing in graduate school, but these texts were people’s everyday lives. I knew how to interpret that data and hone in on the ideas that were compelling organizational points in the data set. Because that’s the challenge with data—it’s not just collecting the data; it’s knowing how you are going to read it and make decisions about what’s most important. How should someone who doesn’t know anything about a particular sphere understand what is most important about it? While that’s not intuitive work, it felt intuitive to me because that’s what you get after 10 years of reading fiction and being trained in theory: you learn how to read, interpret, filter out, and then explain that to your audience.
Zoë: How do you think about your relationship to anthropology and ethnography today, as someone who identifies as a humanities-trained researcher? I imagine there are readers out there who, similar to you, leverage ethnographic principles in their research despite not having a background in anthropology or ethnography. So, hearing more about how you position yourself in the industry could be helpful for others working on their own personal narratives.
Maria: Many of my colleagues were able to advance their industry careers as anthropologists, referencing both their training and their actual jobs. I could not use my academic training that way because if I were to walk into meetings talking about myself as a literary critic or as a student of French literature,
I would have been laughed out of the room. No one would have understood what that meant. But ethnography aligns with me personally in the sense that the ethnographer
is someone who writes, interprets, and produces texts.
It’s the writing dimension of my work that draws more from my own background in literature—the emphasis on language, interpretation, and text. At E-Lab, there was a lot of emphasis on language and narrative. By “narrative,” I don’t mean storytelling alone; I mean the underlying organization of everyday experience: the central behaviors that people adopt to make life meaningful. For example, the importance of “routines” in how people use certain retail channels. The most useful research hones in on those concepts and builds them out in robust detail so that design can use that material as a basis for intervention.
At Intel, the output of our work could take the form of internal briefs, white papers, and select external publications. I had the time and support to do the actual writing as a deliverable for internal audiences. For better or worse, I even approached PowerPoint presentations as a writer, meaning with a focus on language and argument. So, I encourage researchers and consultants to think about how their training—in whatever discipline that may be—also shapes their outputs, not just their research methods, in a unique way.
Lastly, I’ll say it did take time; inside a big corporation like Intel, diverse backgrounds are often regarded with more tolerance and positivity as a person gets into more senior positions. As I advanced in my career, it became more possible for me to talk about myself as a humanities-trained researcher and as someone who had a background in literature. It was personally important to me to be both recognized as a particular kind of “scientist” and to bring more diversity to the minds of my colleagues for what kinds of fields can contribute to research that is useful to companies.
Zoë: Let’s talk more about the two big career transitions you went through—from academia to consultancy, and from consultancy to working in-house at a big corporation—and some of the lessons you took away. What do you think is important for people to know who are making these types of moves?
Maria: The challenge in the move from academia to consulting was simpler. It was about learning how to work with people, how to talk to people whose backgrounds were not like mine, and then learning how to take direction from clients who wanted to have a hand in aspects of our approach and work. Those aren’t lessons you learn quickly or overnight; it takes time and practice in a real-world context. The advice I would give someone making a similar transition is to apply all your good listening skills to working with new colleagues and stakeholders and develop some good breathing practices.
Going from the consultancy startup to working as a research manager in a large multinational corporation was very different and probably much harder. Here, the first order of complexity was like an adolescent growth period, where you learn that the world is not going to revolve around terms that you already understand. I walked into a setting that had a very different set of values, norms, and requirements that shaped how people did their work.
For example, in a classic technical research organization like Intel Research, which was the Intel Labs division I was hired into, people were rewarded by pursuing an individual research agenda that they outlined and had a lot of authority over. I had come from consultancies where people worked on interdisciplinary teams to solve problems for clients. Additionally, since I was hired as a manager, there were a set of pressures that were already part of the environment that were shaping how people treated me and how they perceived me. Compared to the startup, where there was much less hierarchy, my role inside the corporation felt much more rigid. Coming to understand this new world and how to function successfully in it took me multiple years.
What I learned from this transition, and what I would say to others, is you have to have patience. Things moved slower than I had been accustomed to. First, I had to learn how to worry less about interpersonal dynamics and give people space and time to do their work. Then, over time, I was able to uncover opportunities to bring to the organization that others could not see because they were opportunities that went beyond the individually shaped work agendas people were used to. For example, one of my biggest early successes was hooking my team into conceptualizing and executing the innovation processes for a major set of Intel product opportunities in 2008, which involved working with architects, engineers, and planners out of our Israel Design Center. We set the foundation for requirements for two new Intel products.
Zoë: For readers that have never worked in an in-house or “client-side” setting like this, can you share a little bit about how research projects were initiated and eventually socialized to stakeholders in your role at Intel?
Maria: Our job was to observe and focus on what was emerging from tech culture, from digital culture, and work to interpret that back to the company so that it could start to understand how quickly things were moving. An early example would be the appearance of the iPhone in 2007 and the growth of app culture. So, what did that mean? What everyday behaviors would change as a result?
We also started to investigate the rise of visual media and smaller form factors. PC culture had been based on text and keyboard inputs, and all of a sudden, by 2008, communication was clearly shifting from text to visual media, and these material changes would start to enable new social experiences for people. We researched that trend and what it represented and explained those evolutions to our internal partners: Intel’s architects and engineers. Our work shifted the emphasis of two key Intel products at that time to processing requirements that would be capable of much more mainstream media manipulation.
At the time, inside Intel Labs, which invested deeply in academic research, it was entirely possible for an individual researcher to pursue a research agenda that was completely disconnected from near-term business goals. For people who are in in-house UX research roles today, the research they do is usually tied to product development and business processes from the start, so this might sound like an antiquated idea. But since that wasn’t the norm or expectation in Intel Labs, it was transformational to the company that my team was able to tie its work to product roadmaps.
Zoë: What were your methods for investigating these topics and sharing learnings back with your internal partners? Can you give readers who have never worked in-house before a sense of your toolkit and resources?
Maria: We did what any kind of good applied researcher does with these kinds of problems, which is to say we asked ourselves: where and among which populations are we likely to see the most interesting embodiments and expressions of the particular topic at hand? An example would be the fieldwork we did in 2017 in China to understand networks of connections and relationships as a way into our wireless communication group’s thinking on distributed computing and novel infrastructures enabled by 5G silicon. In that case, we were looking for particular values and behaviors that exposed how networks were activated in a cultural context that is deeply dependent on them.
Fieldwork that involves collecting data about real people and everyday lives has particular importance. Over the course of my years at Intel, fieldwork provided a unique way to educate Western business leaders, for example, on culture and norms in different parts of the world. In the early years, we were funded to work globally, so the work had global scope. Then, if we really had the luxury of resources, we would hire an external agency to help scale the fieldwork faster than we could by ourselves. Usually, we design, execute, and share all of the fieldwork-based research ourselves in-house.
But fieldwork wasn’t always a requirement. My job was to find the right sources that we could use to move our engineering and business colleagues’ thinking from flatter ways of thinking about a space like “smart technologies” to enable a larger, more robust space for innovation. In the context of “smart technologies,” for example, I used academic essays that have explored the concept of skill and analyzed the historical evolution of the term “smart” and its appearance in all sorts of settings, including the military in the 1950s and ’60s to provide good working definitions of the topic.
This kind of analysis was more in line with my academic training and helped my stakeholders understand the assumptions embedded in the language they were trying to harness for innovation. I encourage researchers to think about the tools and methods that were useful during their own training and consider how they translate to business contexts.
Zoë: What advice would you give to our readers who are positioning and repositioning themselves as they navigate their own career transitions, either between academia, consulting, and in-house, or otherwise?
Maria: You’ve got to keep doing your work, you have to keep building relationships with new colleagues who see the value in what you do, and you can’t be afraid of the technologies that are emerging today to automate aspects of the work. We are competing not just with new AI tools but also with colleagues and other types of researchers who think that they can do the work that we do. So, how do we function in that kind of environment? We have to embrace these changes, build new ties, and, in the course of developing these relationships, clarify for ourselves and our partners our unique values. Maybe there are aspects of the work that other people can do more effectively, and that’s fine. But that refinement of our value shouldn’t be something that we’re afraid of.
Relationship-building is not a skill that comes naturally to researchers. I think it is one of the things that absolutely distinguished me in the context of my career; the value that I’ve been able to provide the teams that I have been responsible for is that I tune into my stakeholders’ needs pretty quickly and am quite fearless in pursuing solutions to their needs. Most researchers wait for research opportunities to come to them—for example, they wait for someone to submit a research request or approach them with a question about users. But you don’t grow and advance in big companies if that’s how you behave. You have to go out and find the opportunities yourself by building relationships and initiating conversations about how you can help them via research that addresses their questions.
Zoë: That’s great advice. Thank you, Maria, for sharing your experience and wisdom with us.
