Special Release! Research Ops 2.0, Episode 1: The Evolution of ResearchOps
In just ten years ResearchOps has transformed from an obscure Silicon Valley specialty into a vibrant global profession. My name is Kate Talzi, and this is ResearchOps two point zero, a five part audio documentary series all about the future of ResearchOps. In this series, you'll hear the voices of ChaCha Club members, senior research leaders, and the smart minds behind user interviews, the fastest, easiest, and most affordable way to recruit participants for user research. This is episode one, the evolution of ResearchOps. In this first episode, we'll explore what's pushed ResearchOps to evolve so quickly and in true two point o style, what the future holds.
Speaker 1:Here's Erin May to kick us off.
Speaker 2:I'm Erin May. I am the CMO at User Interviews.
Speaker 1:If you've ever listened to the podcast Awkward Silences, you will know Erin's voice well. Erin's about to run you through a simple generational framework to understand the past, present, and future of research ops. There's Gen one, the lab engineers, administrators and recruiters who emerged around 2010. Gen two, the ResearchOps professionals of the present who are rewriting the rules and building sophisticated research systems. And gen three, the agentic designers and consummate data architects of the future.
Speaker 2:So gen one really responding to some pain that was happening with the scaling of research, which was a wonderful thing to see, not the pain, but the scaling. Research has earned its seat at the table. There's a demand for research. The wheels are flying off the bus. We need research ops.
Speaker 2:And so they're problem solvers. Right? And we don't know what our tools exactly are or what the systems are gonna be. We don't have a big community of people to talk to to figure this out, but there's a problem we're gonna come in and fix it. And so that was kind of gen one, which is, you know, fun.
Speaker 2:It's scrappy. It's startup. It's first principles. Right?
Speaker 1:That's a perfect summary of the early 2000s when the WhatisResearchOps movement inspired hundreds of people around the world to collaboratively define research ops. And optimism, inventiveness, and even naivety were in full supply.
Speaker 2:Now that group is hiring gen two, right? And gen two is it's different. There's more of a sense of what research ops is. Some of these initial challenges have been worked out. But of course there are new challenges now, which are some of the macro that we've been talking about and the reinvention of what re ops is, having sort of figured out gen one.
Speaker 2:So gen two is gonna, go through a different kind of change and a different kind of figuring things out. And then, of course, gen three in the future. We've talked about AI, but that's gonna be all over gen three. I I have a feeling and I'm excited. I I I can imagine a world where gen three is just making an even bigger impact per person, if you will, both through technology, but also through reimagining what re ops can be, as a sort of brain and nerve center of the organization.
Speaker 1:Erin has set us up beautifully. Let's slow it all down and dive into each generation one step at a time. Lexi's gonna kick us off with a deeper exploration of Gen one.
Speaker 3:Hi, everyone. I am Lexi Breitz. I am the Director of Research, Data Science and UX Operations at Workday. At the beginning, there was lab support. So we had this incredible person who was there supporting all the labs set up, making sure that we had all the tools and technology that we needed.
Speaker 3:So it was really kind of tactical support early.
Speaker 1:The early 2000s were the prehistoric era of research ops, when research labs were the crown jewels of user research. But these research labs weren't just meeting rooms with cameras they were sophisticated audio visual production suites, complete with one way mirrors, high-tech gear, and control rooms that wouldn't look out of place in the world of television broadcasting. Here's Kayleigh Dankner, the senior manager of research operations at LinkedIn. Kayleigh has similar memories to Lexi.
Speaker 4:So yeah, like Roland was our lab operations specialist. He came from media services,
Speaker 1:I want
Speaker 4:to say something like media productions. That's the name of the team. So he was there just to make sure that all of the mics were working, all of the video equipment was always working so that they could produce a lot of things post research. But it was not at all, the thought process wasn't participants, how do we reach them? How do we make processes?
Speaker 4:The researchers felt very, like a lot of ownership from what I understand over those pieces the process and how they came together and they were very protective of it for years. As you probably remember.
Speaker 1:These are the stories of the very first ResearchOps professionals, even if they didn't know it at the time. I actually got into research ops through labs myself. I loved building labs because I could use my background from the music and radio production worlds. And in those early days, the lab was usually at the heart of how research operated. But here's the thing about having an all singing all dancing research lab.
Speaker 1:First, the day to day management of an in house lab involves a lot of downtime and you need people to do research within the lab AKA research participants who also need to be guided to the lab and settled in. So as the demand for research scaled, many researchers eventually did hand participant recruitment over to a friendly ops person to help.
Speaker 5:Yeah. I was the person in the lobby meeting and greeting, and it was, like, end to end service, basically, walking them to the labs, everything like that. So I kinda, like, got my start at the very, very beginning and bottom in some sense and was like, alright. Let's grow this. So That's
Speaker 1:Tim Toy, the senior manager for research operations at Adobe. Tim set a research ops job title since 2010. He is a trailblazing original. Tim takes us back to that time.
Speaker 5:It was pretty stressful at times because, like, if you recruited five people in one day and four didn't show up, you definitely felt like crap that day. And there were there were days like that because we were recruiting people off of Craigslist, so I would, like, go to Craigslist, etcetera category and say, hey. We're doing an acrobat study for $75. And we would screen on, like, a Excel spreadsheet. You know?
Speaker 5:It was, like, the very there weren't, like, Qualtrics or any platform.
Speaker 1:But Tim's experience wasn't unique. Garrett Sukada, another ResearchOps trailblazer, had a similar experience.
Speaker 6:My name is Garrett Sukada. I work at Intuit and I lead the Center of Customer Obsession Research Operations team. I spent years in college not knowing what I did, and I ended up with this anthropology degree. And eventually, while working at this educational software company, I saw this role for UX researcher open And within that, one of the criteria was, it's like, you want to have a degree in anthropology. And I'm like, this has got to be assigned because who wants somebody with an anthropology degree?
Speaker 6:Like, I don't even want an anthropology degree. And I started off as, we'll say like a UX researcher at that company.
Speaker 1:Garrett's got this great story where he actually applied for the wrong job and landed up in a research ops role. This was like way back in 2014. The good news is that Garrett stuck with it, saw a ton of opportunity, and now runs one of the most mature ResearchOps outfits in the world.
Speaker 6:The role was nothing like I had expected it to be. I thought there was going to be more of the relationship building and kind of there was part of that with teams and helping them connect with customers. But really, my role was like 80% full service recruiter, where every day it's just like calling customers, you know, able to screen them, schedule them, compensate them, going back to the teams that I'm working with, ensuring that people are showing up and, you know, they're on time and there's no shows within their labs, but I did that for probably about three years and I
Speaker 5:decided I don't want to
Speaker 6:be a research recruiter anymore. And I really realized that there's a lot of inefficiencies in the team that I was on. And I really started to operationalize more of the process. And I think this was still before the term research operations was even coined. So wasn't research operations per se, because that didn't exist.
Speaker 6:Was just part of the job of what I had to do.
Speaker 1:Here's what's remarkable about these early days of research ops. There was virtually no technology built specifically for user research. If you wanted to recruit participants, schedule interviews, or manage research data, or operationalize more of the processes Garrett points out, you had to hack together solutions using whatever was available. I did it myself. CRMs, spreadsheets, emails, you name it.
Speaker 1:Everything was manual, complicated and incredibly time intensive. So it was almost impossible to hand these tasks over to anyone else. As a result, ResearchOps was typically a full service offering.
Speaker 7:Great. I'll leave a little bit of space between two, so if you decide to.
Speaker 1:Here's trailblazer Noelle Lamb. Noelle was also an early adopter to the role of ResearchOps and has seen this evolution firsthand.
Speaker 7:Noelle Lamb, ServiceNow, Senior Manager, Research Operations. It was so nuanced in so many steps and so complicated that you couldn't expect anybody else to understand how to do it and do their job at this, like a researcher, you know, if I wanted to enable a researcher to do it, they could do it. There would be zero time for them to actually research. They would spend most of their time trying to move participants through very fragmented systems and workflows. And now it's so intuitive in systems and platforms that you just give them a login and you just say, hey, this is how you know, here's how you might do one or two things.
Speaker 7:But everything is taught within the tool. And it's so they make it so easy. All of the manual administrative work we were doing before is not required anymore. And if it's easy enough that someone else can do it, then that really changes the focus of our roles.
Speaker 8:We started user interviews in 2016. And at the time, we only had a rough idea who our ideal customers would be. We knew that research was we just knew that recruiting was such a pain point for people who were doing research. But at the time, we didn't have a great sense of the landscape.
Speaker 1:That's Dennis Meng, the co founder and chief product officer at User Interviews. Early research ops professionals like Tim, Garrett, and Noel wanted to make research more efficient and scalable, but they were pushing the boundaries of the tools they had access to until something magical happened. Purpose built tools began to emerge.
Speaker 8:So we knew product managers existed. We knew product managers did research. I think shortly after, we realized that researchers were they were full time researchers who felt this pain the strongest. But I think in 2016, there were not a ton of I think research ops had not been coined in the same way that it is a common job title today. So I think our first exposure was people who had kind of adopted the research ops function without the title.
Speaker 8:And I think a lot of that was There were titles of recruiting managers or it felt more of an admin role at the beginning. And then I think as we started talking to larger organizations like Atlassian, Uber, like Airbnb had a had a pretty established function, that's when we first started to see that, ah, there there are people who are really focused on enabling research at scale. And that was probably early twenty eighteen, something in that time range.
Speaker 1:I actually first met user interviews when I worked at Atlassian, and I've been a fan and a collaborator ever since. So the mid two thousands, as Dennis said, brought the first wave of purpose built research tools like user interviews. Research teams were scaling, PMs weren't the only ones doing research, and bleeping research labs were joined and sometimes usurped by other bleeping technological things. It was boom time in research. But all this new purpose built technology didn't just empower PMs and researchers.
Speaker 1:It unlocked a whole new world for research, research ops and countless fast growing companies who wanted as many of their employees as possible to spend time with customers. Introducing Sam.
Speaker 9:Hi, I'm Sam Gager. I'm a research leader in financial services. I don't know if I like that one, but Sam Gager, research leader in financial services.
Speaker 1:Sam reflected on how the evolution of research tech has changed the landscape over the past decade.
Speaker 9:The the biggest the biggest change I've seen is technology working its way into the field. And I think streamlining a lot of the processes, right? It speeds up kind of like the scheduling, right? The tooling is really robust nowadays. I mean, they're like the tooling companies have basically built CRMs for researchers purpose built, which I think drive a lot of value into the org.
Speaker 1:And all of this fantastic enablement opened up new avenues for intrepid ResearchOps professionals like Noelle to do even bigger and better things with their time. And this was the start of Gen two. The shift from lab technicians, administrators and full service participant recruiters to research systems designers started to take shape.
Speaker 7:Instead of scheduling participants in Calendly and logging into a different website to send incentives, we're using data about our panels to work more proactively, less reactively. So where we might have been recruiting for a specific study, now we can really focus on the health of our panel and the comprehension of our panel. And so when we have these systems and tools enabled, turned on in our team, and we're no longer stuck in spreadsheet sorting participants, we're looking ahead and leveraging our internal partnerships and external partnerships as well in ways that we never had time for. And so we can think more broadly, more strategically from 30,000 view instead of the 10,000 foot view.
Speaker 1:Even the notion of full service participant recruitment, the bread and butter of old school style research ops, was challenged, like seriously challenged by the tooling evolution.
Speaker 6:Over time, what I've seen is just an evolution where it's not uncommon to leverage multiple tools at this point. I think having a full service recruiting team is quite the luxury, to be quite honest, and I will say that I probably would never do again if I was to create a team again, I wouldn't do something like that. But you see the role evolve in that it's not so much about supporting one small team, it's about scale. And I'm seeing that more now within the broader research operations, their mission. I think the big thing to talk about now is democratization, right?
Speaker 1:It's not so much about supporting one team. It's about scale. That is the crux of Gen two. Sam Gager was there to see the evolution from a research leader's point of view.
Speaker 9:I think research operations can help enable best practices, set those people up for success when research expands beyond the shores of just the researchers, which I think is a net positive to any and all organizations, whether you're tech or not.
Speaker 1:Okay, we've covered a lot of ground. So let's take a moment to recap. Between 2010 and 2020, research ops evolved through three distinct phases. As we've heard, we managed research labs. Then we handled full service participant recruitment.
Speaker 1:Then tools enabled us to hand participant recruitment back to researchers and all sorts of people across the organization who needed to do research. So ResearchOps was empowered to focus on other things. None of this could have happened without the boom in research tech, as Sam pointed out. So tools didn't just fill a gap, they helped drive the field of ResearchOps in an entirely new direction. But technology and the growth of research weren't the only forces driving change.
Speaker 1:The introduction of the GDPR, the European Union's General Data Protection Regulation in 2016 an increasing awareness of data privacy pushed research ops to evolve into areas like compliance, data governance, and research ethics. And again, the game changed. Lexi describes how she saw this unfold at Meta.
Speaker 3:There was a pretty big change at Meta in my third year there. And that was around things like GDPR, privacy and legal restrictions, and Meta became more conscious of these needs. And I would say our research ops folks started to step in and really support on that. So we had more of like formalized research review process that they helped develop. That included like legal review and things like that throughout the process.
Speaker 3:So that was the kind of next evolution that I saw. And then when I shifted to being a manager, that's the next evolution that I saw. So this was really like research ops isn't sort of just a tactical partner. They're also like thinking about the end to end research process. They're thinking about how we, everything from how we prioritize our research projects to how we actually manage our impact and make sure that we're accounting for it and make sure our insights last.
Speaker 3:So once I was in the manager side of things and I was seeing more of like behind the curtain, all of the steps that go into things, then I realized that my research ops partners play like a much bigger role than I was aware of as an ICE.
Speaker 2:I'm Erin May. I am the CMO at User Interviews.
Speaker 1:We are shifting focus from the past to the future. As a recap, Erin's gonna talk us through that simple generational framework. Gen one, the founders. Gen two, the builders who scaled and systematized. And gen three, these are the architects who are creating the next generation of research ops.
Speaker 2:So Gen one, going back to around, right, 2018 when we talked about, I guess, I was on the pulse of when this whole thing was starting and didn't maybe know at the time. Gen one really responding to some pain that was happening with the scaling of research, which was a wonderful thing to see, not the pain, but the scaling. Research has earned its seat at the table. There's a demand for research. The wheels are flying off the bus.
Speaker 2:We need research ops. And so they're problem solvers. Right? And we don't know what our tools exactly are or what the systems are gonna be. We don't have a big community of people to talk to to figure this out, but there's a problem we're gonna come in and fix it.
Speaker 2:And so that was kind of gen one, which is, you know, fun. It's scrappy. It's startup. It's first principles. Right?
Speaker 2:Now that group is hiring gen two. Right? And gen two is it's different. There's more of a sense of what research ops is. Some of these initial challenges have been worked out.
Speaker 2:But, of course, there are new
Speaker 1:challenges. Such a cool note about the fact that gen one is now hiring gen two. If you've spent as much time trolling ResearchOps jobs posts as I have, you'll also have noticed that ResearchOps jobs descriptions or JDs are becoming much better defined. No longer an impossibly long laundry list of administrative tasks. Well, those JDs still exist, but they're fewer and farther between.
Speaker 1:JDs written by Gen one are more nuanced and specialized, which is great news for everyone.
Speaker 2:It's different. There's more of a sense of what research ops is. Some of these initial challenges have been worked out. But of course there are new challenges now, which are some of the macro that we've been talking about and the reinvention of what re ops is, having sort of figured out gen one. So gen two is going to go through a different kind of change and a different kind of figuring things out and then, of course, gen three in the future.
Speaker 2:We've talked about AI but that's going to be all over gen three. I I have a feeling and I'm excited. I can imagine a world where gen three is just making an even bigger impact per person, if you will, both through technology, but also through reimagining what re ops can be as a sort of brain and nerve center of the organization.
Speaker 10:All right. Mia Myszczyk, Target, Senior UX Research Operations Manager. Three point zero is like bringing it to the next ideal level. How do we incorporate the new AI tools into our workflow? How would we function if we didn't have any researchers?
Speaker 10:How would we function if we had to collaborate with this team versus this team? And I'm just thinking, like, there's so many ideas that haven't even we haven't even had time to really sit down and think through and brainstorm. And I hate using, like, the house analogy. Right?
Speaker 1:Mia, any analogy to do with civic design or architecture is welcome here, so knock yourself out.
Speaker 10:But it's like three point o are the architects. Three point zero is the Frank Lloyd Wright. It's the, you know, innovators of the space where a building's a building a building, right? Except for when you make it something exceptional. And so I think that's where three point zero could really go.
Speaker 1:MEA's architectural vision isn't just theoretical. ResearchOps professionals are already building these exceptional research systems. We are seeing teams move from reactive support to proactive orchestration, and from tactical execution to strategic systems design. The question isn't whether this transformation will happen, it's already happening. The bigger question is how quickly we can evolve as a profession to meet the demand, especially in the age of AI.
Speaker 1:Casey's proved that this evolution is already in flight.
Speaker 11:I'm Casey Gollin, and I work in AI productivity at IBM. My role has actually shifted to the point that I sometimes wonder if I am doing research ops because now I'm managing a team of engineers, and we're building what we call productivity platforms. But that's not a traditional definition of research operations or product operations. And I think increasingly, those kinds of roles to think of an operations team like a product team is gonna be a useful skill set and also a useful team composition. So it's not necessarily just operators, but you think of the team as a product and what you're delivering.
Speaker 11:And yeah, I do think it's a emerging model that an operations team is really creating the systems that deliver the operations, especially with changes in automation and AI. There's really just in the past year or two, lot around autonomous agents, which sounds a little hokey, but it does really impact this kind of operations work. So the operations team is really the ones building and designing this agent architecture. I think that's one possible future and even a near future like next quarter.
Speaker 12:I'm Basil. I'm the co founder and CEO of User Interviews. I keep using the word orchestration, right? Like I feel like there are going to be dashboards and it's going to be a level of, you know, seeing at a high level how things are flowing, right? Like is research happening?
Speaker 12:Are the insights going here? But I think of it much more as like there's a system that's been built and it's a lot more of conducting and orchestrating that system and tracking that system and seeing where things are falling away and responding to requests from inside the system. I think being able to see the flow of insights across the organization is something that no one really has right now, right? But I think that would be really cool to me. Right?
Speaker 12:If you can see like how are these insights being used? Who's using the insights? Like where are they showing up across the whole company? I don't know if we'll get there, but I think we're not even close to seeing that, like, next level there either.
Speaker 1:Basil's vision of tracking insight flow across entire organizations represents something unprecedented. True organizational learning intelligence. Today, most companies have no idea how their research insights travel, where they land, or what impact they create. Imagine the strategic advantage of knowing not just what customers think, but how insights move through the company and how they can be better placed to help shape decisions every day. Research leader Sam sees research ops as core to this vision.
Speaker 9:Research operations plays a role because, like, how do you make sure people know how to feed the ecosystem? Research operations can play a role in making sure that your PM org, your design org, or your sales org is, like, funneling the right information in to, like, empower and and help educate.
Speaker 2:I think that we haven't cracked the code on insights management, and I think that's a really vital piece of this. We've talked about recruiting and all the the numerous functions of research ops. But really, when you break down what is the value of research, what is the value of research ops, how do we learn meaningful stuff, and how do we bring that to our deciders or, you know, key, deciders of big business decisions and small in the organization. And I don't know what that looks like, but I think it opens lots of different possibilities that are sort of separate from being the co conspirator of research. I can imagine a world where Gen three is just making an even bigger impact per person, if you will, both through technology, but also through reimagining what re ops can be as a sort of brain and nerve center of the organization.
Speaker 1:Basil, Sam, and Erin touch on something truly next gen. The role of research ops is shifting from making sure the tools and processes are set up for people to do research, to also ensuring that the right information is flowing to the right people at the right time. This vision of ResearchOps as the orchestrators of organizational knowledge represents a massive expansion of scope and impact. But to be the architects or orchestrators of customer insights systems, to be the nerve center, as Erin calls it, we'll need to leverage much more specialized skills. Here's Mia Myszczyk.
Speaker 10:I really do think that research ops is going to go away from generalists, and we're going to get into specialist res ops roles because there are so many people out there. For example, like, people who go to grad school for librarian studies, and they are just their skills with repositories and knowledge management centers, I would never even be able to come close to their skills in that, you know, but I would consider myself, like, more of a generalist. Right? But I could really see res ops going into that direction of specialties. I think we're already seeing that, right, within the coordinator positions, within like those large, large organizations that have, you know, big repositories.
Speaker 10:I think maybe that will become more common. Who knows? Introducing Daniel Gottlieb.
Speaker 13:My name is Daniel Gottlieb. I am the head of research operations for Microsoft's Developer Division. So I see the direction of ResearchOps growing depending on what the needs of the organization are. And I shouldn't say expect, but I have a hypothesis that the direction this might go is we might start seeing more specialized ResearchOps types. And we already see that to agree.
Speaker 13:You see a job application that's like, this is a research op job specifically for recruiting, or it's specifically for our knowledge database. And that's what your main job is. It's not always like research ops and everything that falls under that. We're getting more specialized, and I think some of the specialties could grow and go beyond what we see as the current norms of what is research operations.
Speaker 1:Daniel is right. ResearchOps is at an inflection point. The economic storms of recent years have reshaped the product landscape and with it the research landscape too. User Interviews' 2025 budget report showed that though companies aren't always investing in researchers, they are investing in research capabilities. AI and knowledge technologies are experiencing hyper growth and ResearchOps professionals are uniquely positioned to help organizations leverage all of this to tune into their users' needs, ideally in partnership with researchers.
Speaker 1:But to make the most of the moment, we'll need to reinvent ourselves. Here's Erin from User Interviews.
Speaker 2:I think, you know, Gen three is all about reinvention. You know, it's a very transitional, transformative time in tech and in research. It's exciting. It's scary. It's not all good.
Speaker 2:It's definitely not all bad. Obviously, AI is a huge part of it, of of everything happening in technology in general and in research in particular. But to me, it's a a time of reinvention, of having moved from addressing tangible acute pains to scaling systems and really defining and becoming what that glue is going to be to now what do we reinvent? What does that look like in the in the future?
Speaker 11:When I think of Gen three, I actually think of something that I think Marty Kagan posted about the future of product teams, where product teams may move away from being these siloed disciplines. And what you might think of as the researcher, the product designer, the engineer, may just be different activities that everyone on the product team is doing in their day to day. So I think as we see where technology is headed, there's a lot of interesting advancements in engineering, where right now, you can do what's called vibe coding, where you open up an AI code editor, and you just describe what you want. And you can watch the code stream in, and then there's your application. So you've built it just by having a vibe.
Speaker 11:You know, I want this type of tool today. And I think that we might start to see that come into other disciplines. So I don't know what it looks like. But if you think of vibe researching or Vibe designing, I think that Vibe operations, yeah, what would it look like to just kind of describe the operations that you want and see it kind of stream in? And I was talking to an engineer on my team about this phenomenon of AI coding, where you can assign an issue and it's just automatically reviewed, solved, closed, and documented in two minutes, you know, while you walk away from your computer.
Speaker 11:And he was saying, you know, what's left? You know, should I get into sweater weaving or something? You know, should I get into knitting? Yeah. And I think what is left is thinking, and planning, and making change.
Speaker 11:Because what we're seeing come into the picture is almost like this brute force loop of solving a problem a thousand times in a row. And right now, that's being called thinking in the AI field. But it's really not the same type of thinking that somebody that understands the shape and the politics of an organization is doing. So I think that in the third gen of operations, it really is going to be a world where you're not assessing yourself based on the number of goals that you've completed or operations, you know, that you've done. That stuff is just commoditized.
Speaker 11:But it really is about how you can solve problems in new ways, create change, and that kind of puzzle solving and creative thinking is not something that a computer or any kind of automation can do.
Speaker 13:Well, as we enter into Gen three, everything in I want to say tech, but really everything in the world is being impacted by AI. And how is AI going to change what we're supposed to be doing? I think for Gen three, for research operations, what's exciting is we just got access to this tool that is going to really help people be able to do research. And it's a tool that even at first the promise is like, It's AI. You just tell it what to do and it's going to help your research project go better.
Speaker 13:It's not that simple. You still need to wield this tool appropriately. You still need to be intelligent in the way you use it and strategic in the way you use it and responsible in the way you use it, both ethically and in terms of getting the right research results. So like any tool, you need somebody to help you use that tool and give you the right guidance and find the right tool because there's good AI tools out there and there's bad AI tools out there. And so research ops, I think, are primed more than any other role to be able to help people use the tool, find the right tool and use and when I say that, I mean use AI, find the right AI, understand how to use AI and then work with it.
Speaker 11:There's really just in the past year or two, a lot around autonomous agents, which sounds a little hokey, but it does really impact this kind of operations work. So the operations team is really the ones building and designing this agent architecture. I think that's one possible future and even a near future, like next quarter.
Speaker 8:Today, talk about researchers. We talk about powders. There are two different personas within the organization that are conducting research. But as you move forward, I think it's very likely that researchers and POWDRs will not be the ones conducting research. I think they'll be thinking more about research strategy.
Speaker 8:But I think AI agents, whether generalized AI agents or AI agents within software tools are conducting research, I think that would be much more common over the next few years.
Speaker 1:I asked Dennis how he thought the primary definition or job function of research ops would change as a result of AI, not to mention the evolution of research and knowledge management in organizations. Here's what he had to say.
Speaker 8:Yeah. This is I mean, obviously, is relevant for us at user interviews. We don't think about the definition changing very much. We think enabling research at scale will be an important function at every organization as, you know, in the age of AI and whatever comes next. We think what it looks like may change.
Speaker 8:So the amount of enablement being done, the volume of research being done, we hope that increases a ton. And so we think what it takes to enable research at scale, I think will change even more. One of the things that I think about is who the constituents are for research ops. Today, talk about researchers, we talk about POWDRs. There are two different personas within the organization that are conducting research.
Speaker 8:But as you move forward, I think it's very likely that researchers and powders will not be the ones conducting research. I think they'll be thinking more about research strategy. But I think AI agents, whether generalized AI agents or AI agents within software tools are conducting research, I think that would be more much more common over the next few years.
Speaker 1:AI agents doing research? It's all pretty mind blowing, and that's even old news these days. The transformation is happening so quickly, and it's happening right now. The basic premise of ResearchOps is no longer about solving small problems, firefighting or administrating. It's about solving knowledge problems in entirely new ways and creating systemic change in how organisation learn and make decisions with and without AI.
Speaker 1:But to do that, we need to become highly strategic systems designers. And in ResearchOps teams around the world, we're already seeing that crucial change.
Speaker 10:With research ops professionals, we always know where we can improve. We always know what we're measuring, what we should measure, what we want to measure, and how that all trickles up into the success of either the team or the organization. And I think I tend to see that in res ops folks, that they really have this strategic bird's eye view of how does their work impact the research org, but also how does their work impact the entire org. They don't tend to have their head buried in the sand in the corner. They're very like wide lens for sure.
Speaker 11:Our team have pivoted almost entirely around AI, which is maybe no surprise given what's going on in the industry and in the news. And there's a lot that we're excited about. The next biggest thing is the concept of these agents in a product team.
Speaker 8:I think research ops really needs to think about what are the controls and systems that we have in place for a world where you have a third constituent. It's not researchers, it's not powders, It's these autonomous AI agents, and how do you keep them under control within the organization? I think that's my overarching thought for the next five years or so for research ops and AR.
Speaker 1:All of this evolution from lab technicians to full service recruiters and then organizational knowledge architects and agentic designers, the fifteen year transformation has been breathtaking. And it's only the beginning. The next chapter where artificial intelligence doesn't just assist ResearchOps, but fundamentally redefines what's possible is already being written. And that's where we're headed next. The next episode of ResearchOps two point zero is all about leveraging AI for research superstardom.
Speaker 1:To get this and lots of other ResearchOps goodness delivered straight to your email inbox, subscribe to the ResearchOps review. Find the link in the show notes. This series was produced by The ChaCha Club, a member's club for ResearchOps professionals. A huge thanks to User Interviews for sponsoring this series. User Interviews is the fastest, easiest and most affordable way to recruit participants for user research.
Speaker 1:Finally, ResearchOps two point zero was co produced with Glenn Zamilton, Jenna Lombardo, and Renata Venter. Thank you to our guests for giving their time too. I'm Kate Tauzy, the founder of The Chartered Club, a ResearchOps guru, and the author of Research That Scales.
Creators and Guests
