From Classroom to Career: AI's Role in Job Interview Success

In this episode of Innovation Fuel, we explore the transformative power of artificial intelligence in career readiness with Imran Muna, co-founder and director of strategic partnerships at Instage. Discover how AI-driven simulations are revolutionizing experiential learning, helping students build confidence and develop essential skills for job interviews and presentations. With insights from leading institutions and inspiring success stories, this episode sheds light on the future of education and workforce training.

Transcript

Imran Muna talks about how artificial intelligence can help prepare for careers

>> Dave: Welcome back to Innovation Fuel. Today we're talking about how artificial intelligence is being used to build confidence, prepare for careers and transform experiential learning. Something that I'm very passionate about. I know my colleague Gelareh here, the co host here, is very passionate about our guest. Imran Muna, is the co founder and director of strategic partnerships at InStage a Toronto based company that's redefining career readiness through AI driven simulations.

>> Gelareh: In stage help learners practice real world skills like interviews and presentation through immersive 24.7Virtual experience. Their tools are already helping learners across institutions such as the University of Waterloo, Seneca Polytechnic and Northeastern University, as well as organizations like the Government of Canada, IBM and Scotiabank.


Imran Muna is using artificial intelligence to help students prepare for interviews

Let's welcome Imran Muna to another episode of Innovation Fuel. Hi Imran.

>> Imran Muna: Hi Dave. Hi Gelareh. Thank you for having me here. I'm excited to be part of the podcast today.

>> Dave: we're so excited, my friend. What you're doing with InStage and the story that we're going to tell here today is beautiful. But I first have to recognize that today is October 31st when we're recording this. And I want to recognize that there's a big event that's going to happen in Toronto and when this actually drops, I hope it's going to be the basis of today that the Toronto Blue Jays will win the World Series.

>> Imran Muna: I hope so too. I am definitely hoping that it's exciting day over here for sure.

>> Dave: Many institutions are exploring AI based learning tools, but they often ask, does it really work? How does InStage show the comm that communication skills developed in a simulated AI environment actually transfer to real world performance like job interviews, presentations or client meetings?

>> Imran Muna: You know, it's funny, I was just talking to a couple of our partner organizations about that. What kind of stories can we tell to highlight the benefit of this technology? And I was speaking with Norm McRae, the Associate Provost at the University of Waterloo, just earlier this week and I really like how she put it. What she said was, in an ideal world, if we were preparing students for an interview, it would be amazing if we could have employers come in and help them practice as many times as they need, ask them questions, give them feedback. But from what I have seen, students need to practice anywhere from five to a hundred times for an interview. And so as soon as you start scaling that need out, it becomes extremely difficult to organize something like one on one practice interviews for every student, especially at, institutions like that and some of the other institutions we work with. So what AI can do is give students that customized learning opportunity so they can practice as many times as they need in an environment that still feels very close to the real thing. And I'll share a quick story on that in a second. But that's where I believe the true benefit is, is being able to customize the learning experience for each individual student. Because not only now can they practice as many times as they need in an environment that feels real consistent. They can also get personalized feedback. That's how sophisticated these systems are based on what the student says. For instance, In stage can give them very specific feedback on how they can tailor their answer to be more relevant to the job they're specifically interested in. And we had a student come through the system around this time last year. She had recently graduated, and she was a mature student. She had said she spent 10 years prior to going through her program working as a farmhand, working with horses. And her joke was, on a farm, you never have to interview. There's always work to do. You can just show up. But she had decided to go back to school to become a 9-1-1 call taker.

>> Dave: Oh, okay!

>> Imran Muna: And I know an incredible calling and some amazing stories from her that I'm excited to share as well. But after graduating, she said it was an extremely competitive job to interview for. And they actually told her during one of her interview processes that there were a thousand other applicants for the role she was interested in. But she told us that she had practiced with InStage because she had never been to an interview before. And so, again, I think that's the benefit of this technology, is that she told us the interview simulations felt exactly like the real thing. And so when she actually did interview for the real job, we're, proud to say she went on to get that position over a thousand other applicants. And she keeps in touch with us. Now. She told me just about a couple months ago, she helped deliver her first baby as a 9-1-1 call taker.

>> Dave: Wow!

>> Imran Muna: And so that is kind of the full circle experience that we're seeing happen here, is that people are going from having never interviewed before to being extremely competitive in the field and going on to do the work that they're excited and passionate about.

>> Gelareh: That's so nice.


How did you train your AI to make the simulations be successful

I just have a little bit, technical questions here. How did you train your AI to make the simulations be successful?

>> Imran Muna: It's definitely not something I can't take all the credit for. We have an amazing team behind In Stage, an extremely hardworking development team. I like to say they don't sleep much here. They're always working on something new. But we've done this development and training really in collaboration with our academic and nonprofit partners. So from the very beginning of InStage my co founder and our CEO, Michael Kaley has been extremely adamant that we don't build this in a vacuum, that we continually look for feedback and ask for insights from these institutions. Who we are building the technology with, truly with. And so as we iterate on the versions of this technology we offer, we're constantly asking, is the feedback in line with what you would have given students? Are the questions in line with what you're hoping they're prepared for? Is the experience matching what you would want to have happen in a one on one meeting so that we're getting as close to that experience as possible? And so that's the kind of training we do, Larry, is we're constantly asking for that feedback and refining the guardrails around this technology.

>> Gelareh: That is fantastic! First time users, I mean for anywhere you go can be scared of talking to an AI, an avatar, trusting an AI. The design choice in a stage made to help a non tech savvy or non tech users feel comfortable and stay engaged during their first simulation. How you did that, how you made them comfortable to talk to an avatar and a human?

>> Imran Muna: It's been an interesting learning process. So initially what we had was what felt like a zoom meeting. Students and job seekers would go through what felt like a zoom meeting with these avatars, with these characters that you could tell were not real people, but responded the way real people would. Part of the technical choices we made were based on the state of the technology itself, what rendering technology was available, what kind of animation technology was available. But also we had to keep in mind the systems that many of our users were using. Some have very high In the latest computers available to them. others don't have access to that type of technology. So we needed to build so that it was as accessible as possible. And so there were times where people would ask, you know, why don't you make the characters look like they do for a movie? And we said, well, there are lots of reasons for that. Those are pre recorded, they're pre rendered, they're not happening in real time. And even if we could do that, it would mean that we limit a large segment of our user base from being able to actually make use of technology like that. So that's part of the thought process. There is what's possible, what is accessible, and then what can we do to make it like you said comfortable for them to engage with these characters. So we've come up with actually a couple different types of personalities they can choose from. So for ESL learners, students or job seekers who are new to the English language, we have a specific personality that they can engage with where the characters are not making too many Canadian based jokes or things that they may not be familiar with. And then on the other side of the spectrum for advanced learners, we have ah, a humorous setting where the characters are making jokes and asking them things with expressions that are common in the Canadian workplace. So they can get used to that. And then the last thing I'll say is one of the latest innovations we're working on is making this a phone call based experience so that you're actually not seeing a character anymore. You're just having what feels like a phone call. And the characters do disclose that they are AI characters. So you hear that initially, I think that's part of what gives people a sense of what they're in for. But there is also a precedent to overcome. I think a lot of people are expecting the classic sort of phone call with an airline type experience where the characters can only say certain things. But that has changed greatly. These characters really do respond to what you say. So it does take people, you know, a couple back and forth, a little bit of conversation to realize, oh, these characters are really responding to what I say. That's kind of what goes through our minds as we think about how to make the first experience a good one,

>> Gelareh: Gelareh. Sometimes when you are dealing with AI and avatar, you just say that, okay, you don't get what I'm asking! Just connect me with a human!

>> Imran Muna: Yes.

>> Gelareh: Okay, so the most reason is that I don't know how to prompt. But how did you solve these issues in your simulations? Is there any point that I just say that connect me to a human?

>> Imran Muna: I will say that I think that issue is going to change in the near future here. If you're still experiencing that, you're probably not talking to a system leveraging the type of voice AI that's available today. Those types of legacy systems have, I think, set the standard for what people expect because they really are limited in what they can respond to. They're waiting for certain keywords and then they have a bank of responses. And it's, you know, something that we experienced many years ago when we were trying to do this before. AI is, you know, what it is today. But now you're most likely not going to experience that in something like in stage, because these are dynamic responses, they, they are taking into account what you said. If you say something like, you know, we don't have a customer service based conversation, but if you say something, for instance, like, oh, this weekend I'm excited to go to my friend's wedding, if you're getting asked some sort of icebreaker question in the interview, they'll say, oh, that's great, congratulations to your friend. Right. It's that dynamic that they're going to pick up on these little things in the conversation. So it's just a benefit we are reaping of how advanced AI has become over the years.

>> Dave: And it's really interesting.


InStage uses artificial intelligence to help students deal with sensitive workplace issues

And Amber and I want to go dive further into this Imran, because I think, you know, one of the things that it sounds like you're conquering with In stage is this empathy piece. Because technology and empathy is the big thing here. The dynamics of we can go into AI and artificial intelligence, we can do all these things with artificial intelligence. But when it comes to something like what In Stage is doing, when they're being that bridge for that student, being that supportive element and helping with the feedback and creating empathy around this, if a student has a really bad experience and they're looking for that support, how do they go about that element?

>> Imran Muna: It is an important factor to keep in mind, and it's something that is becoming more and more important for us to play our part in because we are expanding far beyond doing only mock interview type conversations. We're doing a lot of what we call guided reflection now, where students will have conversations with these characters and these AI guides as they go through something like a work integrated learning experience or a co op experience. And they're checking in and talking about the difficulties they might be facing in the workplace, the challenges they're trying to overcome, the goals they're hoping to work towards. And as part of that conversation, sensitive material can come up. And so we've drawn a very clear line that InStage is not designed to intervene and help students work through some of those more sensitive issues. But what we can do is alert faculty at scale that, hey, this student might need someone to reach out to them. Here's the information you need to make a difference and help in that moment. And that comes from work with our partner organizations. They were telling us that these reflections are not new. They've traditionally been done in a written format and, and students would write about challenging moments in the workplace that would take faculty a long time to address because they're physically reading such a large volume of these reflections. Whereas now we can analyze the transcript of these conversations. Students are more comfortable, many of them talking about it than they are writing about it, and flag that a student needs help much quicker. And so I think that's the kind of role we're playing from an empathy standpoint is that there's a way to express these concerns and then students can get the help they need from faculty who are trained in these issues.


It does take early adopters to drive innovation

>> Dave: Specifically, specifically going further into this element because one of the things that we talk about is innovation and you're doing something very innovative. And when we think about innovation, there's the, the innovation are the innovators and there's the early adopters and there's early believers that need to buy into your system and you buy into your idea. So where are some of these first institutions, organizations that are champion in stage, and what convinced them to take that early leap with you, create that partnership with you?

>> Imran Muna: Yeah, that's a great question, one I would love to ask them as well, because I agree it does take early adopters. And the institutions that come to mind for me are places like the University of Toronto, Seneca Polytechnic, who we've been working with for, you know, over five years now. Long before Chat GPT became a household name, when AI was again, not something everyone was using or aware of the potential of. and so with institutions like that, I think the leadership in place was critical. There was an openness to trying new things and to learning about what was possible and a willingness to develop this alongside us. So I think that's where it comes from is again, it's actually, I think events like the one we met at, so for instance, where you see a lot of these innovators come out that are excited to share the work they're doing and are willing to ask questions about what is out there and what are other people doing. That's where I think we've met a lot of our early champions, is through events and community based opportunities and experiences like that. And I think we've come to develop friendships with them as well. We're genuinely interested in trying to help solve some of the problems they have. They're genuinely excited about developing the technology that we're working on. And so it's a combination, I think of luck being in places where people bring these kinds of ideas forth and are receptive to them, and then patience, I think as well on both sides. I think we have definitely benefited from the patience of these teams and organizations as we have worked through some of the things they have asked us to develop and on our In as well as we try to get this product to be what we've hoped it could be over the years.

>> Gelareh: I totally feel you. Because in academia, I mean, it's all. Everything is through relationship, you know. Yes, especially a faculty relations faculty. They like some tools and techniques they advocated. They talk to their colleagues from the other schools in their seminar conferences. And, that's most of the time how it works. So how did you try to work through the word of mouth from faculties that they are early adopters or career centers that they are early adopters?

>> Imran Muna: I think we tried to remember that we can't go into this just asking for what we want. We need to get a sense of what these first of all institutions are, ah, working on what is important to them. And in the beginning for us, what we could do as a small company was support the events they were running. So we would participate in the entrepreneurship programs, in accelerators, in events that we could sponsor. That was the early contribution we could make is to support the innovative events they were trying to run and come out there and try and highlight the work that was being done by the early organizations who were willing to try very small pilots with us. I think one thing we've learned along the way is that again, we're not doing this alone. And, it's important to recognize the work being done by others as part of this larger development plan we have. So I think for us early on it really was getting involved in the events at different schools. And they could be small, they could be large events, but being there, setting up a booth, contributing to the panels and the keynote presentations, offering to share insights genuinely not, you know, as a promotional tool, but we became part of the community in a genuine way. And I think that's kind of to your point, Gelareh, is where we started to make some of these friendships and build these relationships. And sometimes, you know, the first relationship we made would not be someone who became a customer, but they might mention it to someone who said, oh, you know what? I actually need a tool like in stage and a, relationship would form out of that. But I do have to give a lot of that credit to one of my other co founders, Nicole McLean, who is a natural relationship builder that way and who has a way of genuinely engaging with people and learning about what their needs are and being able to forge some of those connections for us that way.


How do you nurture relationships with early adopters of new technology

>> Dave: So how, Imran, how do you guys then, okay, I've got these advocates, they're engaged. How do we then nurture that element? How do we Nurture that network and help that network expand this idea to other institutions that might onboard.

>> Imran Muna: It's a great question. It's something we ask ourselves actually regularly, is how to nurture these relationships. And one thing I have learned, it's a lot of the work I do, is to maintain contact with these champions. So you're not just giving them a new innovative technology and once the check is signed, leaving them to figure out how it works. I personally am constantly running onboarding sessions and I'm in meetings where people are asking, how can this be used? And early on, we would set up a lot of the initial technology the way a staff member would, so we would fully understand what the assignments they were working on were. You know, we would ask, what did this assignment look like before in stage? How were you doing mock interview assignments? Okay. Once we understood that, here's where we think in stage can work, here's how much we think it could be worth. Here are the instructions you could send to students. And then we were on call constantly. In the early days, if there was troubleshooting to do so again, faculty didn't feel alone and like they had purchased an innovative software that they now had to figure out how to use on their own. we've had a very high touch relationship with our early champions to make sure that they were supported throughout that initial usage period, so that if there were any questions, we truly understood what they were going through and how to help and we could answer quickly. We didn't have to get up to speed because we were already part of things things. And that continues to today. We have, now at this point, almost 10 years later, developed many systems that can help with that. But the premise is the same, that we keep these high touch relationships in place so that it does foster, you know, a true collaboration. And it's not transactional that once the contract is signed, you're on your own. It's not how we do things, because...

>> Dave: In institutions this happens all the time where new technology comes in, it's adopted in, and it's not supported, and then you see it just die on the vine.

>> Imran Muna: Absolutely. And it's something that, we actually hear early on is, we'll hear many times about our competitor technologies and I'll say, oh, you know, that's great, it's good. You have something that you're using, you know, what do you think of it? And many times I'll hear, oh, I haven't tried it. I'm not sure how it works. And so it was an early lesson from us to go, okay, if we're going to get this in here, it's not good enough to just convince someone to bring it in. It's in our best interest and theirs that we are there to help them use it and that, it's a win win if they are using it and excited about using it. And another unexpected lesson we learned was that initially this was intended for students. You know, how can we help students become better job seekers? How can we help them get the roles they're interested in? But just as important was how do we do that without overburdening staff with a new technology? So what do we need to do to make it easy for staff to use and easy for staff to share with students and explained to them? So there were actually two very important groups of people we had to keep in mind as we developed it, that the technology was easy to integrate into a program and connect to existing systems, and that it was helpful for students.


InStage started as a virtual reality product. What's your biggest challenge scaling up?

>> Gelareh: I have a final thought. It seems that you have a great product. You also very good establish yourself with some of the early adopters. What's your challenge? Your biggest challenge for scaling up, is it technology? Is it more society? Is it more community? Is it more regulations? What is the problem?

>> Imran Muna: One thing that I, think we have the answer to that has changed over the years. Now, AI is something people are much more familiar with and this type of technology is something being talked about a lot more often. But in the early years for InStage I feel like we were pioneering a lot of this technology. That's how we would describe it to ourselves is that we initially started this company as a virtual reality product. So we would actually go to organizations like Scotiabank and the Government of Canada and train employees by putting a headset on them and having them immerse themselves in a, sales meeting or things like that. We're very focused on higher education now. We don't work with those organizations as closely anymore. But now that people are familiar with this technology, we're not introducing it to them for the first time the way we have been in the past. So initially, I would say the main challenge for us was introducing people to a technology they've not heard of before or don't have a reference point for and trying to explain to them how this new idea could be helpful. That was challenging because they had never seen anything like it before. Many people had never seen virtual reality, had never experienced what it was like talking to an avatar or having a back and forth conversation. So we first had to overcome all that novelty before we could even get to ROI and what this could do and prove that it was stable and not something that was experimental. And thankfully, we were able to do that early on and build some of those early partnerships. And now I think the challenge for us is about raising awareness. We've spent a lot of time forging these relationships and building a strong product, but it's challenging to know how to share that message. And so we have started working again more closely with the organizations who have partnered with us to put together presentations based on the work they're doing. So instead of now attending conferences like where we met and talking purely about In Stage, what we're trying to do is share the work being done by our partner organizations and say, actually, this is what Northeastern is doing. This is how they're leveraging the technology. And we, of course, still have a part to play in the presentation, but I think sharing it from that perspective is giving new organizations a sense of what their peers are doing, which is very different than what could In up feeling like a sales pitch. So, we're again, just continuing to reinforce this idea that we need to highlight the work being done by our partners and the role we play in it. And that's giving us a way of raising awareness that I think is, is helping.

>> Dave: I, love where this is going because it really leads down the other pathway. And I think Gelareh and I experienced this in both our institutions. We have people that are very skeptic about AI. We have people like Gelareh and I that is just adapting it and saying, hey, look, we're going to do these great things. But I've got a presentation coming up, my institution, where I'm the AI expert, talking about the benefits of what we can do with it. But I've got three other people are going to talk about the negative elements about it. And I think the whole element of skepticism, and I want to know what In Stage is doing around this. because you. Not only do you have to think about skepticism around AI, but you're also thinking about credible coaching partners, like, and that element, how do we divide that? So how is In Stage dealing with that? How are they looking forward?

>> Imran Muna: That's one thing I think Michael is extremely good at doing on our team, is when we talk about AI and what In Stage can do and what the potential of this technology is as a whole, he does not only highlight the benefits, he speaks to the limitations of this technology. He talks about what it can do and what it can't do. And I think that's where you build trust. If you just hear that AI is going to solve all problems and it's amazing in every possible way, I think that reinforces and strengthens the skepticism because it sounds too good to be true and in some cases it is. It can't do everything. But I think talking about where its strengths are, this is something that can be done at scale. This is something that can be used on demand. This is something that can be customized and personalized. Those are the true sort of things we can talk about when we hear about things like, well, students need encouragement and students need people to get to know them and be there for them through something like a job search process, which is, you know, has tons of ups and downs and is challenging. Well, that's a role for a person. That, that's something that we need people to do. We need people to get to know their students and be there for them to provide that emotional support. So I think we're trying to find the balance between talking about the strengths of AI and remembering that people are nervous about what this technology means and recognizing some of those concerns and addressing them, not kind of hiding from them.


In Stage aims to embed AI into every major milestone in the student journey

>> Dave: Imran, what's next for InS tage?

>> Imran Muna: We have a vision for In Stage to be a part of every major milestone in the student journey. So our vision is that as students are thinking about applying to university, they might be having a conversation with an AI admissions counselor that is getting to know them. But the grand plan is that from that point they are having a conversation that will continue throughout the rest of their academic journey. So based on the things they say at the beginning of that initial conversation, our system is designed to remember the goals they set and the things they say. And one thing we didn't get to talk about too much in the presentation in Niagara Falls is there was a Northeastern student, for instance, that was interested in having a coffee chat with their employer after their co op experience. And this system remembers those types of things. So halfway through the semester it asked them, well, you know, have you booked that coffee chat? And they hadn't yet. They were a little nervous. They were still trying to figure out how to broach that subject. And so throughout the remaining check in calls that this system was doing it, brainstormed with them how to have that coffee chat. And they went on to book a meeting with that person they had worked for, I think spend about an hour talking about their future career goals and start building some opportunities that could come out after that. that's what we envision the system being able to do is go from admissions to those first exams where you might be thinking, this isn't for me, like, I don't know what went wrong. I'm not sure what happens next. Well, it's time to check back in and have a continued conversation and again raise a flag for faculty who might be able to say, hey, okay, we know you struggled in that last exam. Maybe you need this or that support. And then it continue to job seeking and hopefully beyond, you know, what happened? What happened after you graduated? Did you go on to get that 9-1-1 call taker job and really complete the student journey that way as a continuous, ongoing conversation?

>> Dave: Absolutely, Im! I love it. I love the conversation, my friend. I love what In Stage is doing with AI. Can't wait to hear what happens next. And we're going to be checking back in with you in a few months from now. But for our listeners out there, how can they learn more about In Stage? How can they explore how this is being used in education and workforce training? How can they reach out to you?

>> Imran Muna: Always happy to connect on LinkedIn. You can reach out to me there. Our website is InStage IO. We will be also in London, England later this year presenting at the QS Awards. So stay tuned to learn a little bit more about that. That's, the next time we'll be sharing some information about InStage but definitely through the website and on LinkedIn. You can find InStage on LinkedIn as well. We're always happy to answer questions and learn more about the work being done in this community.

>> Gelareh: Thank you, Imran. Thank you, Dave. That was another episode of Innovation Fuel.