0:00:05: Welcome to The HR Tech Spotlight podcast. I’m Deanna Shimota, CEO of GrowthMode Marketing. The HR technology market is crowded and we know it can be hard to find the best software solutions for your business in the sea of sameness. On this podcast, we shine a spotlight on some of the best up and coming technology options out there. Check it out if you are interested in learning about new innovative solutions available in the market.
0:00:33: And if you are with an HR tech company and interested in being considered for a guest spot, stay tuned for details at the end of the show.
0:00:45: Hi everyone. We’re back with another episode of The HR Tech Spotlight, and this time we are looking at Humanly, a conversational AI platform for high volume professional hiring. The platform’s AI Copilot handles scheduling notetaking and follow up to support the hiring process. Joining me to talk about this technology is Prem Kumar, co founder and CEO of the company. Welcome to the show, Prem.
0:01:10: Thanks for having me, Daniel.
0:01:13: So tell us a little bit about your background in HR Tech. I always like to start with this question because I think it’s fascinating to learn how people get into this space.
0:01:22: Yeah, so my background, I kind of started my story when I was graduating from the University of Washington here in Seattle, and I was a job candidate entering the high volume space and saw a lot of inefficiencies in how candidates are engaged with how they’re processed. But when I started my career so I started at Microsoft and I really saw that some of the inefficiencies and bias around processing large volumes of candidates weren’t having to do with recruiters or hiring teams, just being bad at what they do or anything like that. It was more just having the tools and technology to engage at scale. So I was at Microsoft for about ten years, and half of those I was the PM for our global HR portal. So any new technology, whether it was ta technology or employee engagement technology, would go through my team. So I had a purview around how we build HR tech for our global employee base. But then later in my career, I started working on how as we acquired LinkedIn and evolved what Microsoft was doing, how we actually then sell it to external folks.
0:02:37: But really that’s where I started. And then I went to Tiny Pulse, a startup focused on employee engagement. So I stayed within the HR tech realm. My experience is kind of on the crossroads of people, data and product management.
0:02:55: Awesome. So let’s dig into humanly. Tell us in your words what the company does.
0:03:02: Yeah, so we help high volume hiring teams screen schedule and do remote interviewing more efficiently, more equitably. We’re generally focused on professional high volumes, so insurance, banking, accounting, and we also address the deskless worker space. But really what our technology does is we will automate initial screening through chat. And then our assistant will join virtual interviews, like a zoom interview. So taking notes for you, writing follow up emails, but really we want to help save you time in the kind of top or middle of the funnel for these high volume hiring scenarios.
0:03:46: So you are a co founder of the company. Tell us a little bit about the story behind founding the company and what are the problems that you saw in the market that made you think, this is something we need to go out and create to help organizations?
0:04:04: Yeah, so I’ll dive a little more into kind of the initial part of my story. So when I was applying for jobs as a candidate, as a high volume candidate out of college quite a while back now, but it was interesting, I would apply to these jobs and never hear back. And there just seemed like there was a missing element there. I wanted a little more. And then when I would get interviews, I would oftentimes compare notes with my colleague.
0:04:36: We would have companies coming on campus to interview myself and other folks that were in my major. And my colleague and I had the exact same experience, same major, same internship. And when we compared notes, we were asked completely different questions. They were kind of grilling her on her tech skills. They were grilling me on my communication skills with much different topics. And it became clear whether it was due to bias or not having enough time, that first we weren’t hearing back. And then when we did get interviews, they were non standardized at all. So I felt that pain early.
0:05:13: And then as I kind of grew into my career and did more research and learned about some of the problems and starting Humanly, we found that, generally speaking, most recruiters and recruiting coordinators at high volume hiring companies just don’t have the time to engage at scale. About $6.6 billion is spent in the US. On high volume hiring jobs, doing very manual things such as going through stacks of resumes and having screening calls, which are oftentimes very repetitive. So what we want to do is automate the more manual so you can spend human time on what’s more meaningful in terms of those conversations.
0:06:01: So really, at the end of the day, we want to give humans more time to have engaging conversations with job candidates.
0:06:10: AI has become very popular in the HR space, and I know that there’s a lot of questions around ethics with that. Let’s talk about your perspective with ethics and AI.
0:06:25: Yeah, no, absolutely. I mean, I’ll start by saying hopefully the obvious, but AI is not going to replace humans in the recruiting process, but recruiters that use AI may replace those who don’t. It’s kind of interesting as I think back to my time at Microsoft when cloud computing hit, it’s the last kind of time that I’ve seen a technology that has so much potential. So about according to a tidyo study, about 83% of companies right now are looking at AI as a high priority, but so much potential yet such a lack of trust.
0:07:06: In that same study, it said 28% of people actually trust AI. So since cloud computing, I haven’t seen an enterprise technology hit the forefront that people want to use and adopt at such a prevalent rate, but yet do not trust yet. So it’s really interesting. And when I see RFPs, when I see buyers coming to us, I’m trying to educate them to ask more questions. We have a lot of framework around how you can really ask the right questions to vendors. But I would say from an ethical standpoint until fairly recently and it’s still not effectuated yet. But the laws and standardization has not caught up. So it’s really incumbent upon vendors to do the right things as well as buyers to ask the right questions.
0:07:57: And at the end of the day, you have to be thinking just like you think about accessibility and technology, data security, you go through Sock Two and ISO. I think that same level of scrutinization needs to be applied to vendors you’re considering. So to me, any change management starts with trust. And until vendors can prove that they are able to be ethical and responsible in the data they’re using to train their AI models, the practices they have, who they’re hiring, there’s level of work left to do. So really one of our jobs as a vendor is to be at the forefront of how we think about that and happy to talk more about that, but those are some of the initial thoughts that come up.
0:08:45: When I think with AI in the industry, it’s not a new thing, right? There have been companies in HR Tech using AI for years. Humanly obviously has been around for a few years already. You were built on the premise of AI, so there’s lots of great applications for it. I think where HR tech buyers maybe hesitate on it at times is all of a sudden it feels like there’s a proliferation of AI options out on the market. Right. And they’re not sure which ones are well established and built out and which ones are an insert into an existing product. And I think there’s a lot of things to figure out in the market as companies continue to navigate that.
0:09:30: But I don’t think there’s any question that the future means AI is going to be involved because quite frankly, there’s not enough people in the workforce and there’s not going to be more people coming into the workforce to fill those gaps today. So we’ve got to find ways to work more efficiently as HR organizations and as businesses in general.
0:09:55: Yeah, no 100% agree with that. And one quick thing I’ll add there when we talk to our buyers and if we’re asking AI to take on some manual tasks that are done by humans. One thing I often ask our buyers is to interview your AI in a similar way that you might be interviewing a human. So write a job description for it. Think about the experience and training you want it to have. So what training data does it have?
0:10:24: Is your AI a culture ad to your organization or is it detracting from your culture? What are its credentials? What’s its background? What’s its pay? Are you going to increase its comp if it performs more tasks? I think a lot of this starts with asking the right questions. And if you kind of really think about it as a thing that is going to be directly talking to your candidates like a human might, is it really hitting on those things that you expect from your culture, from its background and whatnot?
0:10:57: I think that’s great advice to kind of treat it like an employee and look at it from that perspective to be able to figure out where it fits within your organization. What is your company’s unique point of view in the market as buyers go out and they’re looking at the options and how they can streamline processes within recruiting and other areas of the business, there are obviously lots of different options out there.
0:11:26: What makes Humanly different from other options?
0:11:31: Yeah, I think that the big space that we want to eventually be kind of market leader in and we’re starting to get there. But anytime you’re having a two way conversation with a job candidate and a chat bot could be one way, SMS could be another, humans could be another channel. So anytime there’s a two way conversation with a job candidate, we want to make that more efficient and more equitable. So we don’t want you to have to figure out, okay, maybe we use a chat bot for initial screening and then we’re buying another solution trained on another set of data to do SMS and then we’re using another tool to help us interview better. So anytime there’s a two way conversation with job candidates, regardless of the channel, we want humanly to be there helping you make those more efficient. So I think part of it is being multi channel and the other is playing very nice with ATSs and CRMs.
0:12:28: We are not building our own applicant tracking system. For instance. We want you to continue to work out of workday success factors toleo greenhouse lever that should be where you live. You’ve already invested in those tools. How can we be on the outside talking to candidates, putting data back in, engaging, putting it back in? So I think the other value prop for us is we’re more of a tool consolidation play we want to be than adding more tools to a tech stack that is already too busy.
0:13:04: What are the different use cases for Humanly?
0:13:08: Yeah, so really I’ll start with what is not a use case. So we’re not sourcing. So we’ll generally come after or helping you attract candidates. We’re not doing that. So generally we’ll come in in high volume scenarios where you have a lot of attention from candidates coming to your website or coming to your career fairs or to your social media. So our initial use case is applicant intake and screening. So we’ll take that big list of people coming in and maybe even through job boards like Indeed.
0:13:41: And we’ll make that list smaller through a two way conversation with our chat bot. So you might have I’ll give an example. One of our customers, Moss Adams here in Seattle during university hiring season they’ll have 4000 candidates that apply and it’s often hard to have the human time to engage at scale with 4000 candidates in a short period. Our chat will talk to everyone within 24 hours, answer their questions, screen them automatically.
0:14:11: So make that big list smaller, put it into your ATS. So you now have a shorter list that you can engage with. And candidates that might not be a good fit. Now maybe they don’t have their CPA yet, or we will put them in another list so you can engage with them. So the initial intake and making the big list smaller is the first use case, and the second use case is sitting in your zoom or Teams or Google Meet interview to take notes, put it in ATS, write follow up emails, and even give you data showing that. Hey, if you bring up remote work at the beginning of the meeting or spend less time at the beginning of the meeting on small talk, you might have a stronger chance of converting the candidate. So it starts by automating top of funnel and the remote interview and then giving you some insights to be more efficient.
0:15:03: What is the profile of a company that would be the ideal fit for humanly?
0:15:08: Yeah, so generally speaking, there’s kind of two core groups we’re going after. One is professional, high volume. So this is an insurance company, a bank, an accounting firm. The other is deskless workers. So quick serve restaurants, hospitality within that volume is one thing we look at. So are you getting over 100 and 5200 applicants for your open position? And if you are, we feel we can help you be more efficient in engaging with them.
0:15:39: So, high volume, certainly looking for companies that care a lot about ethics and AI responsible AI diversity, equity, inclusion and belonging. There’s a lot of threads there digital transformation and moving to kind of a new way of doing things. The other thing we look for is companies that are not looking to completely upend their existing process. So I’ll make this part brief, but I feel AI, like any other technology, can make things happen faster, more efficiently and at a higher quality.
0:16:13: But if you have a process that isn’t sound, it can also make bad things happen faster, more efficiently, and at a higher quality of bad. So we look for companies that have a pretty decent process in place from a ta standpoint. And we’re not there to replace your process, we’re there to make a sound process at a much faster rate.
0:16:36: So what type of impact have you seen organizations that are working with Humanly experience?
0:16:42: Yes, two categories. One is time savings, and I can share some data there. And then the second is candidate experience, which is very important to us on the candidate experience side. So from an impact standpoint, so generally speaking, we’re saving you a bunch of time. And we have different ways of quantifying that based on industry. But generally about fifty K per every 15 roles you have is what we’re looking at from a time saving standpoint. And that specifically is based on time savings in screening, in scheduling, and then in those remote interviews. So a lot of our recruiters have seven calls a day. So imagine ending your day where all the calls now, the notes are already in the ATS. The follow up emails are in your draft folder and you can review them and send them. So really, the time savings there and then candidate experience is just so big in all companies.
0:17:42: With some of our B to C customers, candidates are customers. Your employer brand is your brand. And with companies like Virgin Media, not a customer of ours, but they’ve done some research saying they lose $6 million a year because candidates that have a bad experience will actually go to a competitor. So candidate experience is a very hard cost savings. So generally, our average rating of our chat experience is about 4.7 out of five. And candidates feel in this very branded experience, they can not just be screened by the bot, but screen the company as well so they can ask questions to make sure this is the right fit for them. So when they get to a human, you’re not working with someone that hasn’t already filtered your company.
0:18:31: So I think that two way conversation early can really help with candidate experience. So we measure that via actually asking candidates how they would rate their experience. And the last thing I’ll say is candidates that didn’t get the job will rate the experience about a 4.5 out of five. So they’re happy they got in and out pretty quickly, even if they didn’t end up getting the job.
0:18:55: Well. So what is your future vision for humanly?
0:18:59: Yeah, I think at the end of the day, anytime you’re having a two way conversation with a job candidate, whether in the future that is through Alexa or some VR technology, right now it’s through SMS, it’s through humans, it’s through email, it’s through chat bots. But whenever there’s a two way conversation in real time, we want to be in all of those conversations. For all the high volume companies in the US. And beyond, and as we grow, we’re becoming more of this kind of hub to be able to engage with candidates in those conversations.
0:19:39: And that’s the space we want to stay in. And we’re starting with high volume. I could see us branching into a little bit horizontally. So right now we do with some of our customers will provide onboarding engagement and we could potentially see ourselves going a little bit down the people lifecycle. But very much right now, it’s kind of winning this conversational space in pre hire and starting after Sourcing and before day one.
0:20:11: For those that are out there currently evaluating a solution like Humanly, what would you suggest they take into consideration as they evaluate their options?
0:20:23: Yeah, so I’ll kind of go back to one of the things with NEI is there’s obviously, particularly at the enterprise and mid market as well, there’s big change management that needs to take place. And I think change management starts with trust. So making sure that you’re asking the right questions to trust the vendor, trust their process, trust their data. So if I go back to the example of treating it like you’re hiring a human, I would encourage you asking questions around the AI’s experience and training. So what data is AI trained on around the AI’s background?
0:20:59: So what use cases has it worked on before? Responsibilities. So how does it kind of fit into the puzzle right now? Skills references that it might have, so other companies that it’s worked for. So I would definitely ask a lot of questions. I think the biggest one is around the data. So the currency of AI is data and that’s what powers it. So how is it being trained? Is your data as a company going to be used by the vendor for other companies?
0:21:31: Are they using platforms like OpenAI that might be trained on the Internet? And the Internet is a very biased data source. So how is it being trained? I think is one of the biggest things. And yeah, I’d also kind of think a little bit about the future because this is evolving very quickly. So where is the vendor? How are things changing in the next five months, one year for the vendor? And what audits are in place?
0:22:00: We’re going through an audit with a third party called Fair now, right now. And I think it’s important to make sure that there’s also a kind of particularly if you’re going to work with an earlier stage vendor, are they being audited by a third party? So those are some of the things I’d consider and there’s just a lot of promises right now. So I think really cutting through the noise has to do with us as buyers asking the right questions to our vendors.
0:22:31: I think that’s some really great advice. Thank you for sharing those thoughts. What final thoughts do you want to leave our audience with?
0:22:40: Yeah, I think we’re in a fairly early stage right now in terms of obviously AI has been around for a very long time, but in terms of using it to directly engage with our customers or our job candidates or our employees, we’re fairly early. So I think my final thought would definitely be looking at the different resources out there. I’m happy to actually have a few written down here which I can share, which have no affiliation with Humanly. But some of the things that I just read, there’s definitely quite a few.
0:23:22: So Data and Society is a nonprofit research organization. The AI Now Institute partnership on AI is another one. Data and trust alliance. Those are some of what I’m seeing out there, some resources that can be useful, that are non affiliated with vendors like us.
0:23:44: Awesome. So my last question for you. Where can our listeners go to learn more about Humanly?
0:23:51: Yeah. So you can go to our website, humanly IO. Check out my LinkedIn. My name is Prem Kumar. Obviously you have that, so check me out on LinkedIn. My Twitter is at Prem Kumar tweets but would be happy to connect on LinkedIn. I do a lot of kind of one on ones with folks that whether they’re interested in Humanly or not, I do a lot of kind of one on ones that talk about the landscape and whatnot. So shoot me a LinkedIn message and my email is prem at humanly IO.
0:24:22: Prem, it was a pleasure to have you on as a guest today. Thanks for joining me to chat about Humanly.
0:24:28: Thanks, Deanna.
0:24:30: I’ll drop the links in the show notes so listeners can learn more and tune in again next time.
0:24:40: Thanks for listening to this episode of The HR Tech Spotlight podcast, where we showcase some of the best up and coming HR technology options in the market. If you are an HR tech company leader who would like to be considered for a guest spot on this program, please contact me via grossmodemarketing.com or reach out to me, Deanna Shimota on LinkedIn. And if you found this show informative subscribe, connect with us on social media and leave a review.
0:25:10: This is Deanna with GrowthMode Marketing signing off. Thanks for listening. We hope you’ll tune in again next time.