After all the commentary and debate about AI and talent acquisition over the last two years, we are finally starting to see what this brave new world might look like as many technology providers roll out new AI-driven products and services.
While it is clear that massive changes are coming to the way companies hire talent, there are still many unanswered questions and contradictory views on what the future will look like.
I wanted to get a different perspective on things, so this week, my guest is Shashank Saxena, a Managing Partner at Sierra Ventures. Sierra Ventures is an early-stage VC firm that has made several investments in AI-driven HR software companies. In our conversation, Shashank gives us some alternative visions of what the future of work might look like and implications for talent acquisition.
In the interview, we discuss:
• How is the world of work changing
• AI use cases and the speed of adoption
• Does AI make TA more efficient, or does it completely disrupt it?
• Are AI-powered job seekers cheating?
• Can AI make hiring decisions?
• The implications of AI agents on white collar work
• What does the future of HR and Recruiting Technology look like?
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Matt Alder [00:00:00]:
Support for this podcast is provided by Popp AI. Popp AI brings next generation conversational AI to RPOs in house talent teams and recruitment marketplaces, making every candidate interaction faster, more human and more efficient. From automated screening and voice note transcription with support for 40 plus languages, the AI powered platform engages top talent through natural multichannel conversations. Popp AI transforms early stage hiring, capturing insights, collecting documents and seamlessly scheduling interviews so you can focus on building stronger connections with the best candidates. Visit joinpopp.com, which is J-O-I-N-P-O-P-P.com to discover how Popp AI is redefining recruitment automation for the modern workforce.
Matt Alder [00:01:13]:
Hi there, welcome to episode 657 of Recruiting Future with me, Matt Alder. After all the commentary and debate about AI and talent acquisition over the last two years, we’re finally starting to see what this brave new world might look like as many technology providers roll out new AI driven services. While it’s clear that massive changes are coming to the way that companies hire talent, there are still many unanswered questions and contradictory views on what the future will look like. I wanted to get a different perspective on things, so this week my guest is Shashank Saxena, a Managing Partner at Sierra Ventures. Sierra Ventures is an early stage VC firm that has made several investments in AI driven HR software companies. In our conversation, Shashank gives us some alternative visions of what the future of work might look like and the implications for talent acquisition.
Matt Alder [00:02:13]:
Hi Shashank and welcome to the podcast.
Shashank Saxena [00:02:16]:
Thank you Matt. Thanks for having me. I’m excited to be here.
Matt Alder [00:02:19]:
A pleasure to have you on the show. Please could you introduce yourself and tell everyone what you do?
Shashank Saxena [00:02:24]:
Yeah. So my name is Shashank Saxena. I’m a Managing Partner at Sierra Ventures. I joined Sierra Ventures April of this year. Prior to this I was the founder of a company called Venly. Wendley was acquired by Workday in 2021 and what Venly did was we thought of ourselves as the Workday hcm, as in the system of record to manage all your non employees, consultants, contractors, your contingent workforce. So I was the founder and CEO of that company and I started the company in 2017. The company was acquired by Workday in 2021. I was at Workday for the past two and a half years and I joined Sierra Ven this year. April.
Matt Alder [00:03:05]:
Fantastic stuff. So obviously it’s a pretty Dramatic time in terms of HR and recruiting tech at the moment with AI and everything else that’s, that’s going on. What are you seeing in terms of AI in this sector at the moment? You know, interesting use cases. How, how’s adoption compared to sort of other. Other areas?
Shashank Saxena [00:03:28]:
Yeah. So when you look at the HR life cycle, the simplest way to think about the HR LifeC is in four different buckets. Source, which is how do you go out and source candidates Engage, which is how do you engage candidates in the interview process and the recruiting process and all the way up to the job offer letter. Manage, which is once you’ve onboarded them on the assignment and now you’re doing the ongoing management, which is performance reviews, appraisals, things like that, comp planning. And then the last one is pay, which is the payrolling aspects of payment and management. Right. So source, engage, manage, pay. And we’re seeing some really interesting HR trends in each of the four buckets. Right. So in the source bucket we’ve seen everything, right. From AI based recruiters and automated recruiting. In terms of the engagement bucket, we’ve seen candidate CRM systems and other systems of engagement that are there trying to engage candidates using AI bots. The Manage piece that’s going through with AI agentic workflows. Last month at Workday Rising, Workday itself announced a bunch of AI agents. I know ServiceNow has AI agents in the space. Salesforce did a joint announcement with Workday at Dreamforce for their AI agents, which is. All of that is focused on the Manage bucket, which is how do you manage the life cycle in terms of critical tasks that need to be done when people are at the company and on assignment? And then the pay is, I would say where we are still seeing some AI, but it’s not as prominent as the other three buckets because payrolling, a lot of it is already rules engine driven. Right. Your tax withholding structures, your other payrolling aspects. So yes, there is some AI in terms of anomaly detection and figuring out and catching issues before they exist. But at the same time it’s not as transformative or at least we’ve not seen as many transformative companies in that fourth bucket as we’ve seen in the first three.
Matt Alder [00:05:30]:
I suppose to take a step back and look at the bigger picture around this, I mean, how do you think AI is going to change the world of work kind of more generally? What are the implications of it?
Shashank Saxena [00:05:42]:
Yeah, so when you think about the world of work, a lot of tasks that outsourced and offshored or even, for example, things like call centers and BPOs, a lot of them entry level people that have been given a certain playbook and a certain script to go follow on how to go ahead and handle situations. Right. So those tasks are pretty ripe for AI disruption because now you can go ahead and train AI using a rules engine and prior handling mechanisms in terms of how to handle future instances or when the similar issue arises in the future. So I would say when you think of the world of work, a lot of things that are either outsourced, offshored or bpo, the bucket of bpo. And in that bucket, those, I would say, are the ripest for disruption.
Matt Alder [00:06:38]:
No, absolutely. And I suppose to just to drill down a little bit here into talent acquisition specifically, how do you think talent acquisition is going to change and what are the impacts for people who are currently working in talent acquisition?
Shashank Saxena [00:06:52]:
So there are a couple of different themes on this one. The first one is to make the recruiter or make the talent acquisition folks more efficient. That’s one theme that we see. And the other one is a little contradictory, which is disrupt the talent acquisition professional. And we’ve seen companies in both of those buckets. So the first one is think of it more as a copilot, which is how do you automate tasks? How do you automate the email reach out and the engagement back and forth and then the interview scheduling and all of that stuff using AI agents. Right, which is you’re making the recruiter more efficient. The other one is more around a disruptive theme around why does the workflow have to be the same way that it has been since the early days of the Internet? Why not rethink the entire workflow and manage it completely differently? So we’ve seen both. We don’t know where exactly things will end up, but the interesting dynamic on that, Matt, is companies that we are seeing that on the other side, which is helping the candidate work with talent acquisition professionals on the candidate side. I would use this in air quotes, but cheat the system. So we’ve seen companies that basically have bots that can join calls and answer interview questions and help you with a teleprompter where you can go ahead and read the responses out loud so you’re not thinking the responses, you’re not coming up with your own responses. When AI is helping the recruiter ask you the right questions, there’s AI on the candidate side helping the recruiter answer those questions. So at that point it’s AI on both sides. So what the hell are humans doing? Right? Like they’re just reading out scripts on both sides. So we’re seeing some really interesting dynamics there too where AI is trying to make things more efficient and authenticate and genuine. When AI is used on the other side too, then it’s like AI versus AI at that point.
Matt Alder [00:08:55]:
No, absolutely. And do you think that that kind of, that aspect, that kind of third thing that the candidates sort of using, using AI is do you think that’s going to kind of set the tone for, for where we go in terms of forcing employers to disrupt how they think about talent acquisition? Because, you know, as you say, you just have kind of AI talking to AI and you know, it just seems that the, the way that we, we currently go, the way that we’ve traditionally done acquisition is kind of a bit unten circumstances.
Shashank Saxena [00:09:25]:
Yeah. And you know, there’s a lot of this is also perspective and it’s generational perspective. So when we see such companies, Right. It’s interesting around our office. So people who have been around the block and are very experienced and are mid to late career professionals, the point of view is, oh, that’s cheating. Like why would you ever use that? And how is anyone going to think that that’s ethical? And then there is some of the more entry level folks or the early career professionals, when we ask them that question, they’re like, what do you mean? That’s unethical. It is perfectly fine. How is this different than a software developer using an AI copilot to write code? Right. And what AI is doing is helping me highlight experiences that I’ve already lived through, things that I already know. So the fact that they’re helping me better articulate it, how is that cheating? Because I’m still going ahead and responding and proving a better version of myself. So why is that considered cheating then? So there are contradictory points of view and it’s very generational in terms of what point of view. Hold on that one as well. So it’ll be very interesting to see how this space plays out given that this is not just about the functionality or the use case, it’s also about the perception as to what is and what is not acceptable and where that boundary gets drawn.
Matt Alder [00:10:42]:
Yeah. And I think that’s interesting because you have employers who consider that unfair or cheating or whatever, but they’re using AI to generate job adverts and job descriptions. They’re using AI in the flow of their work already. So it does seem kind of strange from, from that perspective, I guess.
Shashank Saxena [00:10:59]:
Yeah, exactly. So that’s the point, right? So if AI Used on one side, why can’t it be used on the other? So if it’s not considered cheating on the recruiter and TA side, why is it considered cheating on the candidate side?
Matt Alder [00:11:14]:
One of the big discussion points has been around using AI in the hiring process. What’s its role in actually making choices about selecting people? And obviously there is legislation around the world in place or incoming that kind of might complicate that. So what are the challenges for people when it comes to AI in the hiring process and what are the benefits if they manage to get it right?
Shashank Saxena [00:11:40]:
That’s a little bit of a tricky question, right? Because when you think about hiring process, the broader question that we are seeing when we talk to our CXOs at these different companies, the broader question that they are asking is should I actually be hiring a human or should I be setting up an AI agent for this task? And that is true for software development jobs, that’s true for data engineering jobs, that’s true for call center jobs, that’s true for support jobs and customer support type jobs. And that’s where the perspective around hiring is no longer just assumed. Because before this it was always hiring means you’re bringing in humans. And the only debate was should I add full time employee headcount or should I outsource this work or should I bring in consultants or contractors to do it? Like that was always a debate. And now the question is even broader around can I set up an AI agent to do this? Is this a work fit for a human or it’s better done by an AI agent? So that whole question is now the entry point in terms of getting work done?
Matt Alder [00:12:39]:
No. Absolutely. And what about the impact of legislation around this kind of thing?
Shashank Saxena [00:12:43]:
I don’t comment on legislation too much. Right. Because depending on where the political beliefs are and people are all over the space, and it tends to become more political rather than so legislative, without political opinions becomes hard to decouple. But when you think about the world of work, most people have this belief, or at least on media you’ll see the popular belief that AI is going to disrupt humans and humans are just going to be sitting around doing nothing because AI is going to do a lot of the work. And the counter argument to that and this will play a role in legislation and how legislators think about it is look at the world population, most of the western world or the developed world, right? Most of these populations are in decline. Look at most of the European economies, look at Japan, look at us, look at Germany, look at any of these countries. The birth rate is in decline. There just aren’t enough humans to do work. So is it going to, are we going to end up in the future where there are humans and no work, or is it just are we headed towards a future where there just aren’t enough humans to begin with so we don’t have to worry about what do the humans do because we just aren’t producing enough of humans? Right. So that point has to be factored in, which I think will be factored into regulation and legislative thinking. But at the same time, of course, as you know, these things tend to get very political. So it will be interesting to see how this comes up. Where do they start to have laws around taxation and things like that, around AI doing work?
Matt Alder [00:14:18]:
Interesting. No, that’s a very interesting point. And obviously it’s been the last sort of couple of years has been a bit of a whirlwind when it’s come to AI and the progress with the technology. What’s the thing that surprised you most in terms of what’s happened over the last sort of 24 months or so?
Shashank Saxena [00:14:36]:
The maturity of what AI agents can do in terms of white collar work. So traditionally the mindset always was, oh, robotics will take on blue collar work and it’s going to automate the manufacturing and things like that. Until a few years ago, just the thought of AI taking on things like data engineering and software development was hard to believe simply because of all the nuances that go into that. And now with the recent breakthroughs, that’s not just feasible, it’s not just a far fetched thought in the future, it’s happening today and now. Right. So same thing in terms of customer support, for example, when you think about customer support, a lot of this was about people think of it as the old stodgy bots that basically, if you type two words incorrectly, they’re clueless and they can barely answer your question. And the frustrating experience of dealing with bots that we all have, you might as well just go talk to a human directly. Right? Because the bot is never going to get there. Now, if you look at the recent breakthroughs, they’re actually pretty damn good. So. And if they don’t understand, they understand the fact that they don’t understand and then try to redirect you automatically. So that is also keeping in mind the context that you’ve asked a question two different ways and the AI agent did not understand it and now is trying to go ahead and help you and support you and redirect you in other ways. Because it understood the fact that it’s not being helpful to you, of course.
Matt Alder [00:16:07]:
So as a final question, what do you think the future looks like? What’s the world of HR technology going to look like in 5 years time? What do you hope is going to happen?
Shashank Saxena [00:16:17]:
It’s very interesting because every time there is a major tech breakthrough and you can think of this from the early days of the Internet, we’ve always thought of disruptive technologies that by the nature of the term disruptive, they’re meant to disintermediate someone, right? So if you think of the early job boards, monster.com for example, from the late 90s, right, the goal was monster.com was going to disrupt recruiters and staffing companies. Well, guess where Monster got most of his revenue from? Recruiters and staffing companies, right? Similarly, LinkedIn, when it came about as a second waiver in terms of recruiting solutions, LinkedIn was supposed to disrupt recruiters and staffing companies. Because now everyone’s available on LinkedIn and I can go in and just do a search query and find who the right person is and why do I need staffing companies and why do I need recruiters? Well, guess where LinkedIn gets most of its revenue from? Staffing company and recruiters, right? Similar examples can be made in other categories too. So be it. Zillow and Realtors, right? So on Zillow, if you can see homes, why do I need a Realtor? Well, guess where Zillow gets all this revenue from? Realtors, right? And similarly for brokerage platforms with E Trade and whatever the other trading platforms are, they’re going to disrupt the broker. Well, what really happens in most of these scenarios is take financial services as an example. You stop calling your broker to you not pick up the phone to say, hey, buy me 500 shares of whatever stock, name the stock, right? Of Tesla stock. And that was just a tactical task that you were doing with your broker or your financial manager. And now because you can do that on the real time trading platform, you can execute the order. Now, what you’re spending time with your financial agent discussing is what you should buy, how you should do asset allocation. So the point being, the tactical part always gets automated and humans end up doing the most strategic thought leadership thing. So similarly in HR tech, when I think about this and how this will play out in the next few years, will AI automate a bunch of stuff? Absolutely. Will there be efficiencies provided in the mix? Absolutely. Does that mean that humans will have nothing to do? Absolutely not. Because what humans will do is move to the more thought provoking things around. What should my talent bench look like, where should I use AI, what tasks to outsource, what to offshore, what to automate and what do I need to bring in humans for and what the skill sets needs to be so it becomes a more intellectual role rather than just a tactical executionary role. And that’s where I think the market’s headed with AI, assuming AI continues to live up to its promise.
Matt Alder [00:19:01]:
Shashank, thank you very much for talking to me.
Shashank Saxena [00:19:04]:
Thank you Matt. Thanks for having me.
Matt Alder [00:19:06]:
My thanks to Shashank. You can follow this podcast on Apple Podcasts on Spotify or via your podcasting app of choice. You can search all the past episodes at recruitingfuture.com on that site. You can also subscribe to our weekly newsletter Recruiting Future Feast and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.
