Support for this podcast comes from Smart Recruiters. Smart Recruiters is your all-in-one platform, but faster, smarter hiring, making recruiting easy and effortless. Smart Recruiters are making some big changes, revamping their user experience, adding AI features and refreshing the UI. I know from experience that they truly are a company that really values the recruiter and the practitioner. They understand the intricacies of the recruiting business, and this has always been reflected in their functionality and customer support, so it's exciting to hear that they're making a bunch of updates. If you're ready to be part of the future of talent acquisition, head over to SmartRecruiters.com and find out what they're up to. Trust me, your team and your future hires will thank you. Hi there, welcome to Episode 642, a recruiting feature with me, Matt Alder. Most conversations about AI in talent acquisition focus on efficiencies and automating repetitive tasks. However, we really are missing the point. If we don't start talking about how AI could help reshape recruiting entirely, making it not just more efficient but also more effective. A why stop at recruiting? AI could revolutionise work and the whole way we think about careers. The current limitations of our thinking were really brought home to me when I attended the SmartRecruiters Hiring Success Conference last week in Amsterdam. An overarching theme was that automation is a given, and with AI, we should be thinking much bigger. So, what does this mean for TA strategies? And how can TA leaders ensure that they are proactively shaping the future direction of recruiting? My guess this week is Brian Solis. Head of Global Innovation at ServiceNow. He's also an internationally renowned digital anthropologist and award-winning author. Brian was the opening keynote at Hiring Success. And I caught up with him after he came off stage to get his thoughts on the current state of the AI revolution and the future of talent acquisition. Hi Brian and welcome to the podcast. Well, thank you. Thank you. I'm excited to be here in Amsterdam with you. Well, it's an absolute pleasure to have you on the show. For the few people who may not have heard of you or come across your work before, could you introduce yourself and tell us what you do? Yeah, absolutely. For the few billion people who have no idea who I am, my name is Brian Solis. I'm the head of Global Innovation at ServiceNow. I've been a longtime digital anthropologist, analyst, futurist, publishing research, books, articles, blogs on the future of business and markets based on the emergence of new technologies to try to make sense of what to do today and how to think about tomorrow differently. You've just literally just come off stage and I've kind of rushed you to this room to record the podcast. After doing a great presentation to a group of TA leaders really about the possibilities of AI and really trying to get people to think differently about what the future of recruiting would look like. So let's kind of start with talking a little bit about JNI. You played a really interesting clip from Sam Altman that kind of really sort of summarized the hype that when chat GPT-4 was released and then the disappointment that there wasn't this instant revolution and everyone hadn't lost their jobs. And I think if we got a look back 18 months, there were lots of commentators saying that there would be no more jobs at all within six months. And obviously that hasn't happened. So where is the Gen AI revolution? What's it for? The Gen AI revolution is, I won't say it's a quiet one, but it's in plain view for those who want to see it and it's also hidden for those who want to pretend it doesn't exist. I spend a lot of my time in every facet of every organization, not just a Gen AI, not with just a Gen AI revolution, but every technological revolution that has happened going back to the 90s. And I can tell you that what usually happens is that people will find every reason why they shouldn't have to believe or believe in something or to find the need to change. And so for example, with Gen AI, we could blame regulators. We could blame ethics. But what we cannot do is ignore how people are using artificial intelligence in their day-to-day life. And those are our candidates. Those are our employees. Those are our colleagues. And like every technological revolution, it is teaching people new behaviors. It is increasing or elevating their expectations. And it is also providing them with skill sets and capabilities that we don't understand because we are not them. And so where that revolution comes, you know, coming back to your question, where is that revolution? It's happening. It's just not happening in ways that we can follow along like an AI-driven transcript from a Zoom meeting. No, absolutely. And I think it was really interesting because you talk about how all of the technology revolutions that have happened over the last, particularly over the last 20 years have actually radically changed our behavior and our expectations of things in ways that we probably don't even realize or notice. I think you use the phrase accidental narcissists. Explain a bit more about that. Yeah, the accidental narcissist was born out of work I've done as a practicing digital anthropologist where I explore the impact of a new technology on behavior over time. So a simple one could be iTunes, Spotify, trained people how to have a different relationship with music. As someone who loves music and as someone who used to write music, it's different than the world that I knew. It doesn't mean that it's bad or wrong. It's just different. So I had to understand it. But if you look at things like Uber, or if you look at things like food delivery, or if you look at buy online pickup in store, every single one of those I've studied to show that people get increasingly more and more impatient and demanding with their services, causing each of those services to be faster, but introduce better algorithms. I'll give you an example. This is how crazy things get. In the United States, we have an app called DoorDash, and it's food delivery. One of the things that they had noticed is that as more and more people were ordering food, if it took longer than they thought it would take, they would bombard the customer service, bought or phone line, to say this is unacceptable, and DoorDash would have to offer discounts or complete refunds just to keep people using the service while they were in growth mode. And one of the things that they figured out was that if they put a little icon of a car on the map to show you where it is in its journey to you, they would eliminate a vast majority of people reaching out because subconsciously you understood it was on its way to you. The accidental narcissist is just used to having things better, faster, more personalized, and it's in that nature as someone uses, say for example, generative AI in their day-to-day life. Once they start to encounter different services or experiences or job postings, application processes that don't feel familiar, then it feels unfamiliar. And that starts to, over time, dictate whether or not your company is the right company for them. We'll come back to job seekers and candidates and an AI in a second. But before we do, how are you seeing companies respond to what's going on? How are organizations responding to JNI? I'll tell you, having been helping companies see suites and also startups and founders launch their companies, there has been a dichotomy of responses going back to internet 1.0. Not surprising. But I've seen a similar response from executives today with JNI. Sort of exploring, wait and see, maybe making excuses as to why things aren't ready or fully baked yet, or maybe limiting the technology's capability, for example, in the line of automation. Can we take out repetitive tasks? Can we increase productivity, scale, efficiency, take out costs, etc. But what's different with JNI is, I've never seen CEOs of large organizations lean in like they have with AI. One of the stats that I had shared was that CEOs and earnings calls in last year had mentioned JNI 40,000 times. And there's a remit from CEOs to go get that AI. Then you have the rest of the organization not ready to respond with that level of enthusiasm or excitement. And so it's sort of limiting its possibilities where you get headlines like in the Economist. Where's that AI revolution? Absolutely. And I think it's very true in our industry as well, because I think that most of the narrative and the conversation, the discussion around AI is about automation and efficiency, and will recruiters lose their jobs and all that kind of stuff. And as you say, at the same time, we've got candidates who are just experimenting and doing things that they've never done before in terms of applying. And there's sort of a big mismatch there, isn't there? But it's also a message of empowerment. And that is to the individual listening to this. If you think AI is going to take your job, then it will. If you think of your role as one of transactions, and you think of your role as steps of which could be replicated through AI, then that is your limitation. But if you think of AI, one of the things I introduced today was AI not standing for artificial intelligence, but instead augmented intelligence, where it becomes an extension of you and the value that you'd like to create for your organization and for job seekers and candidates, you have an entirely new opportunity to reimagine your role and the impact that you have in your organization. Thinking about that kind of that augmentation, I think you said the phrase of unlocking the real magic of AI, how should people think about that and just kind of position it in a way that allows them to look at the possibilities of what could happen in recruiting with AI? Yeah, it's such a hard question to answer because it's like, well, just ask different questions, just be curious, just use your imagination. But in reality, we're not trained to think like that the way that we used to say like when we were kids, where everything was possible, where we were all artists, where we would go outside and explore the world. And we were space journeyers, or we were policemen and police women, and where we got to explore the world through our imagination first. Today we've learned processes, we've learned systems, we've learned metrics, we're measured by certain things, and that becomes our box. That becomes the world in which we then think about AI. What does it mean for me in this capacity? And where we first have to start is by someone giving us safe space, usually a manager, usually a sea level executive, to say it's okay that we as an organization or we as a team don't have the answers, but let's go figure them out together. And let's go understand the unknown, let's go explore the unknown, let's experiment with what we don't know, we don't know, to then try to answer that question. And there's all kinds of ways frameworks and systems or creative journeys that you can undergo to open your mind, I call it a mind shift, where you just ask different questions, you use the systems, you use the technologies, you explore the experiment, and in the process of doing that, you actually become more and more versed in the very thing that you didn't know. We were kind of talking before I hit the record button about job seekers using AI and that kind of thing, and you shared a brilliant example in your presentation of someone in India who created a homework machine that uses JNI and actually writes with a pen to, you know, clones your handwriting and writes with a pen. And obviously the analogy there is about, you know, job seekers using JNI, JNI to cheat in recruitment processes, whether that's applying for thousands of jobs in one go or getting it to write the perfect cover letter and things like that. There's lots of soul searching and debate about how employers should respond to that. And you know, the first kind of knee jerk was like, we'll just get software that reads that out. How should employers respond to what's going on with job seekers in AI at the moment? One of the, one of the quotes that I shared in the presentation was that it's from an architect. When we, we spend a lot of time thinking about the design of the bridges, I can't remember it verbatim, but we think a lot about the design of the bridges and not so much about the people who use it. And I think that's where it starts. It's an empathetic approach to understand job seekers and how they use technology. And instead of labeling it, cheating, understanding why they do what they do, how they learn to do what they do, and also understand what matters to them, because it isn't just how they use AI to apply for jobs. It's probably how they use AI and other technologies in their day to day lives to make decisions, to accomplish tasks, because it isn't just about the job seeker. That job seeker might also become an employee or already be an employee or a colleague. And it's, it's applying that empathetic approach to actually see the world as they see the world. And then look at your processes, look at your systems, look at your touch points, your experiences, you're onboarding everything from that perspective, because every one of those is an immediate opportunity for improvement, where you're taking incremental and maybe even even innovative steps to make that experience better, which also makes you more competitive. So the the low hanging fruit, the quick wins are there through an empathetic lens. Absolutely. And I think you sort of talked about talked about quick wins and things like that. Well, it comes after quick wins, because I think what we're seeing, which is, which is fantastic, is there are a number of employers where the heads of TA or the people leaders in the HR team have given people that safe space, and there's some great sort of innovations coming from very often using publicly accessible versions of chat GPT and all that sort of stuff. And we're seeing use cases like writing job descriptions or researching talent intelligence in terms of looking at workforce data and and automating that. What comes after the quick wins? What the people who are already kind of doing that? Well, let's let's let's talk about that. Quick wins apply to, for example, taking out repetitive tasks, automation, in how you see the role today. Quick wins could also come through how you see the world through the eyes of a job seeker who uses all of this technology. So you have two two immediate opportunities with quick wins, right? The internal view and the external view. Most are using the internal view. So you have an immediate opportunity with quick wins from an external perspective for differentiation. The next wave is differentiated use cases. So what aren't people doing? Where can I create new value that doesn't exist today? How can I be more attractive to a candidate or a job seeker, for example, that has a different way of interacting through life? The next phase from there is transformational initiatives. What is it that we could do to reimagine our industry or our work or the meaning of our work? More existential or philosophical questions that a lot of people just aren't ready to have, but they're needed. And it's not just because of AI. It's just because these things are dated and and they feel that way. As someone said to me, not so long ago, in a lot of ways, recruiting has not changed in hundreds of years, let alone, let alone a few months. And I suppose that brings me to my next question, because you're actually doing some recruiting yourself at the moment. So you're kind of very much in the in the process. What do you think recruitment should look like in, I don't know, five years time? What what do you think could be could be possible? Where should people sort of be pointing pointing their energy and their and their visions? I have to be very careful with this answer, because I do appreciate, for example, the recruiters that I work with in our organization, they have been incredibly helpful in helping me find the right candidates and helping them come through the system with the best possible experience. And the thing that I think makes them so valuable is the human touch. My particular partner in this recruitment initiative is just one of the best people you could ever meet. And so when you have an opportunity to speak with her, it comes through. And I guess that's one thing that I want to say is that like in every aspect of our organization, let's take customer service, for example, we have used every technology that's come along, think the internet, think contact centers, think chatbots before JNI to get further and further away from the customer. And so we were using technology to become more systematic, more transactional, more self-service, because it was cost-effective. But no customer ever woke up and said, I hope I get to call a call center today, or I hope I get a chatbot to help me out today. And so I think the same is true for recruiting. Technology aside is that we have to explore ways to be more human, because at the end of the day, we're trying to bring people into a community, not just a company, of other people, where they want to be, where they're going to spend a significant amount of their time, their lives with us. So from there, then it is taking that empathetic lens we talked about earlier, thinking about people and relationships, and then asking the question, how can we use AI, Gen AI, what comes next to enhance those experiences, or to create the types of engagement opportunities that we've never had access to before, but keeping that people focus lens. That's how I would approach your question. And then analyze, once we start to philosophically understand what that could look like, it's then what is it today? What are the expectations of people? Where are their sources of joy? How are they using technologies to accomplish tasks and why? And then go through the journey and see exactly where we can get our quick wins, where we can get our differential use cases over time, create a roadmap, and then what could be transformational, like think big, dream big. It's a methodology that could be traced to things like human-centered design. But that's how I think about it. And I look at what can be improved, right? That's my iteration, and then where I can create new value, and that's my innovation. And so a final question for you, and you've touched on this many times in the conversation, but just I suppose by way of summary, for the TA leaders that are listening, for the people who want to be leaders in the future, anyone sort of thinking about what the future of time acquisition is going to look like. What's the one thing that they should do right now to kind of start that journey or to free up method process or whatever it is? What's the one thing? All right, let's do three things, and we'll come back to the second and third, but the first is to take a deep breath. Take a deep breath, and tell yourself this is going to be okay. And it's going to be okay because what you do next is actually going to define what the future of your industry looks like. There is no playbook for this, so everybody's scrambling to try to figure this out. And there's also certainly a lot of people covering their eyes and closing their ears. So understanding what is taking place can be as simple as going through YouTube or through TikTok with searches around how people are using AI. There's all kinds of fun hacks, there's all kind of fun use cases, and I explore those quite a bit to be inspired by the things that I couldn't think about, so almost like my own cheat code. But it's fun to go through that, and you'll find yourself first maybe saying that's ridiculous, but eventually you'll start laughing, and you'll start finding fun in it, and let yourself be touched by it and inspired by it. If you're a parent, let it inspire how you think about your children and how they partner with this type of technology to go throughout their scholastic career. Because if you think about education, that's also going to change quite a bit. So that part of just embracing the unknown is a really, really big step, and having fun with it is a really big step. Because in that, you'll start to see your work differently, you'll ask different questions, you maybe even start to play with systems. For example, I use two systems pretty consistently on a daily basis. One is chat, GPT, and the other is perplexity. And I use perplexity like a search engine, but I also use it as a research tool because it does footnote its findings so that I can then double click on the footnotes. That's the one place I'd start. The second place I would start is going back to what we talked about, which is look at the world through the lens of someone else, and allow it to inspire you to see your work differently. You can't unsee it once you do, if you truly let it in. And then the third thing is to just start ideating, whether it's with yourself, or whether it's inviting your team to do the same process, and just helping each other along this journey, but just get on the journey. Because we can find every reason, we can make every excuse why we shouldn't do any of this yet, and we'll just be that much further behind. Brian, thank you very much for joining me. Thank you, thank you, man. My thanks to Brian. You can follow this podcast on Apple Podcasts on Spotify or wherever you get your podcasts. 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. Bye. [Music]
