[Podcast] Industry Spotlight | Maurice Fuller – President at StaffingTec – AI Trends Shaping the Future of the Talent Industry

Maurice Fuller [00:00:00]:
So today we believe that the new gold standard for automations within a staffing firm is 100. We believe that staffing firms should get to 100 automations to help automate many different facets of their staffing operations. And many firms that have put their minds to it and have dedicated the resources have quickly been building up their automations to 100 and well beyond that. So we have staffing firms now that are running hundreds and hundreds of automations, and they’re seeing real significant productivity gains as a result of that.

Kortney Harmon [00:00:33]:
Hi, I’m Courtney Harmon, director of industry relations at Crelate. Over the past decade, I’ve trained thousands of frontline recruiters and I’ve worked with hundreds of business owners and executives to help their firms and agencies grow. This is the full desk experience accrilate original podcast where we will be talking about growth blockers across your people, processes, and technologies. Welcome to another episode of the full desk experience.

Kortney Harmon [00:01:09]:
Welcome back to another episode of the full desk experience. Industry spotlights it’s an absolute pleasure to have Maurice Fuller grace our presence once again. Last year he really joined us and enlightened us with his expertise and insights into tech trends that define 2023. This time around, we’re in for an even more captivating discussion as we delve into the ever evolving world of technology and AI and its profound impact on shaping the future of our industry. Maurice is a true staffing industry veteran with a visionary mind behind staffing tech, a consulting firm dedicated to helping businesses harness the power of cutting edge solutions. He’s a wealth of information and he brings unparalleled perspective to the table. So today, I’m thrilled to have Maurice share his insights into the realm of artificial intelligence and its implications on our industry. As a pioneer in this field, he’s perfectly positioned to guide us through the intricacies and opportunities that AI presents.

Kortney Harmon [00:02:06]:
So, Maurice, I can’t thank you enough for joining us. Once again, your expertise is invaluable and I’m so eager to dive into this conversation. So thanks for joining us again.

Maurice Fuller [00:02:15]:
Courtney, thank you so much for having me.

Kortney Harmon [00:02:17]:
I appreciate it. So before we dive in, I know you usually do tech trends, and we’re going to be talking about the AI, the details of AI. But before we dive in, let’s start talking about generative AI before we dive into those top ten topics and the general impact on the staffing and recruiting industry, as well as the world around us.

Maurice Fuller [00:02:38]:
Yeah, we did a top ten trends report a while back, and since then, everything has changed with the introduction of generative AI and it’s such a massive and important technology, and I want to share some thoughts about that with your audience and specifically this idea that this time is different with AI. Also that we’re just on the cusp of a new industrial revolution. Talk a little bit about the massive demand that we’re seeing for AI chips, the rate at which generative AI is improving at a double exponential rate. And then also this last thought, that AI is going to be the greatest wealth creation opportunity in history going forward. So starting with that first point about this time is different. I work with a lot of staffing firm owners who’ve been through a tremendous amount of technological change over the last several decades. And oftentimes a technology comes along and it seems to threaten our industry. But if anything, many of these technologies have actually benefited our industry, and it’s helped drive the growth of the industry.

Maurice Fuller [00:03:51]:
But with generative AI, it’s really different this time because this is one of these technologies that will benefit the industry overall. The industry is definitely going to grow as a result of generative AI, but it’s also going to drive tremendous change in the way that the individual firms operate internally, and it’s going to lead to significantly higher operational efficiencies. And so we have not really seen substantial performance improvements in staffing firms in the 30 years that I’ve been part of the industry. I started as a recruiter in the late 1990s, recruiting it and engineering folks. And once I got up to speed on this industry and became fully productive, I was consistently placing two people per week on assignments. And I was probably, let’s say, in the top 10% of my office in terms of performance. Now, as a management consultant and technology expert, when I’m working with clients and I’m looking at the performance of recruiters on the team, no matter what industry segment they’re in, if we see recruiters that are performing above five or six placements per month, they’re doing really, really well. So why is it with all the advancements that we’ve had in technology, with computers that are 500 to 1000 times faster and more powerful, with hundreds of millions of lines of software that have been produced specifically to support staffing and recruiting, that we haven’t seen material improvements in the performance of recruiters? Now, that isn’t to say we haven’t seen improvements in some areas.

Maurice Fuller [00:05:40]:
Technologies like automation, which we’re going to touch upon, really have made a difference. But given the advancements in technology, we haven’t seen improvements in productivity that are commensurate with what we would expect on the computing side. And I think the reason is because we just haven’t had the right technologies in place to enable sort of automation of all the remaining pieces of the recruiting process. And that missing technology is these large language models, which is a really massive breakthrough in computing technology. So it fills in a gap that has held us back from automating substantially the most parts of the recruiting process. So this time really is different. And so it’s imperative for staffing leaders and owners to really pay attention to technology and the implications on their firm. Number two, with this generative AI, we really are at the beginning of a new industrial revolution.

Maurice Fuller [00:06:40]:
These industrial revolutions come along every 60 to 80 years. The last one occurred in the mid 1960s, primarily as a result of the birth of the IBM 360 computer. Before that, we had a technological revolution around the turn of the previous century, where we had the invention of electricity and telephones and radios and automobiles that drove substantial performance improvements. Before that, we had an industrial revolution that brought about improvements in textile efficiencies, steam engines, higher levels of production of steel, et cetera. So I’m pointing this out to let your listeners know just how significant this moment in time is. We are at the very beginning of a new industrial revolution that’s going to drive a tremendous amount of change in our industry. So the question is, what is at the very core of this new industrial revolution? What is driving all this technological change? I mentioned earlier, it’s these large language models. What fundamentally has enabled these large language models to exist and be stood up? And the answer is this technology that Nvidia has developed, this H 100 platform, which is a massive breakthrough.

Maurice Fuller [00:08:02]:
It’s as big of a breakthrough in computing as the IBM 360 computer was 60 years ago. Everything that we’ve done in computing over the last 60 years has really been built off of that IBM 360 architecture, the intel architecture, the arm architecture. It’s really a big extension of what IBM did in the 1960s and led to massive computerization of everything. The Nvidia H 100 is a massive breakthrough. It’s a box that costs about $200,000. It contains 30,000 chips, it draws 10,000 amps of power, and it combines thousands and thousands of graphical processing units together in a high performance architecture that enables us to do the kind of processing that’s required to build these large language models. And there is incredible, massive demand for these H 100 boxes. And Nvidia is not the only player.

Maurice Fuller [00:09:03]:
AMD is right behind it. They’ve got their version of it. But Nvidia dominates this market with, let’s say, 90 plus percent market share. I read a survey a while back that said that 95% of wealth that has been created that exists today has been created on the back of the birth of the microprocessor, which occurred in the early 1970s, about, let’s say, about eight years after the IBM 360. So 95% of wealth today, based on the microprocessor, I believe that 90% of wealth that’s going to be created in the next 25 years will be built off of AI and generative AI. So traditional computing that has brought us up to this point created 95% of wealth to date. But traditional computing will kind of lay the foundation for AI to provide the next level of value creation going forward. And here’s what’s important for everyone to understand, is that this AI cuts right to the very heart of the operations of our staffing firm.

Maurice Fuller [00:10:10]:
Like I mentioned before, it’s the missing ingredient that’s held us back from significant amounts of productivity gains and operational efficiencies. And so it’s really important to factor this into all of your planning. The third point is that these large language models and the work that Nvidia has done has led to tremendous demand for AI chips. So Nvidia has over a one year backlog for their chips, and they’ve been growing at a massive clip, and that’s why they’re now one of the top five most valuable companies in the world. And just in the last month or so, Sam Altman, who’s the head of OpenAI, has been talking about the need to invest five to $7 trillion into foundries, integrated circuit manufacturing plants to support the production of AI chips. So to put five to $7 trillion into context, that represents about 30% of US annual GDP, which is about $20 trillion. Global GDP is about 80 billion. So five to seven might be about 9%, 89% of global GDP if you were to look at it just in one year.

Maurice Fuller [00:11:30]:
Now, of course, that five to seven would be spread out over multiple years. So basically, what Sam Altman is saying is that we need to spend 1% of global GDP specifically on IC fabrication plants to support the rising demand for AI chips, and specifically, that’s going to allow production of AI chips from Nvidia, AMD, intel, et cetera. So I’m pointing this out to say, hey, we’re going to see massive improvement in the production of AI chips, significant improvement. And there’s discussion now of, like, right now, we might be at, say, 40, $50 billion of AI chips but the market should grow to 400 billion by 2027 and like a trillion dollars by 2030 for these AI chips. So again, this is another indicator that these AI chips and the large language models are going to drive massive change within the staffing industry and all the industries around us in the years ahead. The other point I would like to make is that AI is improving at a double exponential rate. So if you look at the rate at which chat GPT has become smarter and smarter going back just a few years, chat GPT one, two, which we never really saw, but we heard a little bit about it, and we’re at three and four now. It’s been theorized that chachipt is currently at about an IQ of around 150, but the next version could be at an IQ at 1000 or higher.

Maurice Fuller [00:13:14]:
If you think ahead, Chachi PT six, that is likely to be in the IQ in the thousands, right? So the capabilities are rising very quickly, almost daily, and it’s enabling all kinds of amazing capabilities. So if you saw the demo of Sora, Sora is this video technology that you can prompt, give it a prompt, and it will create videos that are hyper realistic. What’s interesting is you see these videos and these people and these scenes have never existed before, and yet they’re being created by video. So you can imagine the studio, movie studios of the future will be built off of technologies like Sora. Kids in their bedrooms are going to be able to produce movies that just a few years ago might have cost $10 million, $100 million to produce, and they’re going to be able to just produce them on their laptops. So a huge amount of content that we consume in the years ahead will be produced using AI. And so another really interesting use case for generative AI has been these self driving cars that Tesla has been working on. So for many, many years, Tesla is building this self driving autonomous driving capabilities, and they’ve been doing it using traditional rules based technology, using C code, hundreds of thousands of lines of C code.

Maurice Fuller [00:14:43]:
And the progress has kind of stalled out. And everybody was wondering, like, how many more lines of code do we need to write in order to perfect the self driving? Well, Tesla took an entirely different approach, and they built these supercomputers that take all the video data and other data of their current customers that are driving Teslas, and it feeds it into the supercomputer which trains these large language models to drive the way that humans drive. So in a rules based system, you might come up to a stop sign and halt the car, and you would have an instruction that says if there’s a stop sign, we stop. But humans actually kind of slow down and sometimes they kind of slowly go through that stop sign. And so now with these large language models, we can train the car to drive the way humans are actually driving. And the most recent version of Tesla’s self driving technology is built on these large language models, and it’s a real breakthrough in terms of the performance and a measure that’s used within the industry called interventions per mile. So anyway, there already we’re seeing large language models put to use and are really helping to produce significant gains in the performance of these cars. And so all of this leads to the conclusion that I hinted at before, which is that generative AI is going to become just a massive opportunity to create wealth in the years ahead.

Maurice Fuller [00:16:14]:
So it’s extremely exciting what is ahead and what we can look forward to, but it’s also going to result in significant changes and significant disruption. So it’s imperative for people to really think about what AI can bring and how that’s going to drive significant change.

Kortney Harmon [00:16:33]:
It’s exciting, but it’s almost scary. You’re in a car that, I’m not saying the Tesla cars, but you’re in a car with the pedal down and you’re going down the same path and there’s stuff coming at you left and right. So all of this stuff that you just said is interesting, it’s fascinating, and you’ve got to be crazy to think that it’s not going to change where we are today and where we’re going, because we’ve already seen, I know Katie and myself have only been using chat GPT for probably a year and a half now, but just to see the drastic changes already and what it’s doing to our industry is fascinating.

Maurice Fuller [00:17:07]:
Yeah, it really is. And we’re seeing more and more demos with developers and ATS providers that are building capabilities into their system based on large language models. And it’s really exciting the solutions that are coming forward.

Kortney Harmon [00:17:20]:
I love that. So based on what you normally do, you usually do the ten tech trends and this year you’ve arranged them all around AI functionality, am I correct?

Maurice Fuller [00:17:30]:
Yeah, many of them are the same trends that we’ve talked about in the past with some new trends, but what’s so interesting is that now all of these trends are greatly infused by AI. And so AI has really changed so much about the future of these technology trends. We’ve had to completely revisit everything and think about it in light of how AI is going to change, for example, automation, which we’ll talk about, and how automation and AI will work hand in glove to deliver automation services.

Kortney Harmon [00:18:02]:
I love that. So we’re going to go through all ten of your AI topics, but I’m going to try to ask a question around them and that’ll kind of give audience and maybe more concept around the topic that we’re talking about specific to the staffing and recruiting industry.

Maurice Fuller [00:18:17]:
So the top ten trends for 2024 through 2027 are hyper automation, conversational AI staffing, AI clouds platforms, data powered operations, intelligent applications, total experience AI, enhanced marketing, safe and responsible AI, and autonomous staffing and AI driven staffing firms.

Kortney Harmon [00:18:39]:
I love it. So let’s start with hyper automation. Talk to me a little bit more around what you were thinking here. How is the robotic process, automation and AI going to be used to automate? Whether is it repetitive tasks in our industry? What are you thinking around that one?

Maurice Fuller [00:18:55]:
Yeah, so automation is a fairly new phenomenon in the staffing industry. It really started to come into the forefront, let’s say around 2018 2017, kind of in that time frame. And the way I think about it is that you have ATS providers who have given us the ability to program the ATS either through workflows or through sequences. Before we had some of these automation technologies and low code programming technologies, we were programming, often directly against the API, in order to enable automation. But that’s pretty time consuming and requires development resources, and it’s expensive to do. But now we can automate our staffing firms much more, cost efficiently. So even today, surprisingly, if you look across the entire industry, maybe 20% to 25% of staffing and recruiting firms have invested in automation. And the typical staffing firm that is invested in automation is usually running about ten to 20 plus automation.

Maurice Fuller [00:20:06]:
So they’ve invested in the technology, they’ve put some time and effort into it, but haven’t really scratched the surface beyond some of the most basic automations that we would expect staffing firms to have in place. So today we believe that the new gold standard for automations within a staffing firm is 100. We believe that staffing firms should get to 100 automations to help automate many different facets of their staffing operations. And many firms that have put their minds to it and have dedicated the resources have quickly been building up their automations to 100 and well beyond that. So we have staffing firms now that are running hundreds and hundreds of automations, and they’re seeing real significant productivity gains as a result of that. And what’s so exciting about automation is it’s a way to automate routine tasks, which are typically low value but have to be done. And so by doing this automation, it frees up humans to be able to work on higher value added tasks, specifically advising candidates, negotiating with candidates, selling candidates. This is really what we do best.

Maurice Fuller [00:21:19]:
And for me, when I worked in recruiting, this is what I enjoyed the most, was helping get candidates placed on assignments and helping candidates with their careers and help them make good decisions to advance their careers. And everything else just kind of got in the way of that. And so this is what we’re able to increasingly automate through rules based automation, and then the rest of it is going to be automated through large language models. There’s a lot of other benefits, I just want to point out. Automation leads to higher accuracy of our operations, fewer errors. It speeds up operations in staffing and recruiting. It’s all about speed and how quickly we can move candidates through the process. It also improves the overall experience that we’re delivering to all of our stakeholders.

Maurice Fuller [00:22:11]:
When we can automate different facets of the recruiting process, it improves compliance with legal compliance, or compliance with internal operational procedures, helps us mitigate risk of making mistakes. And as I mentioned before, it also enables us to work on higher value added tests, which raises employee satisfaction. So if I’m a recruiter, having this technology that just takes care of things that are low value enables me to make more placements, which enables me to make more money, and that’s something that I can get excited about and get behind. So it’s important when we’re automating that everybody understands, hey, we’re doing this to benefit everybody, and you will benefit because this will make you more efficient. This will enable you to make more placements, and that will lead to higher financial compensation for you. So I think the last point I would want to make is that from this point forward, staffing firms will never stop automating. It’s not the kind of thing where you can just buy a piece of technology, plug it in, and it takes care of itself. This is an ongoing, continuous improvement process that will exist as long as staffing firms are still in business.

Maurice Fuller [00:23:26]:
You will always be automating more and more parts of your business, either through rules based automation, workflows and sequences, or AI based automation built off of large language models and neural nets and deep learning. Oh, one more point I want to make. It’s interesting how we’re also seeing rules based automation and AI work together. So rules based automation could at some point call an AI to perform a specific task, and then those two working together to deliver value to the stakeholders that we’re working with.

Kortney Harmon [00:24:06]:
It’s changing so rapidly, and I love that. Those are very interesting things. You actually surprised me when you said only 20% of organizations are automating today. My assumption was much higher than that. So that was very interesting to me.

Maurice Fuller [00:24:20]:
I would have thought the number would be much higher. But in my own experience as a consultant, I’m always surprised when I encounter clients that have not invested at all in automation. And I’m probably even more surprised when I encounter clients that have especially big staffing firms that have invested a certain amount in automation. But when you dig deep into it, there’s really only a handful of automations that are supporting their business. Considering how significant the return on investment on automation is, staffing firms should be investing much more heavily into AI and automation.

Kortney Harmon [00:25:00]:
I think that’s wonderful. So thank you for that. I think number two on your list was conversational AI. There’s probably a lot to unpack with this, but whether we’re an operations person thinking about best practices for implementation or workflows, you talked about 100 different automations in your business. So talk to me about a little bit more about conversational AI and what do you think is going to happen here?

Maurice Fuller [00:25:25]:
Yeah, so conversational AI is basically the ability to have conversations with computers, humans talking to computers, and more and more the way that we engage with different computing platforms, whether it’s our phone or our watch or our laptop or our iPad, it’s going to be through conversations. And there’s even new devices that are being invented that are based entirely off of conversations. So you’re going to see hardware devices, for example, emerge out of organizations like OpenAI that are just strictly based on conversation. So more and more, the way that we work with the various programs and operating systems will be conversational. So it’s not just one way where we’re giving directives to the computer and telling it what we want to do. It’s going to be communicating right back to us like a human would be communicating. So we’ll be engaging back and forth in a very humanlike conversation. So, for example, with these large language models, we’re now able to talk to the computer and say, hey, could you please produce a report that shows me all the candidates that are available in our system with which we’ve had a conversation in the last three months who reside within 2 miles of this location, and the software should be able to interpret that and produce that report really rapidly.

Maurice Fuller [00:27:09]:
And this is not hypothetical. I’ve actually seen this already. This type of capability exists already on certain computing systems, and it’s going to become extremely widespread. But we’re also seeing the first indications of this on some of these tools that are used to take conversations that we have on Zoom and summarize those conversations like fathom and distill it into the key talking points that were covered and action items that spin out of that. The next step out of that would be to listen to every conversation that goes on. It just follows you all day long and listens to everything that you say. And if your wife tells you, hey, it’s important that we do this, and you say, yes, I’ll do that, honey, this AI could potentially remind you a couple of hours later, hey, remember your wife asked you to do such and such. So this is what it means to be conversational.

Maurice Fuller [00:28:08]:
It’s going to be tools that help us get through the day and be more effective at what we do. And so we’re going to have more and more of these conversations just on an ongoing basis with these various AIs. AIs in our phone, AIs on our laptop. Now, in the context of staffing and recruiting, we have some really interesting tools that have emerged. So, for example, converse AI is a tool that engages in conversations with candidates. It has this Persona, Jamie, that makes outbound phone calls and sends out text messages and emails and reaches out to candidates. And I’ve seen demos of competitors to converse AI, which are astonishing. To hear these conversations going on.

Maurice Fuller [00:28:54]:
They’re based on large language models. It is so human like, it’s scary. And what’s so interesting about this is that we have a team of recruiters. We think, in our minds, okay, we’re constrained by the number of recruiters in our organization. We align the number of recruiters that we have to the volume of orders that we’re getting in. But with a tool like conversational bot, we can quickly scale that bot up. We don’t have to have just one or ten. We could have 100 or 10,000.

Maurice Fuller [00:29:25]:
And they run 24/7 so you can. In software, even a small company could quickly scale up, up their sourcing capabilities to talk to thousands of candidates concurrently using these bots. And these bots are always upbeat. They’re always friendly. They’re programmed to be helpful. They never have a bad day. They are highly efficient. They stay on track.

Maurice Fuller [00:29:55]:
They don’t get distracted. And so they’re really going to help us improve productivity, but it’s also going to enable small, very savvy staffing recruiting firms that can take advantage of this technology to scale up very efficiently. And if you think back to the comment I made earlier about AI improving at a double exponential rate from an IQ standpoint, think about this, that you’re spinning up more and more of these highly intelligent bots that can reach out and have more and more intelligent conversations with candidates to qualify them and to negotiate with them. And it really is going to change the dynamics and the economics and efficiencies of staffing firms in the next five to ten years in a very, very profound way. The other thing is that it’s so interesting is that these bots can change languages. So if you have a candidate that’s a spanish speaker, immediately you could switch into Spanish, and you can also change the voice. It could go male to female. It could also have different regional accents.

Maurice Fuller [00:31:00]:
So you could have a slightly different accent in the northeast versus a different accent in the south, versus a different accent in the west coast to match the regional dialects in different regions. So another aspect of this that’s interesting is that these bots can take advantage of every piece of information that is contained within your ATS system. So every text message that’s ever been communicated with that candidate, every email, every resume, the LinkedIn profile, transcriptions of conversations, all of that information would factor in to the way that the bot will communicate with the candidate. And so right now, as a recruiter, you’re kind of doing the very best that you can. Before you have a conversation, you quickly get up to speed on what’s been said, and you kind of rifle through the different notes. But the AI and these large language models, they have everything immediately at their disposal. They don’t have to spend any time bringing this information into your brain. It’s already there, and they can immediately engage in a conversation with every piece of information that’s available.

Maurice Fuller [00:32:09]:
So again, this is another one of those things that’s going to streamline the staffing and recruiting process.

Kortney Harmon [00:32:15]:
That’s truly fascinating to think about. That before we pick up the phone. We’re looking at a LinkedIn profile to keep it fresh, bring things to our head, but that’s happening within milliseconds at this point in time. Truly fascinating.

Maurice Fuller [00:32:28]:
It really is. It’s going to change the world in ways that are barely imaginable at this point, and it’s going to happen very quickly. There’s famous set of pictures that were taken in New York City in the early 19 hundreds, and in one picture on the same spot, there is all these horse and buggies that are going down the street. And there’s a single car, one single car in this picture. Fast forward eleven years, same scene, same street, and there is nothing but cars. And there’s a single horse and buggy that’s still going down the street. So that is the sort of the automobile revolution and how that played out during the last turn of the century. And we’ll see a similar kind of phenomenon with respect to AI and the way it changes our world in the years ahead.

Kortney Harmon [00:33:22]:
Absolutely. Thanks so much for joining part one of our conversation with Maurice Fuller. He’s a true staffing industry veteran and visionary behind staffing tech.

Kortney Harmon [00:33:34]:
Today, we delved into the potential of.

Kortney Harmon [00:33:36]:
Artificial intelligence and its impact on the staffing and recruiting industry for years to come. We’ve also explored the first portion of the AI trends on Maurice’s list of the top ten AI trends. Tune in on Thursday as we drop.

Kortney Harmon [00:33:52]:
The remainder of the trends that you.

Kortney Harmon [00:33:54]:
Need to be in the know for when it comes to the talent industry.

Kortney Harmon [00:34:00]:
I’m Courtney Harmon with Krillate. Thanks for joining the full desk experience. Please feel free to submit any questions for next session to full [email protected] or ask us live next session if you enjoyed our show.

Kortney Harmon [00:34:15]:
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Kortney Harmon [00:34:17]:
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