AI & the Future of Work

This transcript was created using AI tools and is not a verbatim transcript of the episode. Please forgive any spelling and grammar errors that may be included. 

Courtney: [00:00:00] You’ve probably heard the Steve Jobs analogy from the early days of Apple that the PC would become a bicycle for the mind. So what’s the appropriate analogy for what AI will become? A Ferrari, a fighter jet, or maybe I would get that flying car from the Jetsons.

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era. As always, I’m joined by Knownwell CEO David DeWolf, Chief Product Officer Mohan Rao, and Chief Strategy Officer Pete Buer.

We also have a discussion with Naeem Ishaq, CFO of Checkr, about how the roles companies are hiring for are changing in the AI era. And we’ll welcome Pete and CounterPete back to the studio to let us know if we all need to start working on our resumes.

But first, let’s dig into the bicycle for the mind question with David and Mohan.

Courtney: Steve Jobs famously described the personal computer, and I’m sure you two remember this as a bicycle for the mind. And so today I wanna talk about what’s the equivalent for that analogy with ai and how will AI change the way we work in ways that at this early stage may be hard for us to imagine.

So again, really. Future casting. What will work look like in this age of ai?

Mohan: Yeah. You know, I wonder what Steve Jobs himself would’ve, uh, said about this, because it’s such a beau beautiful metaphor. Right? So, but, um, I think it, uh, described the computing gauge really well, but I’m not sure that it, um, describes the AI age that well. It falls way short of, uh, of it, right? So there [00:02:00] are two sort of, uh, you know, sat Nadella has talked about this a bit, about what should the updated metaphor be.

Uh, right. So in my own mind, this can be like one of two possibilities. It can be something that goes way faster than a bicycle, right? Uh, right. It can, it can be a motor motorbike, uh, that goes way faster.

Or it could be having, um, uh, a second brain, uh, sort of like attached to your primary brain.

Um, and that’s doing the thinking for you and adding cognition.

So it is sort of this combination of a motorbike and a second brain. Where you can go faster and have a cognitive partner with you, uh, for, from a work perspective.

So let me leave it there and see what you all have to add.

David: Well, you know, so I thought instead of just sitting here and guessing what Steve would say, I thought I would ask him. And so I went to my friend chat, GPT, while you

were [00:03:00] talking, Mohan, and I just told it to act like Steve Jobs and to give us the updated quote if the computer is the bicycle of the mind.

And Steve himself apparently says that AI is the ultimate tool, transforming our minds into rocket ships, propelling us to explore uncharted realms of creativity and knowledge. I think that’s kind of what you said, but I, I think the bottom line is there’s something about the bicycle that I think is missed in this rocket ship and just going faster.

Um, the, there’s a creativity in the bicycle. There’s a movement and an activity of the human person that I don’t want to get lost when we move. To the rocket ship. I think the rocket ship feels more like just the machine that does the work for me and I sit there and push a button, whereas the bicycle requires me as a human person to, to drive it and to work in concert with it.

And that fluidity, I think, gets lost in [00:04:00] these analogies.

Um, so while I agree with the direction of Steve himself in chat, GPT and your thought, Mohan, I wanna make sure that we keep the human person in involved because we have seen as ai.

Gets rolled out more and more the power of having a human in the loop and what that can do.

And I really believe that AI has the ability to elevate humanity and, and just like the bicycle of the mind takes the mind to the next level and it gives us a workout and say, I think AI can do the same thing for us Yes, on steroids, yes, at the next level, but it can really help us to be even more human.

And when we apply that to the nature of work, what I say is there’s still all sorts of things in work that are route. And boring and analytic, tedious things that we don’t have to do that computers can do better than us. How can we leverage the new bicycle of the mind to [00:05:00] be able to do those for us? Take it off us, but then also then elevate those things that are truly human.

Um, things like. Um, uh, you know, building relationships. How can we have more knowledge and, and, um, insights into the people we’re building relationships with so we can do a better job at it and, and understand other people. Um, how can we use judgment more and apply our value systems to the facts and the insights that we see?

How can we be even more creative? Those types of things, I think is where the world is going, where we are going to take humanity, what’s really uniquely human to the next level.

Mohan: whenever we’ve seen these transformation periods in the past, uh, the, uh, you know, we need to be also. Uh, be very careful about how we employ these new technologies, right? So the Industrial Revolution caused so many inequalities. It cost more child labor. It cost so [00:06:00] many things till we dug out of it to a substantial degree, but still, it took a long time.

What do you think we need to be careful of here, Courtney?

Courtney: I mean, honestly, right now I’m still twitching from you talking about, uh, attaching a computer to my brain. Um, so I haven’t quite recovered from that.

David: Isn’t that a great example of what we need to be careful of is there are probably ethical moral boundaries that we need to debate as a society and, and like figure out where are our principles and our values and where are the lines, right? technology inherently blends in more and more and more with our lives, right?

It’s gotten smaller. We’ve gone from main great mainframes. To desktop computers, to laptops, to tablets, to mobile phones, to watches, right? It’s getting smaller and closer and more personal. What does that mean? Where is that line is the example I think of the type of thing we need to grapple with. I.

Mohan: Yeah, [00:07:00] there’s no question that there is gonna be so much disruption from this that we have to be very thoughtful about how we employ this. But going back to the analogy, I’m super, um, excited about having this cog cognition, this extra level of cognition that we can all employ, right? So, uh, ChatGPT is a good initial starting example, right?

So you can go there. Get your ideas flowing and then create your own ideas, right? So you can do that, but truly as this technology matures, having a second brain, uh, uh, is, is truly an appealing thing, right? So I need a break. Hey, second brain, do some work for me. Uh, kind of think about these things. I’m gonna come back to, uh, that, that thing when I have some time.

I think it’s super, um, super exciting to have something like This.

David: I do too. And the other thing that comes to my mind when you say that is, um, that there is the exciting part in the elevation that you described, being able to offload things and have it done. If it’s [00:08:00] more route and doesn’t need something uniquely human being able to double capacity, right? Get us start all these types of things.

I also think we can go back to just recent history of social media and how awesome that was to begin to connect people across the world when it first came out. I. And then I think society as a whole now recognizes the detriment of that too, as we see kids walking around with their fo face in their screen and not knowing how to have a conversation, right?

Um, I sit on the board of a university and the professors can tell the decline in social abilities for these kids that grew up with the phones. What does that mean? What does it do to us? And I think we need to have our eyes open for the things that we may not be able to see, right? There may be lines that we can see now and we question.

But I also think we need to, to know that there are unintended consequences and make sure that we keep our eyes open for those as they go. And so it’s looking at the positives and the negatives and navigating it as we chart new territories.

Courtney: [00:09:00] David, it’s so interesting. I was thinking the exact same thing. I just, um, started a book called The Anxious Generation and it talks a lot about these, um, ramifications of social media and phones and how it’s impacting I. You know, kids today, and I think maybe AI, I wonder if it will be the same for us in the professional lens.

For example, Mohan, even just going back to your story of the second brain, even if we can have that, the idea of just being able to check out because we could just more and more offload to the second brain. Like you’re like, I need a break. Well, it could just be like, I need. All day. I’m just gonna take a nap today.

Let the second brain take over for the day of like, how do we let that encroachment, just like we’ve seen with social media, actually start to deteriorate. You know what we create, what we bring to the world, the value that we bring to [00:10:00] each other. And so it’s just an interesting. A lens to think of what we’ve learned from social media and I’m, it’s kind of sad how long it’s taken us to really learn some of this.

And still, it’s so hard. You know, I had a kid come to my house, uh, recently that was. You know, under the age of 10 with a cell phone.

And I was like, what? What’s happening? What is happening? I thought we had learned a few things. Um, and so it’s just interesting, you know, even what you said of it may take a while for us to understand the guardrails that we need to have.

I think it’s what do y’all think needs to happen proactively? I think that’s the hard part. It’s, we, I don’t think we can wait until we have hindsight. To help us figure out what we need to do. It’s at some point I think there’s a proactiveness that we need to establish, and I, I’m certainly one sitting here thinking, how do we do that well in our businesses?

David: Yeah, I mean, I think I’ve said this on this podcast before and I’ve said it in other places and I go back to it. [00:11:00] To me, you can’t script this stuff. So you have to go back to

first things, and I think as a society as a whole, we have over-indexed on the STEM subjects, and science and technology are phenomenal.

It’s where I’ve made my career, but I think the humanities are really important. If you want to go back to the first things, if you wanna look at the fundamental principles that will allow us. To navigate these times as we’re hit and faced with new things. It is the study of history. It’s the study of philosophy.

It’s the study, uh, of religion. It’s the study of art, it’s the study of all of those humanities that really. Give us the ability to figure out, not technologically how do we advance, but as human beings, how do we advance alongside this technology? And how do we really understand the fundamentals of what it means to be human, um, both as individuals and as a society.

Mohan: Yeah, I completely agree that the, uh, [00:12:00] humanities, those subjects, those, uh, that give us context. Text and values are, uh, super important. Uh, but even when you have a second brain, right? So you have to communicate very clearly with your second brain. You have to set the context, uh, um, and you have to, uh, describe the outcomes, right?

That itself is an art and that requires clear thinking that only humans are best capable of, uh, providing that because of all of the grounding that we have in various subjects leading up to the values that you are gonna optimize for.

David: Mohan, when we, we talk about all of this, I think it’s a lot easier sometimes to focus on the societal impact. And I think when these types of subjects come up, we kind of merge there. Bring it back to Courtney’s questions of the the future of work. How does all of this, we’re talking about start to talk about.

An organization in a business, where should we be focused to make sure we’re building the muscles [00:13:00] we need in an organization to navigate these times appropriately.

Mohan: Yeah, just sort of starting with, uh, what are the major pain points?

Uh, sometimes we call it, uh, use cases or, uh, uh, you know, more technical terms, but thinking about in a business, what the major. Uh, pain points, or, I mean, ultimately there are, you can divide that into two. You can, uh, either, um, increase, um, efficiency or you can, uh, improve, the value you offer to, uh, your, um, uh, end customers, right?

So internal versus external views of things. just kind of starting with that, describing the problem set. Understanding the potential solutions that are out there, and then providing the guardrails. Uh, right. So that is sort of the most important thing that you can do as a business leader, right? You can call it governance, but it’s essentially guardrails towards, uh, employing these types of technologies.

Ultimately, what you wanna optimize for is. Um, all of the business things that [00:14:00] we worry about, right? Doing things in an ethical manner, doing things in a legal manner, doing, uh, adding value to your customers, so on and so forth. So that’s where I would start in a business context.

David: The other area that I see underdeveloped sometimes is an organization’s ideology, right? Everybody talks about. The, mission, vision, values and purpose and all of these things. And these concepts get thrown around in management books. Um, but a lot of times they’re posters on walls. Um, I think organizations can really exercise the muscles.

Um, that’s a guardrail. Right. why do we exist? What are our behaviors, right? Fundamental questions on how we show up and why we show up, I think can be muscles that we exercise to insert into this equation as, as other guardrails, uh, to go along with, you know, the basics of ethics and legal and customer value and those types of things.

Courtney: I love that it’s, it’s like a re leaning into the humanities in a way. The ideology is doing that at the leadership [00:15:00] level..

David Mohan. I love that we went very deep, uh, and then very practical, so thank you both for that.

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Since the Paris Olympics are starting soon, we’re excited to welcome everyone’s favorite mental gymnast. Back to the show for another round of Pete CounterPete. [00:16:00] welcome back.

Pete: Thanks, Courtney. Thanks for the mental image of me doing gymnastics.

Courtney: So, Pete, this week the phrase I’d like you to take on is AI is coming for all our jobs.

Pete: Okay, cool. AI alone would have a hard time taking every job. I realize I’m the argument four, and I’ll get to it in a second. Just take the notion of, of manual labor, right? AI. Is not gonna do anything about the shovel sitting next to where the ditch needs to be on its own right.

It’s, uh, purpose-built AI nested among various technologies to power a machine. Then it would crush it, right? It would probably categorize all the bugs and, you know, types of ore found in the ditch along the way. Um. So let’s say we’re talking about this larger category of, uh, systems of intelligence, uh, and automation powered by ai, uh, using data and algorithms, AI and learning to drive [00:17:00] outcomes, whether through machine or, or not.

In that case, yes, a hundred percent. AI will take every job. Um. We could get the right group of people to sit down right now and look at any job on the planet and build an AI powered system of intelligence. Uh, however Rube Goldberg looking, it might be in design in the end and take that job away from the human who was previously doing it.

Courtney: Okay, thanks Pete. That is I, I don’t know how I feel about that. I may need to take the afternoon to work on my resume, I’m not sure it will do me any good counter.

Pete, is there any hope for us humans?

Pete: Well, no, of course, that’s a ridiculous statement. Even if AI-driven solutions could take every job they want. Three simple reasons, number one. It’s not always the best tool for the job. There are just some jobs better done by humans, even if AI could take a crack at [00:18:00] them because humanity is somehow the active ingredient of the work.

Think Think about the bedside manner of an empathetic physician or the eye watering motivation of the best leader you’ve worked for over time. Second, there are some jobs :where wholesale automation ends up not being as effective as the human technology hybrid. I’m thinking here of certain creative jobs where AI can take you 80% of the way there, but the job’s not done until the human touch is applied.

In the end or, or people management. Diverse teams of people in a challenging work environments are better managed, cultivated and motivated by Ironman than by Jarvis. third, there are some jobs that just aren’t practical to automate. Put simply, would I invest in that In a world of trade-offs? The answer’s no. And awful lot of the time, maybe the best evidence for how this. Will go down is to take a look at [00:19:00] history.

Think about other disruptive technologies that have arrived through time. They tend to go through a two-step dance. The Simple case of spreadsheets, right? Took away massive numbers of actuarial and clerical jobs, and then launched armies of analysts and financial modelers.

World Economic Forum data plays well here. Um, 2023 study, they predict 83 million jobs will be de displaced by AI and automation, and then 97 new jobs will be created by AI and automation. Here, Courtney, with your permission, uh, is where I’d like to invite a third participant into the conversation.

Courtney: I love it.

Pete: And this is RePete because I’m gonna hit a point that I’ve made many times in our conversations and it’s about that last. Data exhibits, uh, where we start with jobs being lost and we end with jobs being created. The difficult reality is that there is [00:20:00] time between point A and point B, and there’s loss between point A and point B.

The same people who had the jobs in the beginning will not necessarily be the ones who are suited for the jobs in the end. And so despite that starting point. My, uh, counterpoint, uh, support of re repeat losing track, sorry, is that I believe and I bet with the leaders of society, in business, in education, in government and in families, and that we will take the active and thoughtful steps to steward the humans from point A to where they need to be at point B safely and with prosperity.

Courtney: I love it and I have to say for everybody that is listening to the audio version. Pete had a different hat for Pete, counter, Pete, and repeat. Um, so I love the all in nature and [00:21:00] just to join you there. I will also add my hat to the collection, um, in support of the 2032 Olympics that I’m hoping pickleball will be added to the lineup. Pete, as always, thank you.

Pete: Thank you, Courtney. All the best.

Courtney: Naeem Ishaq is the CFO of Checkr, a platform that uses AI to help more than a hundred thousand companies screen potential employees more efficiently, speed up the hiring process, and ultimately drive more revenue.

He sat down with Pete Buer recently to talk about how hiring is changing in the age of AI.

Pete: Naeem, welcome to the AI Knowhow Podcast. We’re so glad to have you here.

Naeem: Thank you for having me. Good morning.

Pete: May I ask for the sake of listeners to give them some context, uh, and in case they’re not familiar with Checkr, uh, a little bit about the business and [00:22:00] your role.

Naeem: Sure. Yeah. So Checkr is the leader in technology power background checks. were founded just 10 years ago in San Francisco where we continue to be headquartered. And in that time we’ve grown very significantly. And today we serve over 100,000 customers across nearly every size and nearly every industry. background checks play a critical role ensuring trust and safety, uh, and compliance for customers, and ultimately for their customers too. I’m the CFO at Checkr. I’ve been in the company for just under five years. In my role, CFO, of course, I lead finance, but also lead, uh, many other teams, including our corporate engineering IT systems teams, which is, um, probably a little bit relevant to this conversation.

Pete: Awesome. Uh, I like to ask the sort of, uh, lurid fun question first. Uh, as you know, this is a podcast that speaks to issues around ai.

How is AI creating new problems for background checking? I.

Naeem: Yeah, well, I think it’s, I don’t think it was so much as a problem as, as much as an opportunity. Um, so a little bit [00:23:00] of of background on, on Checkr too, as I mentioned, we are the technology leader in the background check space. When we were founded 10 years ago, we took a technology first approach from the very beginning.

And so for us, what that meant is applied AI in the form of machine learning that built those algorithms that we use to. Effectively structure makes sense of enormous quantities of data that comes from many, many thousands of different jurisdictions. Um, and then utilizing that technology to ultimately deliver a result to our customers that’s faster and more accurate.

and, and we’ve continued to evolve that too with, with emerging technologies in AI that we see today.

Pete: I guess I was, I was wondering about like the, the deep fake resumes and, you know, professional personas that can be created now. Like are, do you get a taste for that, presumably?

Naeem: You know, our, our world is a little bit less in, um, ID verification, which is, is probably where that comes.

Pete: Gotcha.

Naeem: in terms

Pete: I.

Naeem: uh, verification of things like, like criminal records or motor vehicle records.

Pete: you crossed the [00:24:00] 100,000 customer mark earlier this year. Congratulations on that. with all those customers and all that data, I suspect you have a really, uh, privileged window into the hiring market and kind of. Observing patterns and signals in how hiring is, is changing.

Are you seeing changes that are sort of AI driven in the way folks are searching for, uh, new hires or, or going about their process?

Naeem: Yeah, well, well certainly given our breadth, we have a really wide view into the overall health of the economy and can see trends in where companies are hiring more or less, as well as the impact of things like the turnover in the workforce. Um, our view, um, and both internal and from our observations is that AI, um, has a major role to play in improving productivity and effectiveness of the workforce.

Um, so we’ve seen this ourselves as we deploy things like AI powered agents to facilitate customer needs. Deploy AI tools to bring better insights for, you know, kind of day-to-day analysis for our employees, uh, to help us [00:25:00] make better decisions. And we hear this very much from our customers too. you know, the recent advancements, uh, that have made AI so broadly available to bring low cost, um, uh, tools to everyone made accessibility so much higher.

Um, so as whereas in the past, employers had to find like really, really specialized, uh, talented engineers and then find hard to retain them. From a small pool, um, both these open source and proprietary models and now readily available have dramatically lowered barriers and access to that, to that talent, and effectively not just the talent, but the end product itself.

Um, so that’s creating new opportunities for new class of worker who can focus on things like implementation and tuning AI for specific use cases, leveraging their business knowledge and context they have, um, about what’s needed. That is a dramatically bigger pool of folks, so that’s really exciting for opportunity for them and for many others as well.

Pete: Sounds like there’s a lot of change, but for the better it seems. How about at, at the level of [00:26:00] role? Would you, do you have a, a window into that? Are there, are there roles in the ascendant and roles that are going away in search?

Naeem: Yeah, I mean, it, it is these, the, the most notable is these new roles that are being created, which have, some have AI. actually in the title as an example. but they’re, they’re different from, you know, folks like machine learning engineer, which was what

Pete: Yep.

Naeem: what was needed.

And, uh, and then again, the, the classification, the worker tends to be, you know, quite different as well. And ultimately that is a bigger pull too. So there’s a lot of, you know, there can be some doom and gloom of course, in what AI means for the workforce. I, I think there’s, there’s certainly fear associated with that.

Um, you know, we, we tend to see and, and observe. The more optimistic end of it. There’s a limitless need for work to be done, for productivity to be raised. That typically results in more opportunity than not. Um, and that’s consistent with what we have seen so far. And it’s not to say some, um, types of roles will be affected or eliminated.

It’s, I think it’s a bit early at this point to, to see that. [00:27:00] Um, but it would be reasonable to expect that. But right now we’re seeing actually more, more roles being created.

Pete: That’s great.

So I, I, as I talk to, um, business leaders and, and talent leaders, when they get the question, you know, what’s, what’s gonna happen to our roles because of AI, I. There’s almost a knee jerk scripted reaction that goes to our philosophy is to augment, uh, and to think about AI as an enabler. And to your point, most of the time I’d like to believe that that’s true, but there will be times when it’s not, you know?

Um, are there, are there particular roles that, that sit in that second category? Are, are there some jobs that 10 years from now we, we kind of won’t see anymore?

Naeem: If I’m speculating here, it seems likely and there are some early observations to, you know, roles that require relatively little discretion. Um, uh, so for example, connecting one set of information, uh, and delivering that to someone else who may not have access to information. [00:28:00] That rot in nature, uh, those, even, even before generative ai, certainly, um, were already, you know, starting to be addressed and automated.

Pete: Yep.

Naeem: AI takes that to the next level because

Pete: Yep.

Naeem: of the work and interactions, I mean, we’ve seen that ourselves as we’ve deployed agents and helping our customers, um, uh, to be better served. and that again, ultimately will allow. Those folks who were previously, you know, doing kind of low level, uh, problem solving, uh, to, to elevate and address deeper problems, uh, which is ultimately more enriching from a career development perspective, from an intellectual stimulation perspective.

Um, but that, that is, that is different, uh, in terms of the requirement.

Pete: shifting gears and, drilling a little bit deep on something that you mentioned earlier, the notion of, of fairness. Um, There’s a lot of concern with AI, um, from a responsibility perspective around, uh, removing bias from recommendations and in particular, that trickles through to [00:29:00] hiring.

Of course.

How does, How does, Checkr help companies ensure fairness?

Naeem: Yeah, well this is very near and dear to our hearts. Um, our company mission is to build a fair future, um, full stop.

Pete: Nice.

Naeem: and that’s been the case from the very early days. And, you know, as, as, as I mentioned earlier, simply by utilizing technology, utilizing AI to construct the background checks and delivering them to our customers, the results come in much faster, which is helpful if you’re a candidate waiting to.

I, I ran into this situation where, um, you know, my family and I were looking to hire a babysitter, um, who, uh, unfortunately the, the company we were using was not using Checkr. That result took nine days to come back to us. Uh, at that point, um, we lost a candidate. Uh, she had moved on to, to do, do a different role.

So getting, getting the results faster is better for the, the employer. It’s better for the worker, for sure. Uh, number two, accuracy matters a lot. If you can imagine. Um, you know, if your name was, was [00:30:00] John Smith, there’s a lot of John Smith across the country. Um, and we wanna make sure, uh, in the interest of everyone, that if you’re searching for, uh, for example, a criminal record search for John Smith, that’s the actual John Smith who is applying for that job.

Um, and the, the risk and impact of getting that wrong is, is very severe. And so we found if our technology has allowed us to have. Significantly improved accuracy as well, which gets better and better over time. So that’s really critical. Uh, and then number three, uh, by utilizing technology, you can fundamentally also reduce or even eliminate bias in the hiring process.

Um, so, uh, when our customers go through evaluation of a candidate, they, you know, the, is the adjudication of a report. if they wanna take a nuanced view around what infractions to consider, what are relevant to the job, which ones are not. Um, if you’re hiring for one person in a week or once a month, that you can, you can probably handle that assuming you [00:31:00] can interpret the results, which itself can be challenging.

however, if you’re trying to hire for a thousand or tens of thousands, uh, in a week or a month, it’s virtually impossible to do that manually with any level of, of of nuance. So we’ve developed, uh, an adjudication suite which allows the administrator to set up rules around what infractions they will consider and what they will not, and they’ll ultimately help to facilitate that process.

That is fundamentally more fair because you have objective criteria that is utilized and it doesn’t vary from adjudicator to adjudicator who maybe woke up one day and was feeling grumpy and decided to be more stern in the review. That is not fair. Um, as an example, um, it’s also much more compliant ’cause you have a consistent record.

decisions and, and how they were made. Um, and so that software has allowed us to help millions of, of workers who have criminal records to ultimately find meaningful work. And that ties back to fundamentally to our mission, which [00:32:00] is to build a fair future. By allowing people who have made mistakes in the past, who’ve served their, debt to society and want to be productive members of society to reenter.

And it’s very difficult to reenter society in a productive way if you can’t find work. Um, and so we’ve been animated by that from the very beginning, and I’m proud to say

Pete: Yeah.

Naeem: able to help, uh, many, many people, um, you know, break through those barriers.

Pete: Thank you and thank you Naeem overall for joining us and, um, sharing your experience. And your thoughts we’re grateful.

Naeem: Great. Thank you Pete. It was wonderful to talk to.

Courtney: thanks as always for listening and watching. Don’t forget to give us a five star review or share the podcast. It really helps other people find this show. ~I.~ And at the end of every show, we’d like to ask one of our AI friends what they think about the topic at hand. ~. Your CEO is the worst. Uh, just kidding.~

Hey ChatGPT. How you doing? For this episode, we’re talking about the future of work and [00:33:00] where AI will fit in care to comment. And now you are in the know. Thanks as always for listening. We’ll see you next week with something a little different from the norm. Stay tuned for a recording of our recent round table on client retention in the AI era.