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Balancing the Future Ep. 17 - Risks and Rewards of Emerging Technologies with Dr. Sean Stein Smith
260 Plays17 days ago
Dr. Sean Stein Smith is an accounting professor at Lehman College and a leading educator on emerging technologies’ impact in the accounting profession. He joins our host to discuss AI, Bitcoin, Blockchain, and other technologies as they apply to an accountant’s ability to provide broader, more efficient client services. He stresses the importance of embracing learning as part of business transformation—not forgetting a healthy dose of foundational knowledge and critical analysis when using automation. Learn more about the changing industry landscape and best implementation practices for accountants.
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Transcript
Introduction to Dr. Sean Smith
00:00:10
Speaker
Welcome to another conversation on balancing the future. i am so excited again to have Dr. Sean Smith with us today. you know, when I looked at Dr. Smith's background, I said, this guy had a conversation with a very articulate, very smart guy.
00:00:25
Speaker
But when I looked at his bio, I'm like, my goodness, he is he accomplished in a lot of areas. We've had so many series now where we're talking about AI and we're
Dr. Smith's Career and Expertise
00:00:34
Speaker
talking about human capital. but We're talking about digital transformation and what that means for businesses.
00:00:39
Speaker
So I'm interested in his perspective because he is unique in the sense of based on what I can gather generically, He is in academia and he is a professor and he is also plugged into the consulting world. He's on boards. He's just has a touch and he has a ah understanding as it relates to transformation and transformation that includes.
00:01:02
Speaker
Obviously, we start talking about blockchain. We start talking about AI and Bitcoin and all these other things. So welcome, sir. So happy to have you. I know there's something I didn't cover.
00:01:13
Speaker
I'm not not good when it comes to buy. Thank you, Chris, and I'm happy to be here. happy to be having this conversation with you on all of those topics, crypto, blockchain, AI, transformation. that Those are all exciting areas for sure.
00:01:26
Speaker
So share share something with the audience that I didn't share. I mean, I know I tried to do you justice, but I just want them to understand how ah familiar you are with this subject matter and how it can be of value to them and what you're going to share.
00:01:38
Speaker
Absolutely. And so as you mentioned during the introduction, I'm currently in academia at Lehman College and I've been at that role and at Lehman since fall of 2017.
00:01:53
Speaker
um boy seventeen But prior to that, I worked in industry for about eight and a half years in a number of roles that I always thought of as half accounting, half finance, and half IT.
00:02:07
Speaker
And so as I was finishing up my PhD at the end of 2015, I was hearing things about blockchain, Bitcoin, and all the rest.
00:02:19
Speaker
And then honestly, Chris, but ever since then, i honestly have been you hands-on in that space doing research doing presentations consultations for you know various industries government agencies institutions of higher education and and have also written courses for the AICPA on this uh topic and then I also as you also mentioned I am on a number of boards for trade groups and also companies operating in that space. And then over the last 18 months or so, i have been adding some more AI background as as all of us have been trying to do, taking courses.
00:03:02
Speaker
i I've recently finished one at MIT, and I'm currently in the program at the U.S. Institute for AI. So, yeah, I've been in the space trying to dabble back and forth, have a have a foot in academia, but also have a foot in industry to keep myself ah to date on all of these fascinating topics.
00:03:25
Speaker
Awesome. Awesome. You know, when I when I thought about the questions that I wanted to ask you, what we could, you know, could share with
Impact of AI and Blockchain
00:03:33
Speaker
one another. You know, I think about, you know blockchain, I think about Bitcoin and I i know they're interrelated now. They they should be.
00:03:40
Speaker
and Okay. ah There's so many things going on. But when I first was introduced to transformation, it was transformation that was going to be more in the in ties with with blockchain based on my you know my my experience with ah technology and and transformation in general.
00:03:56
Speaker
And then here comes Bitcoin. and My son told me probably 15 years ago, probably wasn't that long ago, but it feels that like it's been that long. He says, Dad, give me $5,000 so I can invest in, so we can invest in Bitcoin. I'm like, why don't you take your two grand that you have in your account and invest in Bitcoin?
00:04:13
Speaker
Man, was he right. yeah And I was wrong. Turned out to be right. um and Absolutely. Absolutely. And then I started thinking about AI. OK, and we this is a revolution. I mean, this is the the next wave of whatever is coming our way as it relates to business and the way that we live our lives. And having a tool like this at our disposal will very much change how we function day in, day out, whether we're on the computer, whether we're in our homes, whether we're trying to figure out you know how to draft an outline for whatever subject we or information we're gonna deliver, I'm certain that we're gonna be using a tool to help us with that that exercise.
00:04:50
Speaker
what i What I'd like you to do, because for this audience and for those that don't fully understand, help us very, yeah mean, you don't have to go and expand a lot on this, but it'd be good to know when we say blockchain, when we say Bitcoin, when we say AI, generically, you know what what are we talking about? And I know I've got some that are sophisticated in the audience, but there's still a question mark, even for me at times. Now, what are we talking about? And when they're interrelated and they're connected, you know, as we move forward, what does that mean as well? So, you if you would mind sharing, I would appreciate it. Yeah, sure. And so the so the first point that I always like to make in any conversation on a podcast, at a client, in a classroom is, okay, fine.
00:05:34
Speaker
If we're talking about blockchain, or crypto or AI, all of those areas are incredibly broad, right? And and in those areas, there are all kinds of applications, use cases. So the first thing is to really hone in on, okay, what are we talking about and how are we trying to use it?
00:05:54
Speaker
So on that point, blockchain is basically just a permanent record of of transactions that have been added onto that blockchain by the members of that network.
00:06:08
Speaker
So if you wanna sort of visualize that, it's a giant Excel workbook that has tabs, rows, columns, and all all of those entries and transactions are permanent.
00:06:21
Speaker
After those entries have been approved by the members of the network, they are added onto the chain and it's permanent record. now Now, that It's a very you short definition, but it's powerful implications for audit, tax, and all kinds of other interesting things.
00:06:38
Speaker
So now Bitcoin, and honestly, any crypto asset, Bitcoin, Ether, XRP, Dogecoin, all of those, a a really good parallel there is that the internet,
00:06:52
Speaker
has applications. Zoom, websites, Skype, Amazon, blockchain also has applications. Bitcoin, XRP, Ether. So all of this stuff out here, stable coins, smart contracts, DAOs, DeFi, NFTs, everyone's favorite, all of those are just applications running on-chain.
00:07:18
Speaker
Then AI. Now, AI, it's a really interesting time here, Chris, right? Because all of us, you know or most of us grew up watching movies like the Terminator, Space Odyssey 2001, all kinds of other films like that, Star Trek, Star Wars, and AI, it's all the way out here.
00:07:39
Speaker
Whereas for most firms right now, the biggest applications of AI aren't the full cognitive computing you know angle. It's really ChatGPT or some other version of that.
00:07:51
Speaker
It's an interactive bot. That, to your point, can really help do a lot of that, you know not grunt work, but those you know more routine tasks that that have to be done, that occupied quite a big amount of time previously.
00:08:09
Speaker
and are important to help us do that higher level work. So AI for our conversation isn't, I mean, it's an incredibly broad area, but for our conversation, I'd say focusing and gen AI, basically chatbots and other interactive AIs is probably more sort of ah on the nose.
00:08:31
Speaker
You know, thanks for sharing that. When I think about academia and I think about the role that you're playing um and educating those that are coming up and through the ranks, obviously you understand the pipeline issue
Learning and Responsibility in Tech Careers
00:08:43
Speaker
that's going on. And, you know, I always tell those that are coming up and through the ranks. And as soon as they hit the doors, I said, you know, ultimately,
00:08:50
Speaker
you're responsible for your career. I wish someone would have shared that with them earlier on in their lives so they really understand the magnitude of that. So when I think about ah their the introduction that they have as it relates to Bitcoin, blockchain, and AI, I mean, what responsibility and how should they be looking at that to better themselves, to put themselves in the best position when they enter corporate America, whether that's within public accounting, whether that's for Fortune 100,
00:09:19
Speaker
I mean, what's their responsibility? What what can they do? Yeah. And... I would say that that point you made, Chris, is an excellent one, right? that That obviously, you know, educators play a big role in trying to help students get ready after their hired corporations have all kinds of onboarding programs, training programs, all the rest.
00:09:40
Speaker
But it's really on the individual to sort of be proactive, right? And to go out there and to be curious and to ask questions and to make mistakes, hopefully earlier on, but to, you know, but to have that be part of their own career arc.
00:09:55
Speaker
And so i always try to encourage any student, right, undergrad, graduate, MBA level, that all of you are going to be sort of expected to have at least a basic knowledge and a conversational you knowledge.
00:10:13
Speaker
around items like blockchain, crypto assets, and AI, right? No one's gonna hire you as a staff or ah a senior and then have this expectation that ah coming in, you know everything, right?
00:10:27
Speaker
But everybody is going to, at the very least, have to understand how these tools work at a basic level, overview level, but more importantly, be able to interpret that understanding to help external clients understand, are these tools going to work for them?
00:10:46
Speaker
And two, if yes, now, right, how do we implement it? What the pros and cons, upsides, and ultimately costs of actually doing this? So it's really more, okay, yeah you you know, you are going to have to understand these tools, but ultimately, how do we take our knowledge and help our clients make better business choices?
00:11:05
Speaker
Because ultimately, as a CPA in any capacity, helping your client to make better business choices is the value add.
00:11:14
Speaker
You know, when I think about how we evolve within a profession and an experienced hire, don't want them to think, i don't want experienced hires to think they're off the hook. you know, because believe it or not I took an a I took an AI course this past year and I felt that I needed it. And it was a very in-depth course. And I hadn't been to school in years. I know I know you will look at me. Folks will look at me and say, well, Chris, we're always learning. Absolutely. We are always learning. But when you're trying to learn it at my ah age and where I'm at in my my career, it's it's different.
00:11:47
Speaker
OK, and I felt that I needed to know more about AI and to the point that you're making. I have conversations with my clients all the time and we're talking about what solutions look like for for them from an advisory perspective, because sometimes we get confused with folks that are coming up and through with an accounting degree. And we think that maybe they're only going to do debits and credits and audit and tax. And now you need to have an understanding.
00:12:12
Speaker
ah The advisory component of how can I help my client if they have a need and where do I see the opportunity when I'm making recommendations? So I'm happy I took it. But when it comes to experienced tires, what do you share with them? What do you recommend for them so they can get up to speed?
00:12:29
Speaker
I did take a course and it was about, think about two months that I was involved in this course, which was great. as a certification process. But what do you recommend? Yeah, so that's a very...
00:12:41
Speaker
important question, Chris, right? Because obviously people who have more experience in the workforce also tend to be the people who are at that partner level or on the client side, own the firm, own the business and have been doing this for X number of years and it's all worked out well yeah so far. but you know, the, the whole way that but try to frame this, right.
00:13:04
Speaker
Is that AI is everywhere but and, and, uh, for honing in on AI, right? AI is already everywhere. it's It's in your Amazon app.
00:13:16
Speaker
It's on your TV. Netflix uses it. Amazon Prime uses it. Uber Eats has AI integrated into its operations. And so even if you might not be terribly interested in it, might not really want to do it ah from a you business continuity point of view, you are going to have to.
00:13:36
Speaker
right but Because if everybody else in your industry, in your field, be it tax and advisory or any other business, is integrating AI, hiring people who have that base level knowledge in AI, and you aren't, all that's doing isn't hurting you.
00:13:54
Speaker
Because ultimately, if you're at that level, at the shortener level, right firm your main job is to bring in business. And... Everyone's hearing about AI, right?
00:14:06
Speaker
Open AI, Microsoft, Apple's new iPhone has AI in it. Everyone's hearing about it. And if the only people they aren't hearing about it from is you, that's a problem.
00:14:19
Speaker
So I would try to pitch it that way. Not so much saying that, yeah, even though you have 28 years of experience, you have to go to school. I try to frame it as, yes, you have experience. That's great. it's It's all working.
00:14:33
Speaker
And then adding in this one component on top of all that can help you build the business, sell the business, and ultimately have the business be healthier going forward.
00:14:44
Speaker
It's not so much focusing on the applications or the actual tools themselves, because you can always hire folks for that if you're smart. ah But really try to understand that tool and how it's going to help the business going forward.
00:14:58
Speaker
You know, I was thinking about all of those organizations that are going through a transformational exercise. And it seems like everybody's going through some kind of a transformational exercise, whether you're a public accounting firm, you know, small, medium, large, whether you're an industry, you know, Fortune 100, Fortune 5000.
00:15:14
Speaker
They're all going through something right now as it relates to just digital and transformation and getting more technologically sound as it relates to their business. How important ah is it that I not sweep this under the rug?
00:15:28
Speaker
Because when you hear some small organizations, they are like, well, you know, I'm a mom and pop shop or small. You know, we are not even at 50 million. We're not even at 20 million.
00:15:39
Speaker
Why would I be concerned about this? Why should they be concerned about it? Are they missing something? Are they going to be that far behind? i mean, what are your thoughts? Yeah. And I mean, obviously, Chris, for every business, you aren't going to need A, right? If if you're running a series of or or a chain of auto body shops, AI might not be what you want to ah invest in too much.
00:16:06
Speaker
But on the other hand, and so here's where always try to sort of hold the conversation. Okay, great. You know, if but if ah talking to somebody, they have 10 storefronts.
00:16:19
Speaker
So AI might not be the best fit for them, but is there anything else out there in this ah tripod of ah tools?
00:16:30
Speaker
Blockchain, crypto, and AI. Blockchain might help, but it's costly and it isn't always the best fit. AI, i can integrate ChatGPT to help me to we draft up some outreach materials, marketing, fine.
00:16:46
Speaker
Automate some emails, you know postings on social media, great. But is there anything else out there that is growing in popularity, that's growing in popularity in that 18 to 45 age cohort and is also becoming widely available on a tool that pretty much every entrepreneur has?
00:17:08
Speaker
Yes, crypto payments, right? PayPal, a household named 400 million customers as their own token allows merchants and individuals to buy, sell, and hold crypto via PayPal. sort of you know if That's the main angle that i always try to take.
00:17:26
Speaker
Sure, ai it's interesting, might not work for you right now. But is there anything else out there that, if you integrate it, could bring in new customers, new business, and again, ultimately, have you be sort of set up better going forward?
00:17:44
Speaker
You know, something that comes to mind, and I think we chatted about this not too long ago, and I look at the accounting profession and the transformation that's going on right now.
Digital Transformation in Accounting
00:17:53
Speaker
I mean, the business is changing and I, you know, and I'm not trying to scare the folks that are out there that are coming into the profession, but it is changing.
00:18:01
Speaker
Why is it changing the way that it is? Because the way I see it and, ah you know I've been a partner in a firm. I function at a very high level. I've been a manager, you know, working my way up and through the ranks. But it is a different business now, especially from a consulting perspective and how they deliver various solutions. It could be audit. It could be tax. Why is there so much change right now? And and for me, it looks a little bit like it's confusing.
00:18:26
Speaker
Not only to my eyes, but to the general population as to what's going on within the profession. So what are your thoughts? Well, so how much time do we have, Chris? ah but No, but I mean, absolutely, right? The whole accounting field is in has been in the midst of, I think, a real fundamental change in how firms operate, how people are hired, and then how those hires move up during during their career arc.
00:18:52
Speaker
And there are sort of three big big picture trends. One is this pivot from billable hours to more value billing, value pricing, which is a whole other conversation, super important to have, but sort of that's a big one too.
00:19:07
Speaker
And then you in that bubble, there's the hours, busy season, work-life balance, work from home is all in there. who is the pipeline issue, right? Any conference, any podcast about accounting has to bring up has to bring up this this this pipeline issue.
00:19:24
Speaker
And then three, there is this growing, I think, perception and idea that sort of two of the pillars of CPA work, taxes and audit, one, are able to be done more and more by non-CPAs.
00:19:44
Speaker
And two, that is in large part due to automation. So all of those big, huge trends, right? so So you have pricing pressure, sure you have employee pressure, and you have a market image pressure.
00:19:57
Speaker
And all of those things are hitting all at once. And so, yeah, it it really has been quite a, um how do I put this, interesting last sort of 10 or 12 years.
00:20:10
Speaker
And honestly, I don't think it's going to calm down ah anytime soon. You know, i when I think about public accounting right now and I'm thinking about the human capital element of it, i and I know, can I do more with less? Because you hear about AI and you look you hear about what's coming and and what it means for me. I'm not billing as many hours. If I'm going through and doing a planning exercise,
00:20:35
Speaker
And AI is helping facilitate that. Then it doesn't take as many hours. So it's changing up my my business model a bit. You know, do I need more seniors or need more managers? Do I need less partners?
00:20:46
Speaker
You know, I think I think the industry from a public accounting perspective is going through. Something is very different than they've experienced in the past. Not to say that they won't figure it out. I see what's happening. Some of the larger firms obviously are partnering with ChatGPT and others that try and come up with strategy and and be unique ah in the market. So when you when you process, when when you're listening to what I'm saying,
00:21:11
Speaker
I mean, what's coming to mind for you? Because I know you're embedded in a different way as well. And you're delivering curriculum and you've got students that are tapping you on the shoulder and you see how things are evolving in the business of a accounting.
00:21:24
Speaker
I mean, what what's front and center for you based on what I've shared? Sure. So probably the the sort of one big, big change that is the most obvious sort of output of all of that is that obviously at firms, it was always more of a pyramid shape, right?
00:21:40
Speaker
You hire a lot of first-years interns, Burnham and Churnham, just yeah being honest, you know Burnham and Churnham after you know two, three years. And then over time, they become seniors, managers, senior managers, and then ultimately partners.
00:21:54
Speaker
More and more, I am seeing more org charts, more sort of plans being laid out where it is morphing, not overnight and not immediately and not instantaneously, um a period from a pyramid to more of a diamond shape, right? now That if I can automate, right?
00:22:15
Speaker
Engagement letters, client follow-ups, basic audit testing, tax preparation, tax ah gathering. Journal entries are already automated. So if all of that is automated or mostly automated, I don't have to hire as many first years.
00:22:31
Speaker
And then on the other end, if you have all of these new tools and these resources, new ideas, right, that everybody's interested in. Blockchain, Bitcoin, AI, ES&G, all kinds of other stuff.
00:22:47
Speaker
How easy is that? And but and ah you and I brought this up the other day. How easy are those ideas to transform into new clients and new business at the partner level?
00:23:02
Speaker
So it's been interesting to see that at the the exact same time that everybody from AICPA all the way down is sort of banging on on this pipeline issue, right?
00:23:15
Speaker
You know, need more people in the field tomorrow. At the exact same time that's happening, there are trends that are happening right now in the marketplace that are going to get rid of quite a bit of the work that those first years, newer hires, earlier career folks did.
00:23:35
Speaker
So so of that's going to be, I think, a really interesting i you back and forth, Chris, because obviously this whole pipeline issue took 20, 30 years to yeah manifest itself as a problem.
00:23:49
Speaker
AI has advanced so fast in the last two years. Don't forget, ChatGPT just launched in December of 2022.
00:24:01
Speaker
So it's only been couple years. And it's already transforming businesses, transforming how we're talking about audit engagements, tax returns, advisory services, firm management, human capital.
00:24:15
Speaker
So I think AI is going to eat up quite a bit of that work. And on the other hand, the partner level, if if I can automate more and more of those sort of bigger picture, higher level sort of strategy setting meetings and processes, then how can the partners charge as much?
00:24:33
Speaker
So it's going to be interesting to see how the pipeline and AI sort of back and forth plays out over the sort of medium term. But yeah, I mean, it's it is definitely something that I always talk to, both both people who are in in the field right now working and students, that AI is coming and it is going to augment or automate 30 to 40% of your job, right? That's going to happen.
00:24:58
Speaker
So then how do you deal with that, right? How do you figure out how best to allocate your time, how best to upscale your own knowledge on AI? Because ultimately, and and I've heard this quote in multiple places, that X, be it a CPA, tax lawyer, engineer, architect, X isn't going to be replaced by AI.
00:25:20
Speaker
They're going to be replaced by X, CPA, lawyer, engineer, who understands how to use AI. So, you know, that said, when I think if I'm coming up and through the ranks and I'm in my junior year and I'm working towards my degree in accounting and I'm trying to prepare, you know, over the next two years, I'm going to graduate.
00:25:40
Speaker
How do you get it right in serving up the right dose of curriculum? You know, because I would think you'd have to partner with those that are within industry to make sure that everybody's on the same page. But I've been in in a partner role and I'll say we all we don't always know what we need because we're trying to figure it out. You just made a really good point.
00:25:58
Speaker
that chat GPT, you know, was introduced, you know, a year ago, you know, and now it's created all of this opportunity, you know, within the profession and how we do business. So how do you make sure that they're equipped? How do you make sure, know, because it's got to be a fine line, you know, that you're walking in order to get there. So how, how do you, have you figured that out or how does that work to make sure that you're serving up the right amount of curriculum for that need in the profession?
00:26:24
Speaker
Yeah, so so that's a really good and really but important question, Chris. And I don't think anybody has sort of the answer yet. If they do, please have them call me because I haven't found anybody that has the perfect balance, right? Because on the one hand, right, you know, we all know that AI is automating more and we're doing more of that heavy lifting.
00:26:47
Speaker
But I always try to really highlight this point to my students because I know that everybody is... I think AI helped them, right? In the classroom and whatever, that's fine.
00:26:58
Speaker
I would do the exact same thing to be honest. But if you're ah a client, if you're in a meeting on the call and you're being billed out at $1,000 per hour, that client isn't gonna wanna see you asking chat GPT for everything, right?
00:27:16
Speaker
So on the one hand, we we have to integrate AI, right? Cause it's happening, automation is here, but also at the same time, We in a educator role, right, be it in a college or in the workforce, have to make sure that our students, be they college students or staff, still have sort of that that base level knowledge, be it around ASU, be it around tax changes, be it around policy changes or the industry.
00:27:42
Speaker
itself because AI is not perfect and it is not always complete. So that's that's always something that I always try to really highlight because I'm somebody, budd got my CPA, went undergrad, accounting, bolt-on master's degree to get to 150, the CPA examined after an 18-month period of just you know ah intense work, that it and then yeah worked and all the rest. But But then I had to pivot too. And everybody in the workforce right now had that exact same thing happen to them.
00:28:19
Speaker
and After doing everything sort of the right way in the workforce, then all of a sudden you have Bitcoin, you have AI coming in from everywhere else. And so the angle that I always try to take is embrace the the tools, but understand that as powerful as they are, they are tools.
00:28:38
Speaker
And that you have to know how to use them, how to interpret that data, and then how to, most importantly, ah sort of translate those outputs into ideas and business steps that our clients can actually understand.
00:28:53
Speaker
You know, I'm thinking about transformation within public accounting and the firms and how we go about delivering solutions, audit tax, as well as operationally, you know, what the business model looks like and human capital equation.
00:29:06
Speaker
You know, we forget that our clients aren't they're doing the same thing. You know, they're using AI as a solution. So they're solving some of their own problems. They're hiring their own folks. So, you know, I know we may not think of it this way, but the opportunity is shrinking.
00:29:21
Speaker
I would think, you know, from an advisory perspective, if I'm getting better and smarter, I may need invite you in to help me out with some things. But. I think I'll have tools and resources to help me figure it out in a different way. There's always a tactical ah you know ah element of it and you know that we can't forget. But and what are your thoughts when you think about how both are maturing?
00:29:41
Speaker
you know How does that change change opportunity across the board? I mean, within within our profession. Yeah, so but obviously would say there, Chris, is that so I have this optimistic answer that I was lead with.
00:29:57
Speaker
And then after that, I follow up with more realistic answers. So optimistically, you know, all of us have been hearing for the last 20, 30 years that we as CPAs have to move out of being a compliance role to being that trusted business partner or the trusted business ah advisor.
00:30:15
Speaker
And now we actually have tools that'll help alleviate some of that lower level workload to allow us to actually do that. Okay, so that's the optimistic answer. So on a more sort of practical basis, right?
00:30:27
Speaker
You know, we have to become, I think, more business oriented. And I'm going to clarify that, that for a long time, accounting and law and engineering and any of those types of practices have kind of operated in a bubble, right?
00:30:44
Speaker
That our whole pitch was that, you know, we come in, bring the expertise, right, around tax, audit, or implementation solutions. We're the experts.
00:30:55
Speaker
You come to us for that. But our clients are out there in the workplace, in the quote unquote real world, doing in business every day, implementing AI, trying out trying out real payment options on an everyday basis.
00:31:12
Speaker
So then we have to come in and say, okay, great. you know That's a great introductory level. How do we amplify that? do we turn that up? How do we accelerate but changing your business? And An important caveat that I always have to point out is that if I have a client, let's say they do marketing. Actually, anecdotally, I have some friends of mine who run a marketing agency and was having conversations with them last year.
00:31:42
Speaker
And, you know, they were integrating AI, allowing clients to pay them in crypto. And was like, guys, that's that's great. Everybody else in your field is doing that exact same thing right now.
00:31:55
Speaker
So how do we amplify that implementation? How do we ah accelerate your adoption of it? And also, how do we make sure that all but that is happening without tripping you up on the back end, right? Because AI has no rules for audit, data privacy, compliance.
00:32:16
Speaker
There aren't any rules yet. Crypto is... much better now as opposed to 2020, but still has a lot of ambiguity as to how to actually implement these things after after day one.
00:32:30
Speaker
Right, Chris? Because our whole pitch usually in the past had been, okay, we will prep you up to day one and then we'll hand you over the the plan, action steps, and then all of us leave.
00:32:44
Speaker
And then if they have to call us back, we're going to charge you. But now, Everybody has the capacity to get to day one. Our job has to be, okay, after day one, how do we keep this rolling?
00:32:58
Speaker
And that's the real difference, I think.
Risks and Limitations of AI
00:33:01
Speaker
You know, there we've been talking a lot about the pros and the cons, but we haven't spent a lot of time on on the cons. And, you know, when I think about AI and and how quickly we've adopted it and and kind of where it's going, we forget that it's new, you know, new in the sense of we're trying to figure out what the rules are associated with it.
00:33:20
Speaker
So what are some of the risks when we start? And I know generically some of the risks that come into play. We talk about data and some other things, but What's the risk? I mean, we we introduce something to our environment. We're relying on it in a different way. We think it's a right the right source.
00:33:35
Speaker
It's helping us aggregate things in a different way, get to a conclusion in a quicker, faster way. But what's the risk? I think there are some sort of more obvious risks and there are also risks that are only going to be found out for day one, right?
00:33:50
Speaker
So on the surface, there are the obvious risks, you have data privacy, and also you really got to keep in mind that all of these AI tools long belong to somebody else, right?
00:34:01
Speaker
There is no open source AI magic, right? They're all applications, usually out of a large established company. So, those gotta keep that in mind. um Training, I know there have been cases where anecdotally interns, and i always hate to pick on interns, but they have tended to be the individuals that'll be on Instagram We're TikTok filming a video at work and then accidentally, you know, post confidential data on the social media.
00:34:31
Speaker
That's also happening with ah with AI. But then after those obvious risks, right, how do we know how good the output is out of the AI?
00:34:43
Speaker
And by good, they mean accurate, complete, and unbiased. There have been cases where AI programs have been implemented primarily in healthcare and the of ah cases and then credit granting cases where they've fed this AI, right?
00:35:03
Speaker
Off the shelf, brand new AI program, all sound bells and whistles. They've uploaded data and then the outputs of that AI were incredibly biased.
00:35:16
Speaker
either for some people, for some customers, or against some people. And so that's a really critical thing, ah especially, Chris, if you have a client that operates in a diverse area.
00:35:31
Speaker
I'm from New Jersey. Jersey obviously a diverse state, and it's all and it's all better for it. But... If you're using AI for client outreach, client management, and you don't take into account cultural differences, language differences, that could easily trip you up and really aggravate people too.
00:35:52
Speaker
And then after all of that, you have to also keep in mind that these AI programs are just that, programs, right? And that over time, that there are going to be patches, there are going to be updates, there are going to be outages,
00:36:07
Speaker
So then how do you integrate plans, again, post day one, to make sure that on a business continuity point of view, your operations are still up and running as usual and your clients never notice?
00:36:20
Speaker
And so those are two big, big risks that are that are kind of being talked about, but aren't being talked about to the level that I think they should be. You know, when I think about AI and I think this audience probably didn't know it's it's it's it's compiled machine language and instruction. Could you go into that a little bit just to give us that background and understanding that we're stacking and stacking languages here and trying to evolve? And it's very complicated, but that creates a lot of the risk as well, the way that that actually works. So if you wouldn't mind sharing, that'd be fantastic.
00:36:56
Speaker
Yeah, so so so d depending on the tool, right, it's supposed to operate just a bit differently. But overall, the sort of AI bots that all of us are talking about and using, they're all just large language models.
00:37:09
Speaker
And sort of, okay, fine. What does that mean? Well, basically, that means that they are algorithms that implement ah machine learning.
00:37:20
Speaker
What's that? That is basically where I will have an algorithm at a base level. So for instance, if you're playing a video game or any sport or karate, you have the white belt and go from there.
00:37:34
Speaker
So you have this model or this algorithm and you train it with examples, data, and you train it on millions and millions of examples, billions of examples.
00:37:46
Speaker
That's the machine learning part. Then after that, there's the deep learning part. And I'm being sort of basic here, right? So that's the machine learning, doing the examples. of This word means this, this picture means this word, this word follows this word 80, 83% of the time.
00:38:05
Speaker
And then after that, deep learning is possible. Meaning then i can ask or I can prompt this this protocol a a question and then it can answer me based on the learning that it already happened.
00:38:20
Speaker
Then it's also integrated with a type of AI called natural language processing. And anybody that has Gmail on their phone probably has noticed that as you're typing, Gmail will start to autofill options for you.
00:38:37
Speaker
That is natural language processing. And so combining all three of those is why now AI seems to be human, seems to be intuitive intuitive.
00:38:49
Speaker
and and is able to answer questions and to make jokes and all the rest. But if you really boil it down, all of that is math ah is math being ah ah plot.
00:39:04
Speaker
Basically, these models, based on your prompt and the words you use and the criteria you give it, these models are basically running billions of options and then putting out what mathematically is the right order of words or images based on your prompt.
00:39:26
Speaker
And so that's why there are cases where AI will just hallucinate, you know create fake data to answer your prompt. And it's also why the the art aspect of AI isn't quite there yet, right?
00:39:40
Speaker
but right Because all of the data that it's been trained on or the vast majority of it to date is is text-based. And so that's why the art aspect of it or the imaging aspect of it, now it is a lot better now, but all of that has been much, much more paced out as opposed to the prompt angle of it.
00:40:03
Speaker
Awesome. Awesome. You know, and and as we can get to the point where we're going to wrap up our conversation today, I'm thinking about that one takeaway.
Adapting to Technological Change
00:40:11
Speaker
You know, you you're speaking to accounting professionals, finance professionals, folks that are trying to figure out what their next steps are as it relates to their careers.
00:40:22
Speaker
They hear about. you know, the blockchains, they hear about Bitcoin, they hear about AI and they're saying, well, hey, that's going to drastically change what I need to know, how I operate, you know, how I'm going to do business. I'm a senior associate within a firm and they're introducing new tools and saying, hey, your job's going to look different.
00:40:39
Speaker
I mean, what's that one takeaway? Because I would think people are a bit confused. yep They're anxious. They're afraid, you know, about what's to come. I mean, what's your what's your one takeaway for them for them?
00:40:55
Speaker
What I would say here, Chris, is that yes, all of that is true, right? That these tools are confusing, they're anxiety inducing, trust me. I mean, I'm in this space every day and I'm learning new things constantly, but that's the main thing, right?
00:41:12
Speaker
And that all of these tools are gonna change tasks, right? They are gonna change jobs. There are gonna be some jobs that are more important, less important, that happens. But all of that has already happened before.
00:41:26
Speaker
Typewriters to word processors, landlines to Wi-Fi, in the office, work from home, ah bring your own device, cloud computing, data analytics, big data, business intelligence.
00:41:40
Speaker
all All of these changes have already come. And yeah, every iteration of technology does change the work.
00:41:52
Speaker
And so the concept or sort of the main point here that I always try to hone in on is all of these tools are tools and they're as powerful or they're as harmful as the as to people using them.
00:42:06
Speaker
And so that's the mindset that I always try to go into. And then one a is that our role has always been to help our clients.
00:42:17
Speaker
and to Be our clients, be students or be external clients or the you know partner down the hall. Our job has always been to help clients. And now these tools are just making it more obvious, right? That it's harder now to hide behind being the audit guy, being the tax person, you know being the yeah ERP expert.
00:42:41
Speaker
Now we have to go, as I was saying earlier, past asked that day one. endpoints and to really help our clients integrate and grow over time as these tools evolve over time also.
00:42:57
Speaker
You know, it's been a pleasure talking with
Conclusion and Future Growth
00:42:59
Speaker
you today. You know, the time has truly passed quickly. ah We just barely touched on blockchain and Bitcoin. And I hope that you come back and have a continue to have more conversations with us because I think this is very interesting. um The world is changing rapidly.
00:43:15
Speaker
yeah Okay. The next three years are going to be incredible. Yeah. You know, i'm I'm buckled in and ready for the ride. But all I can share I'm going to look into the camera and share this with audience. Obviously, thank you for being a part of this. But I want this audience to understand that there's nothing to be afraid of.
00:43:32
Speaker
It's all opportunity. ah Dr. Smith's expressed that this is nothing that hasn't happened before. Okay, this is going to make us better. It's going to make us go deeper.
00:43:42
Speaker
We can't be siloed in how we work and how we operate going forward. It's drastically changing business every single day. If you are unfamiliar With any of this, do the research, take a class, become certified, because there's plenty of opportunity out there and plenty of courses that are being offered.
00:44:03
Speaker
I took a course this past year, which was different for me, but I learned a tremendous amount about AI and some other subjects as well. So don't don't be afraid, embrace it.
00:44:15
Speaker
And I look forward to seeing you on a future conversations on Balancing the Future.