Is your organization adopting AI — or just chasing it? On this episode of Tomorrowist, host Jerry Won speaks with Arturo Ferreira, Cofounder of The AI Report, to unpack where enterprise AI adoption often goes wrong — and how leaders can get it right. From reinvesting time saved through automation to navigating the “AI arms race” with purpose and discipline, this conversation breaks down what business leaders need to know about AI transformation, and what’s coming next. In this episode, you’ll learn: - Why Ferreira advises leaders to “move slow to move fast” with AI adoption - How disciplined integration creates long-term organizational value - Which business functions are most primed for AI disruption - His predictions for the evolving role of HR in an AI-driven future, and more
Is your organization adopting AI — or just chasing it?
On this episode of Tomorrowist, host Jerry Won speaks with Arturo Ferreira, Cofounder of The AI Report, to unpack where enterprise AI adoption often goes wrong — and how leaders can get it right. From reinvesting time saved through automation to navigating the “AI arms race” with purpose and discipline, this conversation breaks down what business leaders need to know about AI transformation, and what’s coming next.
In this episode, you’ll learn:
Resources from this week’s episode –
Register for Arturo Ferreira’s sessions at SHRM25: https://registration.events.shrm.org/flow/shrm/shrm25/public-catalog/page/catalog/session/1744919954572001ZpXQ
https://registration.events.shrm.org/flow/shrm/shrm25/public-catalog/page/catalog/session/1744833025741001XiDO
Subscribe to Tomorrowist to get the latest episodes, expert insights, and additional resources delivered straight to your inbox: https://shrm.co/voegyz
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Jerry: I'm Jerry Won and welcome to this week's episode of Tomorrowist AI is here. We see it in the news. We see it in our daily lives. We see it all over social. I. What we haven't quite figured out as business leaders is how the intersection of AI plays into the enterprise role.
How are businesses adopting ai? What should they be concerned about? What should they be preparing for? According to a new internal SHRM report, 90% of CHROs foresee AI integration becoming more prevalent in the workplace this year, making AI the most prominent workforce trend that CHS expect to gain momentum in 2025.[00:01:00]
Many companies are still trying to figure out how to use AI and what to be mindful of, uh, as they think to deliver real impact without the disruption. and To help us navigate this wonderful and timely question in conversation, we have Arturo Ferreira here.
He's the founder of the AI Report, a wonderful platform that is teaching hundreds of thousands of business leaders across the world, how AI can impact the work, and also make us more efficient. And he will be also be speaking at SHRM 25. And so we're super excited to have the AI expert with us today.
Arturo, welcome to Tomorrowist.
Arturo: Thank you, Jerry. It's really good to be here. I always love being, uh, around the crowd, man. It's, it's a phenomenal group of people.
Jerry: You know, before we get started, I have to say on your LinkedIn profile, the first thing is exhausted, father of three. And so, uh, shout out to you, uh, and to everybody else bringing their authentic selves to the workplace, whether it's in the digital format or not. And, um, it, it is a, a wonderful, um, time to be sharing this conversation with you on something that really has been on my mind.
You know, as a speaker, as a host, you know, how much of [00:02:00] the AI do we use, how do we not, and I think a lot of the conversations around AI has really been around individual usage, right? How are people using it to be more creative? uh, the audience here is mostly business leaders. And so let's talk about sort of the intersection of that. Um, AI and the AI adoption in enterprise world, uh, has been reaching a tipping point, and AI has evolved and grown, uh, more quickly, uh, over the last year and over and over again.
What factors have driven this acceleration and why are so many organizations embracing AI now, uh, compared to even 18 months ago?
Arturo: It's a good question, and I think one that's rooted less in technology and more in just the human condition, right? I think As more companies start to talk about the AI they're integrating and the productivity and the, and the scalability and all these buzzwords that we're hearing, more and more people start feeling behind the eight ball, you start feeling that, that that rising anxiety of fomo. So what we're seeing right now is this kind of like AI arms race to a certain extent where companies [00:03:00] wanna be, first we want to AI and we want to use it as a verb, it's not an ideal position to be in. You know, about a few days ago, pat oppe, the Chief Information Security Officer, JP Morgan Chase, released an open letter to, well, the financial industry, but really any business owner as a whole, functionally saying that AI adoption was outpacing its capability to integrate. And the best metaphor that I'm giving you kind of a lead into one of my new videos coming out is just. Picture, you have these two impregnable fortresses, right? And no one can attack you there, but who's guarding the road that connects the two places?
Jerry: Hmm.
Arturo: I think there's a lot of driver behind the, the logic behind the driver is the same logic behind our, you know, our markets.
It's the illogical human mind driving the logic of a massive human run system. So it's an interesting point right now that I think connects to the greater observation that I've made in the last few years where the conversation around generative ai. Specifically is significantly less about the technology, although that's important, a lot around the social, cultural, and even [00:04:00] philosophical implications of this civilization changing technology.
Jerry: That's wonderful. Let's, let's a step back and, and sort of define some things that maybe you and I and other folks have taken for granted in terms of our, our familiarity with terms, um, ai, obviously artificial intelligence. When we talk about the integration of AI and particularly generative ai, I. What are some of the capabilities that it is capable of that we've seen?
What are people working on that we hope to make it capable of doing and being as it relates to its business function of making businesses more adaptable, more efficient, so on and so forth.
Arturo: So I think the, the biggest advantage it gives is that it starts to take over the lower order cognitive tasks that we're accustomed to doing. reports, idea iteration, that kind of thing. We can move at the speed of thought. And it's pretty exciting. thing that it requires though, is additional critical thinking.
So, you know, I've, I've been in a reversed seat from you where I've hosted multiple guests on our podcast. One of them was Dr. Samson. If any of our [00:05:00] audience has taken my A IHI specialty credential, um, you've heard me talk about this story, but I ask all of our guests, what do you say to people that are afraid of being replaced? And Dr. Simon, the author of The Singularity of Hope. Astutely says, you know, AI isn't gonna take any jobs. It's gonna do the jobs it was always meant to do. The problem is we've spent so much time teaching people to think like machines. So as we see AI start to take these lower order ideas and start to move into more higher order critical thinking, that needs to translate into our usage because ai, the term hallucination, I think is a misnomer. Hallucination is implies that something is wrong, but hallucination is wrong. From our perspective, the AI is doing what it was designed to do. It is generating something wholly new from content. It was trained on and from the Quest request made of it. So when we look at it from that perspective, our job is less about trying to interact with something smart and more just trying to wrangle a probability engine to give us something useful. where tasks like reports or emails or projects would've taken us [00:06:00] days or weeks once we might be able to do most of that now in minutes or hours at most. The difference is where that old project that took us one week to complete, you know, we'd finish and be like, all right, I spent an hour reviewing it.
I'll send it out. Now we finish it in minutes. Now we probably take a whole work day to review it. It's still a net gain on a massive scale, but it's a significant psychological and cultural shift in where our work actually lies. I.
Jerry: Sure. I, I think, you know, the conversation around AI is parallel to the conversation on productivity, which is something that we've had a lot over the last few decades in terms of, are we as, as a species, more productive? I. Can we be more productive per our output? Of course we are, right? 'cause technology allows us to do that.
And so for one of the questions that enterprise leaders have to think about is what are we gonna do with the time that we've earned, that we've gained, perhaps investments in whether, whatever that investment used to be in, whether it is, you know, human labor or another things, what are we gonna do with that, right?
And so these are questions that every business leader [00:07:00] has to think about and also be prepared to answer. Um. You know, we, you've demonstrated, and I think we all know by now, that the potential benefits of ai, both for individual contributors and enterprises are quite clear. Uh, the, the part that's not as clear is the implementation, uh, to get it right and to do it and roll it out in a way that is well received, but also getting it, you know, without making mistakes on it.
So what, what are the key challenges that organizations face when adopting AI at an enterprise level? Uh, particularly for something that. Evolve so quickly where we see new versions of, you know, the most common AI tool that we're all familiar with is chat, GPT, and it seems like every few weeks there's a new version that's x times better, y times faster.
How do you, how do, uh, you know, uh, leaders think about the adoption and the challenges related to that?
Arturo: It, it's discipline. It, it really is leading from the front and kind of setting the standard of how fast we move. You can't let yourself get caught up in the current of you gotta, you're, you're running behind, you're, you, you, you as a leader need to take a [00:08:00] step back, take a breath and say, we've got this, and do the work that it takes to really move slowly.
So one of the things, um, that we do, so we have, you know, you, you're familiar with the AI report. Our enterprise side is called upscale. And one of the things that we do is we guide companies through automation processes and we'll go in and, you know, we can teach people to do this. We go in and we'll kind of help people understand where processes can be automated, where you need a human in the loop and what you shouldn't touch, because the technology might be different in six months or six
Jerry: All
right.
Arturo: But moving to quickly is the same thing that happened during the.com bubble. Everybody wanted to.com themselves to a 74% stock boost, and we all saw how that ended. The smartest ways to engage with AI is twofold. One, start from the problem and work your way backwards, right? And usually it's where is your data or where your time sinks. Find those spots and try to work back. And then the other one is just upskill your people. you're right, technology is changing very quickly, but the fundamentals really don't. [00:09:00] Yes, we've had multiple iterations of ChatGPT more powerful, a little smarter. But The fundamental engagement method with it, the idea of understanding that it's a probability engine and not an actual thinking machine, is a big one. So understanding the fundamentals and helping people come along slowly and, start to own their time to be critical thinkers again, I think will pay outsized dividends in the coming three to five years.
Jerry: As you mentioned, there's a lot of fomo or fear of missing out around AI as it's being talked about constantly. Right. Um, what, what are some mistakes that you've seen, uh, business leaders make in adopting things too quickly? As you mentioned, you know, discipline of sort of holding back, um, and, and what, you know, how do you balance that?
Right. Where do you take action and then where do you stand back, uh, in, in the effort to avoid mistakes that others have made, uh, in both, you know, in, in the business enterprise adoption of ai.
Arturo: I, I think what I, the mistakes I've seen are less relevant than the mistakes we've all seen, right? So we've all had an [00:10:00] experience where a company has this new shiny HRIS system or this amazing new onboarding tool that isn't really well communicated. Or maybe the, the. Training is lacking or number of factors aren't in place.
And sure it doesn't fail, but then you have the death by delay, where full implementation takes two, three years because people just don't use it because humans are uniquely bad at doing something different when they do something that already works. Right. And that's normal. I do it. You know, to your point, I'm an exhausted father of three.
Like I don't have a whole lot of time to start trying new things. So when we face these new challenges, it really is a matter of move slow to. To, to, to move fast, right? Slow is steady. Steady is fast as the saying goes. we wanna really find the low hanging fruit. To give you the example that we use and that I recommend all companies use when we start like working with their automation systems. We rank projects on a scale that ranks. Impact to the company and
Jerry: Hmm.
Arturo: or feasibility to implement. [00:11:00] And we always weigh feasibility because feasibility often means, oh yeah, we can automate your Google reviews or, sure, we can easily automate. When a project comes in, then it goes into Dropbox, your codes are found, then it goes to project manager. Those are straightforward things that can be done with modern technology, right? The things that we have right
Jerry: All right.
Arturo: the sooner you can implement and the simpler the implementation, the greater the ROI you start to produce now. Anything overly complex, anything that's super whizzbang, I, I don't, I don't see that if, if you're already looking at a month style scale to even implement a pilot, you, you may already be behind the eight ball.
Jerry: Let's talk about some of the characteristics on the other side of, of people who've done this right, or organizations who've who embrace AI in a, in a thoughtful and successful way. Um, what characteristics do those companies who've done it successfully integrating ai? I. What do they have in common? Um, and, and why is it important for enterprise leaders to treat AI as business transformation rather than just technology that can be plugged into an existing system?
Um, [00:12:00] and, and what does that difference look like in, in reality versus just a thought?
Arturo: So it's easy to point to the large scale companies, right? The AWSs, the Googles, the, you know, um, Cignas of all these brilliant ideas that they've done. But it's easy to point to 'em 'cause they have that. Infinite money glitch for the
Jerry: Right.
Arturo: right? They can. They can throw a ton of money at the problem when we took it, when we look at midsize businesses, most of what you and I will operate in day to day, that have done it right have moved slowly and deliberately. You start with a problem and you work your way out. 'cause if you find those low hanging fruits, if you find those immediate problems. Which might very well be just upskilling your people to use chat GPT and buy back 30 minutes a day, buy
Jerry: Hmm.
Arturo: minutes a day, right? That, that, that adds up over time. if you look at those companies, you're gonna see outsize impact both from productivity and from a morale standpoint. That morale translates to more curiosity around wait. What else can I do with this? Because the beauty of generative AI is it's the first [00:13:00] technology that doesn't need to be spoken to, like it's technology, and it, by moving at the speed of thought, the fact that anybody can go in and say, write me code for this, for to do something on my website, and it'll give you the code and Python, it, it, it makes it pretty exceptional. So if we no longer need to specialize in highly specific technological things, what can your frontline people do? To to, to give you an anecdote on this, I've done two dozen calls in the last month with companies looking to do audit AI audits with us, and without a doubt, the four people that have told me, I actually tried to make my own agent to do X, but I got a little complicated.
It did this, but it didn't like they actually tried and iterate it. All four of them worked in the trades. And I think that's interesting because you have this idea of already someone who presumably hasn't necessarily gone through a traditional system of education who's forced to be kind of more in the hustle culture of like, what do I need to learn?
How do [00:14:00] I do this? How do I eat what I kill, essentially? And you have this whole different mentality of pursuing this technology. That doesn't need to be spoken to in this high level way.
Jerry: Hmm,
Arturo: that's a long answer. To simply say that I think engendering and empowering your people to, to make initial mistakes will have an outsize impact in the long term.
As you start to let AI proliferate, I think the biggest mistake you can make is a blanket know, because then people are just gonna
Jerry: Hmm.
Arturo: and use it incorrectly, and that's the
Jerry: All. It's not binary whether we use AI or not, you know, which seems like the, the, the pressure from the world and the media, right? You gotta have ai. You gotta have ai. The nuance here is that as you integrate AI into your business practices, different departments and different functions are gonna adopt it more quickly or at a larger intensity.
Then some other ones, like you said, there are some functions that probably shouldn't adopt AI now or if at all, based on sort of what, what it requires. Um, some of the things that we've heard are HR or HR or customer service, [00:15:00] where it's a lot of, you know, um, a, a learning set answering question and answering type of a format.
Um, what business functions are most right for AI disruption, in your opinion or HR and customer service? The first that should be, uh, using it at scale.
Arturo: It's a good question. Um. HR, I agree with, with a caveat that by necessity, HR is a human facing organization. Now you can automate HR processes, think HR touches some of the most important keystones that AI will touch and I see actually see a different new and outsized role for HR
Jerry: Hmm.
Arturo: AI future customer service.
It's a frontline tool. But if I want to be serviced and I have an actual problem, I need to have a way of escalating. So once again, we see that higher order thing. I see the biggest use cases is really just knowledge work data, right? Anything that requires data processing, pattern prediction, [00:16:00] predictive analytics, it's designed for that. Generative AI can extrapolate faster than you and I can literally even think, and that's where we're going to see all these really interesting new things. Now, it's uniquely bad at tasks requiring precision, so.
Jerry: Hmm.
Arturo: engineering,
Jerry: Alright.
Arturo: anything that's commercially available that that isn't specifically trained to do a task will be a decent generalist, but not very good at any specificity.
And I'm sure our audience has seen that when trying to create a specific photo in chat GPT, or asking it to give you a breakdown of something. when it comes to functions, I would say anything involving knowledge and data in the same way that, you know, we don't need to like. a family member to ask for directions to get somewhere.
Now we just go on Google maps. AI is going to do that for us General, just in general knowledge alone.
Jerry: Let's take a look at the adoption from a different lens. We've talked about functions within organizations, but what about the other verticals of industries? [00:17:00] Are there particular industries that should be leaning more into this? And are there some industries, in your opinion, who should take their time to make sure that the technology or the circumstances are more, uh, ideal or optimal before they jump into, uh, putting AI integration into their business?
Arturo: Yeah, this is. Strictly, in my opinion, from just being around it. Right. Um, I, I, I see. AI as an industry agnostic tool, right? It's less of a light bulb and more of electricity. You know, I think it can shape the way we all interact because you think of businesses as you know, same pattern, different shape.
Sure. Commercial construction isn't healthcare, but. If they have accounting, they have onboarding,
Jerry: Yeah.
Arturo: need to hire people, right? There are processes within all businesses that can benefit from automation, that can benefit from a tool that can analyze process, and interpret data quickly. If I had to pick an industry that I think needs to move extremely slowly, it would be the finance [00:18:00] sector, which is ironic considering all the money being thrown at AI right now. But when you're talking about. second and third order effects in the event of a data breach or in the event of an error, a rounding error. What that can do, it, it, it's, it's a pretty significant way, uh, to, to look at things. So I would say moving with co I mean, it seems to me that that would be even worse than medical data leaking.
'cause Yes. Is it ideal that people's private information is leaked? No, not at all. In no world is that okay. But that's preferable to. people's life savings being wiped out in an
Jerry: All right.
Arturo: because someone made a mistake and didn't close the back door, or there's a zero day flaw that wasn't caught in time. out of all them, I would say finance should probably move the slowest, uh, certainly defense, but that's a whole other topic
Jerry: as consumers and both business leaders, we engage with AI knowingly or unknowingly, which is the world of marketing, right? People are now asking AI for recommendations or.
Uh, more than Googling as we used to, [00:19:00] or as we know, go to the search engine, we go to AI and we go to chat GBT and saying, Hey, what are the best, you know, who's the best newsletter to follow in the AI space? Right? And hopefully they say it's it's Arturo's newsletter. Um, how should business leaders be thinking about that from a traditional sense, transitioning from what they used to invest in content in, you know, in SEO, uh, those are some of the conversations that I have with my business friends a lot where it's, Hey, I don't Google anymore.
Arturo: Right.
Jerry: How do we become relevant in a, you know, a model that is trained on existing data? What are your thoughts there? And then where are business leaders or where should business leaders be investing in from a marketing perspective to quote unquote rank? I know it's not ranking, but to come up from the AI answer Bank.
Arturo: It's a good question. I think, I think what I'm seeing, um, is a return to the personal connection. very hard because Chatt PT and generative AI as a whole is drawing from existing information. So Chatt PT is going to [00:20:00] look at existing websites that perhaps are paid. So to your example over the um. the recent Black Friday, I found a, a great deal on a high end graphics card laptop that I haven't had my eye on from $1,400. I got it for six 60 'cause I found a bunch of deals, found a good value Best Buy, um, open Box right now because of that. But it was just searching existing websites. Best Buy and
Jerry: Hmm.
Arturo: I have personally believed the sa, the SEO game has been a scam for a few years now. I think the early days of it were well behind us. I think companies are throwing to rank for no reason. I, I, I don't know that that marketing necessarily moves the needle, that brings the value that companies hope, unless you're like one of the very top few. I see a return to the personal touch, right? There are a lot of marketing companies that I know that are trying direct mailers again, 'cause people are excited to get something interesting and cool in the mail. I think that as we start to automate a lot more things, I think we start to do lot more intentional outreach [00:21:00] to legacy clients and leads that maybe we've already have a relationship with the joke, you know, with, um, internet companies or phone companies, right?
They do more to get a new customer than keep an existing one, which makes zero sense to me from a business perspective, right? Just 'cause acquisition costs. But I think companies are gonna see the value in keeping customers versus trying to, trying to find new ones there's no better salesperson than a happy customer.
Jerry: right.
Arturo: And as the tools become available that will allow younger, smaller teams to punch well above their weight. You know, I, I think a lot of larger companies are gonna have to reframe what they look at, and it becomes less about scalability and more about solidification.
Jerry: Awesome. No, it, it's, I think it's something that, you know, whether you are A CMO or whether you are a entry-level marketing person intern, trying to learn the business, you know, it's changed. It's not changing it, it has changed. Um, I see more. Screenshots of friends asking chat, GPT, who's the best in my [00:22:00] industry?
And if they've done a good job, then they rank right. And, but if I were to ask the same thing of my engine, it may not give me the same results. And so there's a lot of variety in that, but it is, you know, trying to figure out how to be relevant and how to be found as business leaders, whether you're a solopreneur, whether you have a newsletter, you're a speaker, or you run a, you know, fortune 100 company.
Those are things that, uh, have changed and then will continue to evolve. Um. As we wrap here, let, let's talk about some implications and some risks about AI integration, um, within the enterprise level, uh, when it comes to re-skilling the workforce, uh, and teaching maybe even, um, what are some, uh, roadblocks or, you know, uh, things that people should be, leaders should be, uh, especially mindful of, uh, and reskilling their workforce to adopt ai.
Arturo: I think one of the issues leaders will run into is not AI unique and it's just leading from the front. I think it's, it's in a world where we've all specialized and become accustomed to the roles that we play, [00:23:00] moving, just outside, making a lateral shift to a new system, a new way of thinking. I. It's hard. So by taking the reins, being, you know, be, being setting the example of what you're looking for, that's the first step. I think you're gonna run into a lot of people that don't wanna learn this, that are nervous about it, that are uncomfortable with it, that are worried about being replaced. I think businesses that think that this isn't going to squeeze their employees, I think politicians that say, no, AI is great.
We're not gonna lose anything. I, I think they're lying. There is going to be a squeeze and there always has been. Right? Every, every iteration of new technology has come with pain. What comes after is often something better. But there is an outsized impact in being early. There's an outsized impact in accepting the world that's coming and trying to change along with it. I don't, I can't think of a single ecosystem or niche that has ever survived resisting the change of [00:24:00] nature. So the flexibility required of just taking a moment and thinking, can I do this? And knowing that, yes, you can, because as an exhausted dad of three and a small business owner, I could. You can do it. And that's, that's hard, that's hard to do because we're, we're not wired in that way. Especially
Jerry: Right.
Arturo: we get, the more set in our ways we get. But bringing your people along, showing that you have the patience to show them, I think helping them see that the learning curve feels steep, but is actually quite short.
Jerry: Yep.
Arturo: I think that's really the key that you want to, to impart as a leader.
Jerry: I find that part about the AI knowledge, you know, um, sort of community, really fascinating. All of this is relatively new, very new. And so it feels like you missed out on the AI boat, but we're just at the, you know, tip of the iceberg. And so for, for you to get caught up by the time the next thing breaks or, you know, the new evolution of technology happens, you know, it will really be easy to catch up to it.
Um, and I think that [00:25:00] hesitancy in that sort of, Hey, this is the way that we've always done it, is what's going to keep a lot of organizations back and without adopting it. Um, on the same vein, um, one of the things that we. Have to talk about ai, um, is bias, and you've made a recent LinkedIn video about gender bias in ai, racial bias stereotypes, uh, which we've talked about a lot as it relates to enterprises and reliance on the old ways that they always used to do it.
So how do leaders think about AI and its ability to challenge status quo that is cultural within organizations and more so some of these, you know, we'll call 'em old school leaders who like the way that they've always done things. What, what is the bias of AI perpetuating old habits and how can leaders think about using or leveraging AI to introduce genuine, fresh ideas into the culture?
Arturo: Be be the lion that's willing to give up control of the pride. You [00:26:00] know, I think, I think what we have seen is AI isn't biased. I. We are, now it's in our face. It's faster, it's unavoidable. And this goes to the cultural and social implications that AI really is. We are biased. We have been. We are. It's on.
It's served us. In our earliest days, we had to make stereotypes to make it to this point with skyscrapers and parks and whole foods, right? But we're more than that now. And now we have to look at it and say, okay, this is who we have been. Who do we want to become? And now's our chance to do that. So if you are a leader and that feels like it makes you nervous, why. If you are a leader who's more concerned with how you look and not wanting to look bad, examine how and why you feel that way, and really if, if someone else can do it better. that's you, maybe you can do it better, [00:27:00] right? we can all grow. But again, to stand in the way of evolution, to stand in the way of a new way of thinking just puts you on the wrong side of history.
And it, it, it's never worked out. So I, for one, am excited that AI is magnifying who we are and what we are. And I fully admit I am a biased optimist towards what AI represents, but. There is very much that aspect of understand where you stood, be grateful and confident in what you've accomplished, and make the effort to push that ball, push that, that, that needle a little bit further.
Jerry: And, and I think, you know, to, to elaborate on that, I think it also gives us an opportunity to think about the data or the, uh. The information that we've quote unquote fed AI to get the bias results, right? So what, what have we done in media, in business to get AI to think that when you say X, it always thinks y, right?
And so this is, I think, uh, another good sort of, you know, I think what you're getting at is [00:28:00] smart leaders need to reflect honestly and with a little bit of vulnerability to say, Hey, this is giving me an opportunity to reflect on the way that we've done things so that we can get ahead and, and accelerate, uh.
As we think about all these things around ai, there seems to be an overabundance of, uh, videos to watch content to consume, uh, conversations, to have tools to learn. What are some specific things that leaders can do, uh, to help them get ahead? And in particular, what, what is the one question that you think every enterprise leader should be asking themselves right now before green lighting another AI initiative so that they can lead better tomorrow?
Arturo: Do I understand what my organization needs, though? It's not about ai, it's about the problem you're trying to solve. AI might be a part of that, but it's a matter of just making sure you understand the capabilities and limitations of the tool and that you [00:29:00] understand the parts that it effectively integrates into the solution and where you absolutely should not try to integrate it.
Jerry: I will add, I'll answer that question myself. I think one question that every enterprise leader should be asking is, should I send my people to San Diego in June to go watch Arturo talk at term 25 about this? Um, I. Arturo. This has been really fun. And I think, you know, we're, we're recording this in, in, um, you know, in May of 2025, if we were to talk in three months, six months from now.
Uh, the nature of AI will continue to change, um, as the technology changes. And I think I, I'll make this the last question. What is the evergreen nature of AI from a business adaptation and leadership perspective that will never change about ai, that business leaders should stay steadfast on?
Arturo: Stay humble and stay curious. 'cause it's never, it's never going to not change.
Jerry: That's good. General life advice, that's good general parent advice, and certainly it is really, really great business leader, AI advice. Uh, Artur Farrah, founder of the AI [00:30:00] Reports, uh, friend of SHRM. Again, we'll be speaking at SHRM 25. Thank you so much for taking the time, uh, to share with us your insights and your advice on how business leaders can really adapt and lean into, and sometimes lean.
From AI as businesses, thank you for joining us on this episode of Tomorrowist.
Arturo: It is been a privilege. Thanks, Jerry.