Innovating Leadership:
Co-Creating Our Future

Resources:

Neil’s book, Own the AI Revolution, is available on Amazon at https://amzn.to/4kx4af3, and on Audible at https://amzn.to/4lgS0rK.

Learn more about Neil on his website at https://www.neilsahota.com/. He shares his latest observations on AI in the workplace on his Substack channel at neilsahota@substack.com.

Our host Maureen Metcalf posts a newsletter every week on LinkedIn. You can subscribe here.

The book Maureen and Neil referenced which they wrote together is Innovative Leadership & Followership in the Age of AI. You’ll find details about it at https://bit.ly/LeaderInAI, or check out the Kindle version at https://amzn.to/44buVz8. The audiobook version is now available at  https://amzn.to/4dTCleZ.

Other binge-worthy episode about AI is:

– The 10 Leadership Skills You Need to Safely Adopt AI
– AI, Your Story, & The Professional Identity Crisis

Guest(s):

Guest(s) Bio:

Neil Sahota (萨冠军) is an IBM Master Inventor, United Nations (UN) Artificial Intelligence (AI) Advisor, author of the best-seller Own the AI Revolution and sought-after speaker. With 20+ years of business experience, he works to inspire clients and business partners to foster innovation and develop next generation products/solutions powered by AI.

Transcript
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Maureen: This is Innovating Leadership Co-Creating Our Future. I’m your host, Maureen Metcalf, the founder and CEO of the Innovative Leadership Institute, where we help leaders be future ready. Helping us on this mission today is returning guest Neil Sahota. Neil is an IBM Master inventor. Nations AI advisor, author of the book, Own the AI Revolution and professor at uc Irvine. In this multi-part series, we’ll be talking about the five reasons in this multi-part series, we’ll be talking about how to ensure your AI transformation is successful. Neil, welcome back.

Neil: Hey, great to be back, Maureen. Always enjoy our conversation.

Maureen: Thank you. So let’s jump in. We’ve [00:01:00] talked about in the first series, five reasons why organizations Fail with ai. Now we’re talking about success factors. Let’s start with culture and organization dynamics. How can organizational culture impede or facilitate effective AI adoptions?

Neil: Well, you know, people are finicky. I. Mildly. You really think that most of the work we do AI are not, our biggest and most frequent challenges are often people related. And so what I tend to see is, you know, people, most of ’em don’t like change. And so whether it’s a small or big change, you get some built in resistance unless we as leaders paved the way or share the value and the benefits for the people.

So like, I remember, uh, you know, this was the real estate development industry. You, I was talking about the top [00:02:00] five use cases, you know, sharing the list. And there was a, a guy in there that was the CEO, that there’s lots of guys, one guy was the CEO of his own company, said Sweet, took a photo of the list, ran off to his employees, like, we’re doing these five things, right?

I didn’t know this at the time. Uh, a guy reached, the CEO reached out to me about six months later and he is like, Hey, I think you made all this stuff up. I’m like, what are you talking about? Right? Those five use cases, there’s no way anybody could do these things. I’m like, what do you mean? He’s like, I gave this list to my people and it’s gone nowhere and some churn now for, from our top people.

I’m like, I know these are legit. ’cause this is what a lot of people industry are doing because I’ve actually helped a couple of your competitors do exactly these things. So he is like, Lynn, help me. Right? And so I came on to find out there’s a little triage, and what he [00:03:00] did was he basically just told people we’re doing these five things and the people freaked out.

Some people were like, we’ve never done AI before. Some were like, why are we doing these things? But a good chunk of people were like, if I do these things, do I lose my job? Right. And I. Well, guess what? You know, as much as people probably wanna try and create value for the company, if it’s gonna cost them their job, that’s the perception.

They’re not really gonna be supportive of that. They’re gonna be saboteurs, and that’s what was actually going on. People were intentionally sabotaging these efforts. So when we talk about the importance of organizational culture, can’t just hand people a list and say, go, right, we’ve got to champion and create the buy-in.

Establish the value proposition for why we’re.

Maureen: You know, part of our work and all back up when I started the company, one of my questions an underpinning. Reasons for starting is [00:04:00] highly effective. Consulting firms don’t always generate successful transformation. They’re not hired, frankly to create transformation. They’re hired to implement systems. We call that transformation, but you look at the statement of work, it’s implement this SAP or Oracle or something.

It’s not change our culture. not change our leadership behavior. It’s not change how people think about what’s valuable for the organization. And so in my research it became clear that the. One, the thing we’re inviting people to do, to your point, here’s the list of stuff versus truly transform our organization. And so I was having a conversation with a creative organization and. AI is not, [00:05:00] many creatives are not a big fan of AI because of the perception of it stealing their work. Uh, and so it’s gonna be, to your point, there are people who think it is Satan and giving me a list of stuff to do to enable Satan to impact my company. I’m gonna find every way to look like I’m doing the right thing and undermine the thing. I may not explicitly say, you’ve invited evil into our organization, but I’m not gonna go out of my way to get it done. And so even the first question, is this aligned with my values? ’cause if not, the probability of success is low. Then we can look at culture and what are our agreements about how we operate. And for many organizations, it’s gonna have a big enough impact that [00:06:00] we’ll need to change our culture. It.

Neil: A hundred percent Maureen and, and I think that’s the challenge. I mean, even with simple, non-AI leaders tend to take the same thing, right? That they understand the business case and the value. They, I think, assume so do my employees, right? They, they often don’t like, right? I, I can’t tell you how many times I hear the question from people, like, why, why are we doing this?

Right? Even early in my career, I would ask that, like, why, why are we doing this? I would assume there’s a good reason, but I don’t understand what it is.

Maureen: And it’s a whole lot easier to get people to move along the change acceptance curve if they understand it. You know, back to the why and in my, you know, back way back machine implementing ERP systems. worked with a large healthcare organization. I think there were 36 [00:07:00]acquisitions that we were implementing in, and the agreements of how they operated was, you bought my company, you fund us, we send you large amounts of profit. ERP comes in. Suddenly there’s big brother looking at everything we do now. You have insight into every order we get, how effective we are, how staffing’s done. You want us to use all your centralized stuff. It was a complete change to the agreement of how they operated their. Entire enterprise. And for many of them, these were the businesses that they had invested their life’s work building back to.

It might as well have been some evil being coming in to take over their lives. Uh, and, and ERP seemed more, more straightforward than an AI that’s off learning by itself and gonna take its own direction. At least I know what, what the ERP is gonna do.[00:08:00]

Neil: Well, a hundred percent right, but even things that might be beneficial for us. If we feel like we don’t have a choice, we don’t have a say in the process again, people will try and either block it or sabotage it. You know, I ironically, I’m reminded of new Coke, so

Maureen: Mm-hmm.

Neil: probably day day myself here, but I think it was 86 or something like that.

Coca-Cola hundred year anniversary. So we’re gonna change the formula, right? Tweak it, make it better. But when the way they did this was they released new Coke, but they stopped selling old Coke. So a lot of people felt like they didn’t have a choice in the matter. And again, you’re trying to fix something that wasn’t broken.

Right? And I mean, obviously sales went in the tank. People weren’t happy. And so what did Coca-Cola do? They went around doing wine taste tests, right? They weren’t really addressing and trying to manage the change. They would do these blind taste tests. And so people like. [00:09:00] Show you like which one you like better.

And most people did pick new Coke, but when they showed them like, oh no, that’s really old Coke. You’re trying to trick me, you know, no, nobody wants it is like, and you can’t, you can’t use like facts and science to persuade people. I’m sorry, but that just doesn’t tend to work. It’s an emotional response.

And so the only way Coca-Cola finally got over the hurdle was they, you know, brought back old Coke, made a classic Coke. People would buy that. But the sales for new Coke at. Reputation was so tarnished, it just faded away. You know, it might have been the better product, but the way they rolled it out, the change was extremely poor, right?

Bad leadership and the organizational change management.

Maureen: So what are a couple of strategies E, either in the change management space or in the culture space to help people embrace [00:10:00] AI and mitigate resistance?

Neil: So a, a couple couple of things. Low hanging fruit, one that’s not rocket science. Help people understand why we’re trying to introduce ai, why we’re trying to make this change and focus on the benefits for them, right? We tend to talk more about the organization, but yeah. You know how much you hate having to spend.

Of your time reading through the claims adjustments. Well, by doing this, we’re gonna cut that to 5%. You know, you know how much you hate having to fill out these, these same paperwork over and over again for each customer. Well, we’re gonna take that off your plate so you can actually focus more on the marketing message.

Right? Frame it that way. Show them. Show them positive.

Great to think big, but start small, [00:11:00] right? People already don’t like change, even small change. So you wanna focus on small, quick wins, things that tend to be innocuous. You know, one way I’ve been helping some companies actually kind of build that momentum is kind of call it the concierge model. We talk about ai.

Use a small language model, SLM, so not the big, big like chat, CPT, but let the AI read your employee handbook. Give it your PTO policy, you know your tuition reimbursement benefits, and so that if people have HR related questions, rather than go to a portal or talk to an HR rep, they can actually get their questions answered by this HR concierge.

It’s innocuous. No one’s gonna flip out if it, you know, makes a mistake. It says, will you have 19 PTO days instead of 20? Right? It’s a way for people to see [00:12:00] interact, but you actually show value from that, right? And then you can start stacking over there. What I see is when they build an HR concierge, they’ll do kind of like a branding one.

We’ll put something on our website. So if people, our.

They start building out that way. So don’t, don’t, you know, even Jim Collins with his BHAGs big hair audition goals, right? Says you have to figure out the, the, the small milestones in the journey to get to that BAG. So don’t jump all, all the way. And the third is really give people some training, but help them figure out things they can do in their personal lives.

It creates more comfort level. One of the things that, you know, I saw companies do and encourage them actually was have people write their bios using Gen ai, plan a vacation. Right? It’s something that they can see. Yeah, it’s not the end of the world. It’s not gonna take their job or anything like [00:13:00] that, but they can see how to use these tools and the value they can actually get from them, even if it’s small, incremental value.

Maureen: You know, as you say that, one of the back to this HBR article on how people are using Gen AI in 2025. Number two is organizing my life. So this is the list of ingredients I have in my refrigerator right now. Write me a recipe or help me with a workout routine or. The basics of plan my vacation, that it’s, it feels safer to experiment on that than biggest project I’m working on in my career ’cause of

Neil: Oh

Maureen: out on that not so helpful.

Neil: no, but it’s, it’s fascinating, right? ’cause you kind of open up a bit of Pandora’s Box that we found. So they get more and more comfortable using these tools. But again, we can’t just, [00:14:00]you know, as leaders sit by the sidelines. We also have to help them focus some of their efforts. For productivity. There was a, a client I had, they, they sent all 300 of their employees to prompt engineering class.

Right. Help ’em understand how to write good prompts. Got them all, you know, enterprise Chat, GPT, and then they’re, they’re telling me, Neil, we, we’ve made this investment and all this kind of stuff, but they’re not using, they’re not using Chad, GPT or AI for any of their work stuff. Right. So that’s, that’s interesting.

So I, I started talking with them and they’re like, oh, you know what? I love it. The class was great. You know, I actually do some of these things like, you know, plan a vacation and someone was actually talking about, we were actually re researching potential colleges for, you know, my senior in high school, for example.

And then I’m like, how, how come you’re not using any of this for work related activities? They’re like, oh, our management hasn’t told us what to do with it yet. I’m like, [00:15:00] oh, so you’re waiting for the management to tell you where to apply the tool? They’re like, yeah. And I’m like, maybe, maybe they, they thought by sending you to training that you would figure out ways to use the tool.

And I’ll never forget the, what people would say to me, that’s not how we operate here. Right. So I went back to the management and shared the feedback and I’m like, well, no, uh, we sent ’em that so they could figure it out. We don’t know where they should be using this. And it created this weird deadlock situation between them, which was more of a cultural issue than anything else.

Boys are waiting for management to give the directions. Management’s like, we’ve never done anything like this before. So they’ll figure it out. Boom.

Maureen: So back to ethically, does it seem like a reasonable course to follow? And then the cultural agreements about we do what we’re told, not what we experiment with. So that takes us then to [00:16:00] the question of ethics. W uh, with AI’s increased role in decision making in some companies. How should leaders approach ethical considerations and accountability?

Neil: The honest truth is this stuff is becoming a, a must have. Right. You know, you’ll people talk about the legal liabilities, these types of things. That stuff is really out the window now, and I don’t mean that in a bad way. It’s that we have something we start calling really the trust factor, right? If you’re not actively thinking and integrating ethical practices and you’re looking at some of these things, whether legally you’re permitted to do it or not, you’re actually gonna sell out your own business because if people don’t have the right level of trust factor in your products and services, they will actually not do business.

So you look in things like healthcare, where, you know, some of these things are, [00:17:00] I hate to say, kinda automated in terms of recommendations based on cost and some of things, it’s just like, where’s the, the human factor in, element in that, right? And they’re like, well, you know, this is what we normally do. I mean, would you, would you spend $4 million to extend someone’s life?

Two more months, right? It’s like, well, is that a math equation? Right? That’s what it boils down to. And, and maybe it doesn’t make sense to spend so much if the quality of life is poor, but you’re talking about then a math equation. Are you putting all these elements right, all these ethical considerations as part of that math equation?

And that’s where you see leaders stumble. Do I like, well, we’re, we’re kind of doing it the way we were always doing it. I’m like, there’s a lot of tribal knowledge that would go into some of these things. They’re not captured in that math equation. So if you’re not actively thinking about those considerations, uh, you are setting yourselves up to be well knocked out, right?

Because we’re seeing, [00:18:00] especially with the younger generations, they don’t have a tolerance for that. You betray my faith once and I cut you out forever.

Maureen: Hmm. So is there a framework or a series of frameworks to help guide people through the ethical piece? Because you’ve given in the first conversation in this one, examples of organizations unknowingly. Making an ethical error, and presumably if you’re stepping into new territory, everyone’s gonna make some kind of errors.

Neil: They, they will. The answer to your question, Maureen, is yes, no, and sort of, I hate to say it.

Maureen: I.

Neil: Right. Uh, is, is there like, you know, ethical frameworks and standards out there, there’s a lot of different varieties of them. You know, even our UN work, we’re trying to figure some of these things out. [00:19:00] Is there an accepted standard universal use?

No. And that’s not gonna be an easy thing to do, to be perfectly honest. Um, I think it was 20 20 17 or 2018, I forget. I was asked to give a speech at the Global Symposium for regulators, and in my speech I put voice to what everyone is thinking about, but no one wants to talk about was how can you define right use unless you have a baseline of ethics and moral standards.

And think about that. It’s a very subjective thing. We each have our own different kind of code. I’ve seen people, you know, very viscerally react about, no one’s gonna tell me what’s right or wrong,

Maureen: [00:20:00] Mm-hmm.

Neil: I was done with my speech. Nobody clapped, right? No one.

Maureen: Wow.

Neil: I remember the, uh, one of the Deputy Secretary generals from the UN happened to be there, ran to the stage and said, uh, Neil, what, what you said was the right thing.

It was a very brave thing to do. I don’t think you made any friends here. You should probably get outta here. And I, I did. Right. So I was surprised. The next year they asked me to come, come back. What I noticed the next year was you had these little hallway conversations where they were actually kind of talking about that, so you kind of got the ball rolling.

And then last year, uh, at the Global Symposium of Regulators, they actually invited me back to give a speech, which I was shocked by. Um, but they were calling me Fire Starter and I didn’t really understand why they were calling me Fire Starter until they kicked off the whole thing. [00:21:00] So while I was going to give the opening keynote, uh, you know, the introduction, they, they had again, a person from the UN there and she was just saying like, if you actually, you know, we asked Neil to come back and all these things, we’ll call him fire starter because the entire agenda this year is based on that speech he gave in 2018.

He lit the fire that we’re, so, they’re very actively talking about some of these things now. So when I say kind of yes, no. That’s where it is now. The sort of, people forget that AI has a superpower. It’s the one tool that we can actually ask it how to use it better. And so we talk about like, how can we be, what are some ethical considerations we should be thinking about in using you this way, right?

Or what perspectives we’re missing, or you know, unintentionally excluding it could actually help us figure out some of those things. So that’s one of the things we should leverage is AI bring [00:22:00]the machine perspective into the ethical conversation.

Maureen: So does the ethical framework then, uh, I can see another yes, no, maybe answer. Um, it sounds like there are ethical frameworks probably at the national level, maybe some at the industry level. So you gave the example of real estate and redlining or taxes. Um. there’s the company level. How do we behave irrespective of what’s happening in the industry? So is it kind of like a nested doll system?

Neil: To, to a degree, right? I mean, when we, we maybe subconsciously we think about these things, the problems. We don’t consciously think a lot of our work, how it might have dispar impact. Same thing. Like, I hate to say, like, we don’t think about how we could create social good either, right? [00:23:00] We’re you’re a for-profit or you’re a nonprofit, right?

It’s just recently realized, well, you could actually do both, right? They’re not mutually exclusive, but that level of thinking has per, has not permeated our culture or corporate cultures yet, right? And so that level of ethical thinking that could be good or bad hasn’t done the same. So, you know, kind of circling back into real estate, but mortgage lending, there was great fear in that AI could learn some of our biases and, you know, exclude certain groups.

Again, no redlining violating other things, but I, I’m a big believer in what I call the mirror image. Mirror image theory. For every threat, there’s an equal opportunity just flipping around. Right. So the HUD actually started thinking about that. There was a, a test that was run for three years to benchmark this.

Could AI be actually be better and less discriminatory [00:24:00] in mortgage lending? And the answer is yes. If the whole decision is really a math equation, right? Let the AI plug out all the documents, just plug out the information it needs to fill in those variables. What we found was the AI would often approve people of color more frequently and often at a lower rate than the human loan officer would.

Right. And some of the questions like, why? Why is this happening? Right. Even if you blind out the name on the loan application, we found where people were still making. Inferences and judgments based on where the person is moving to or what kind of job they have or where they’re currently living, or their level of income.

And so there were all these kind of built-in biases that were slightly skewing and well, one by itself may not have been too big grouped together. It’s kind of a three mile island situation, so the HUD is [00:25:00] starting to move towards that. Maybe that calculation should only be done by ai, not by humans.

Maureen: Interesting how the ethical. Decision making then kicks off a systemic that has its own ethical loops.

Neil: It’s, it’s a, it’s a never ending process, right? But while ai, we have to worry about AI being weaponized, it could also be a powerful tool to bring democratization.

Maureen: Well, especially addressing unconscious bias by the. virtue of the term unconscious, I’m not choosing to be biased. I am doing it for any number of reasons based on my family of origin or assumptions. I.

Neil: I, I get that right. But we all unfortunately [00:26:00] feed into stereotypes or misinformation. Like, I remember the first time I had to travel to Columbia for work quite a while ago, but I had people saying like, you, you shouldn’t go, you’re gonna get kidnapped at the airport. You know, the drug cartels. And I’m thinking to myself, that stuff was like 20 years ago.

You know, they’ve had farc, they’ve cleaned up, and I, I went to Columbia and I didn’t see any of that. Right. But the average American’s perception at the time. That Columbia was a super dangerous place right off.

Maureen: Mm-hmm. Yeah. Great. So let’s now go on to the next category, which is communication and change management. And you alluded to change management. Effective communication is crucial. Always, especially during a transformation, and I love the idea that [00:27:00] while. AI is learning from me. I am also learning from my interactions with change management. So how do we help leaders ensure that transparent and effective communication is happening throughout the organization? You started with understanding the why of the implementation. Now how do you ripple that through the organization?

Neil: Well that’s, that’s a much larger challenge and it’s goes far beyond ai, right? Because now you’re talking about the, the trust and belief people have in the leadership. And I think that’s one thing we forget. You know, we always talk about different leadership styles and some people are, are authoritarian of the boss, so you.

Maureen: Mm-hmm.

Neil: We don’t really live in an age where, where people subscribe to that kind of philosophy. And I think that that’s the challenge. We saw this with the [00:28:00] writer Skilled Strike in Hollywood a couple years ago when they saw chat GPT come out. That’s when it just crystallized their mind. The studios are gonna replace us.

Right? Even though studio says, we’re not not doing that. We have no plans to do that. The writers Gud didn’t believe it one bit. So even you say the why and the studio was like, well, we, we couldn’t do this. Right? You add value here. The creativity thinking original speech did not matter, right? The lack of trust and faith, we triggered that whole thing.

So I’d be glad, glad that’s all resolved. But from an organizational standpoint, that’s one of the the biggest things we gotta really worry about, that I’ll never, I’ll never forget this, that my IBM days. You know, Nick Donofrio, who was the right hand man at San Paul Modo. So we crossed paths a couple of times for various reasons and I, I, you know, obviously was kinda stuff something happened where Nick was [00:29:00] really happy.

He is really excited. He is Neil. Hey, you know, you, you’ve done amazing work for us that a lot of value. I hope you’re playing a long career at IBM. And I just looked at Nick and I said, Nick, I’m as loyal to IBM as it is to me. And he just kind of paused. He just kind of shook his head like, okay, that’s fair.

Right.

Maureen: Yeah.

Neil: does that, what does that tell you about the, the real importance of organizational culture? Right.

Maureen: Well, and back to that alignment and, and your comment about the writer’s Guild. If my belief is that this is, evil’s not the right word, but if this is going to upend my entire career and ability to. Pay my house payment and feed my family, I’m not going to enable it to happen. Until we address that as part of our change management, not only [00:30:00] why is it good for the business, but what’s in it for, for each employee, then we are unlikely to get the resounding acceptance that we need to, to truly transform an organization.

Neil: A hundred percent Marina, that’s, that’s the big challenge, right? We always talk about what’s in it for me. But if especially the employees are wondering, like, there, there’s gotta be some nefarious reason behind this. They’re not telling us. Guess what happens, right? I, I look at it like AI for good with the United Nations.

A lot of people ask me like, why did you wanna work with the most bureaucratic organization in the world? And it’s like, it’s credibility, right? Not only is it aligned values, but the honest truth is they’re the only ones that could really have led the charge to do this. If you had some country do it, the US or China, they’ll be like, okay, what?

What’s, what are they getting out of this? Right? What kind of advantage? Are they getting, what are the political motivations? With some company like [00:31:00] Microsoft or Google, they’re like, okay, what are, what? How are they monetizing this? Right? We’re just kind of built in that there’s, there’s the good reason and then there’s the real reason, right?

And I, that’s, I think the challenge that some people have is I hear what my employers are saying. My leaders are saying, right, this is gonna help do X, Y, Z and create this value for our company. Are they really trying to lay me off? Right? They’re trying to cut costs or, you know, we didn’t have a great year last year, revenues wise.

So is this a way that that’s, that’s the dangerous thinking, right? That’s a systemic of a much larger problem in the organization, that the employees have lost faith in the leadership.

Maureen: Yeah, we’re, which seems to be rampant right now.

Neil: Uh, that’s, that’s the problem we’re chasing. And I, I noticed from my own, my own days is we’re chasing the monthly numbers. We’re chasing, you know, the quarterly returns [00:32:00] rather than investing in people and true long-term sustainable growth.

Maureen: And that again gets back to a cultural issue and also, and, and our next topic, what metrics we talk about, what metrics should leaders focus on to assess the success of ai. But I would say. In response to what you’ve just pointed out, what metrics should leaders be looking at to assess if we are even ready for this change, faith in the organization?

I.

Neil: That’s the key thing, right? We always think, well, it’s easy to do or learn, we’ll just move forward. But much like you need the right infrastructure to use ai, you have to have the right organizational mindset, maturity level in place to actually recognize those benefits. So it’s, it’s not [00:33:00] enough to send someone to prompt engineering class.

Right. We saw that with my previous example. It’s not enough to say like, Hey, I’m not doing this to take your job, whether they believe it or not. And then, and then that’s the thing. The people, the people challenges are the hardest and the, they’re slow moving and take time and investment. And yet we want to go, go, go.

Maureen: Mm-hmm.

Neil: So that’s why I, you know what I’m saying? Like people are always kind of worried about more the small, medium sized businesses. It’s easier for them to move quicker. ’cause the leadership is usually closer to the ground. Right. And so they have a better beat on the pulse, and if they’re an effective leader can help manage that change and manage the organization and create that value for their employees to drive successful change.

You’re in a big monolithic company. You’re basically trying to make a U-turn on an aircraft carrier.

Maureen: You know, as I think about this, I think about. ago, [00:34:00] we would do, and I assume this is still happening, I’m just not in that space, that we would do change readiness assessments, how, and we would look at things like trust. If you don’t trust your leaders, you are not ready to implement a major change. If you have no valid communication channels, the things you’re talking about, if you’ve got a culture of stability over adaptability, at a minimum, your change initiative just got bigger because you’ve gotta address all of systems around implementing a change. It’s not just a change now, it’s a an org transformation. In

Neil: Yes.

Maureen: of the change thing.

Neil: Well, that’s what I think people either discount or, I hate to say this way, choose to ignore.

Maureen: Mm-hmm.

Neil: years ago I was hoping two grocery chains, [00:35:00] big grocery chains do a merger acquisition, right? And you’re thinking like, okay, well store locations and overlap and you know, we don’t need two HR departments, that kind of stuff.

But it’s also like I’m the only one going there like. One company has a centralized business model, and the other has a decentralized business model. You know, one grocery store, the corporate headquarters sets the inventory and the pricing everywhere. The other one leaves it to the actual individual grocery store manager to dictate that.

That’s a complete 180 in business models, and no one’s talking about like, now you’re integrating, what are you gonna do? Right? You’re gonna pick one model. So what happens to the person not using that model? And I’ll never forget it that all I ever hear is like, oh, they’re gonna toe the line. Right. That’s good business.

I just think it to myself, oh my, this is why most m and ass fail. Right? They don’t address the organizational [00:36:00] people challenges. It’s the same thing with. Right. I ironically, some of these challenges have been exasperated because people are like, well, people are more comfortable with ai now they’re using

something.

Maureen: Yeah. So how do organizations create feedback loops to continually, I would say prepare, monitor the integration and also address the unforeseen challenges.

Neil: So the, the smart ones, the successful ones actually will create what I’ve seen, uh, for lack of a better word, kind of a tiger change team. So they, they actually allocate resources not to just help, you know, manage to explain the change, but to actually to solicit feedback. And again, AI being, uh. A tool that can help you figure out how to [00:37:00] use the tool better.

They’ve actually set up AI bots and so as things are going well or poorly, you could actually share with the AI bot anonymously your feedback. And so again, this goes back to how people are, you are usually more honest with, uh, AI bot, they’re getting a lot better feedback that way. The key thing though is they’re actually moving on the feedback quickly.

So they’re not just acknowledging like, okay, well we got a dozen people complaining about this. If they have a handful of people, they want to go out and try and, and verbalize say, look, we’ve gotten this feedback. We’re concerned by it. We’re try and figure something out. We, we want people’s help to come up with a reasonable solution.

So they’re trying to make people part of the process. It’s a hellacious amount of work, and some organizers are like, well, that’s taking time from them doing. More meaningful work,

Maureen: work.

Neil: but those companies that are doing that, they’re having a much easier and [00:38:00] successful time introducing these changes from So pay.

Pay the dime for worth and do it.

Maureen: Well, and, and the reality is change is incredibly time consuming and costly.

Neil: But it’s, it’s necessary. You cannot get around it, right? It’s as much as like we ask the question, well, do we have the right infrastructure to support this? We should be also asking the question, do we have the right culture, maturity level to support this?

Maureen: Absolutely agree. So let’s now look ahead. What emerging trends in AI should leaders be aware of to stay ahead of the curve?

Neil: So aside from all the things we’ve been talking about today, if you look out into the near future, three years from now, we’re always trying to see the shift. These high energy interns we’ve created are becoming full-fledged employees. [00:39:00] And so as a leader, you’re gonna be looking at literally a mix of both human and machine employees and in some cases.

You’re gonna have a human managing both, or you’re gonna have a machine managing both. You’re gonna have integrated kind of teams. Again, this doesn’t mean that you’re replacing people, it’s just different sets of work. And if you look at manufacturing, they’re actually already doing this. So GE has manufacturing plants.

Where the, the floor supervisor is actually an AI system, and in real time it’s monitoring people’s performance, assigns tasks to humans and machines, and gives them feedback on their, their actual work. But right, this is gonna become more prevalent as we go in places. You look at customer service, you’ve already got some of these AI bots listening on the calls with the human agent prompting questions, but also giving real time feedback to the rep about their performance.

So three years from now, you’re gonna be looking as leaders, a mix of human and [00:40:00] machine. How are you gonna facilitate that change? Right? That’s a massive corporate cultural change. Some people are gonna be embracing some, not so much if you’re not already thinking about it. The honest truth is you’re behind the curve on getting ready for it.

Maureen: Yeah, thinking about reporting to a machine is an interesting bending of our constructs.

Neil: Machine employees don’t get sick. They don’t show up. Work hung over, right?

Maureen: am just thinking more like a machine bot. I get the machine employees and they don’t talk back and they yet, they’re not hung over. They’re not tired, they’re not concerned that I’m not fill in the blank,

Neil: But.

Maureen: a machine boss, sorry, go ahead.

Neil: But, but you have a machine, Moss. Think about, you’re a human, you have a machine, moss, and you’re, you’re going through something emotionally [00:41:00] massive, right? Maybe some tragedy in the family, for example. People are concerned like, well, the machine understand that, right? Could it be empathetic? I mean, is it still going?

Just expect me to suck it up and do the work, right?

Maureen: my human boss.

Neil: We talked about, particularly in the first part, that machines are more empathetic, much better than we. It actually might be a plus to have a.

Maureen: Well, yeah, if therapy’s the number one use right now and your example of it’s gone through the HR manual and may tell me I get three days off for fill in the blank thing. Sick parent. Sick child. Yeah. It could send me home where? Where the human boss tells me to get my butt back to work.

Neil: Yeah, and I mean, think about it. If the machine boss has been trained to say like, well, we wanna maximize productivity and value from our employee, that doesn’t mean like we’re gonna allocate [00:42:00] every second, right? We know that there’s actually a lot of unproductive work by doing that. It might just say like, Hey, I don’t care if it takes you four hours or 10 hours to get this work done.

Just want it done with high quality. That’s what I care about. There might be an opportunity for more work life balance that we haven’t realized, right? Again, the mirror image, right? Every threat has an equal and opposite opportunity.

Maureen: Yeah. The idea that it will take several mundane tasks off of my plate, then there’s a choice. Can I have a more balanced life, or do I just take on more tasks? So let’s now shift to your personal insights you’ve had. Certainly years of doing this, but truthfully, I think decades of, of working with machine learning and ai.

Right.

Neil: Uh, yeah, over 20 years. So now I feel old.

Maureen: You’re young. Um, [00:43:00] so thinking about your what’s been the most surprising lesson you’ve learned about leadership in the context of ai?

Neil: That’s a great question. And I think the honest truth is we, uh, as much as we like to think that we might be great leaders and we figured out certain practices and techniques, we literally under, we literally don’t understand a whole lot of what it means to be a great leader. Right. Part of this has come out, ’cause we were trying to figure out could you create an AI leader like Ari?

One of those things is like, could you have an AI president? So we can only teach AI what we understand and know. And that’s one of the challenges we, I don’t think we understand. Leadership is always constantly evolving, right? The workforce is changing, the world’s always changing. So what works today isn’t gonna work tomorrow.

And so how do we actually get ready to adapt? And what I really learned is that you. Understanding, understanding [00:44:00] and more importantly, anticipating people’s needs. And that’s not something we kind of figured out is like, how does that work with ai? You know, Harari, this ultimate quest for like an AI president or AI prime minister came to the conclusion that it would be great at day-to-day tasks, right?

Operating the country, stripping out some of the political influence so you create, you know, more fair balanced benefits for. For the larger, the big, very audition goals, the BHAGs for unexpected events that pop up, like, you know, war invasion, a famine or something. You actually really need the human leader there because the adaptability, the agility, that’s all needed.

So. The biggest thing right now is it’s not just that. Well, you know, it’s always dynamic. It’s the pace of change of leadership. The world’s entering a time we’re calling hyper change.

Maureen: [00:45:00] Mm-hmm.

Neil: Now when experience a hundred years worth of change in 10 years. It’s the same thing with leadership. Your ability to adapt and change has to be nearly instantaneous now to, yeah, there you go.

That’s the book right there. To be able to handle this. AI triggered hyper change and has triggered the change in leadership.

Maureen: So, so joking aside, the whole intent behind becoming the Innovative Leadership Institute is helping leaders innovate how they lead, not just innovate the topics that they are leading. So how do I innovate myself as a leader is the fundamental question. And also the challenge to our team, including you, is how, how do we then our methodology fresh?

Because what is innovative for leaders today, 10 years ago, [00:46:00] 10 years from now, will be stale.

Neil: Hundred percent right? Uh, my buddy Peter puts it best. He says, you Uber yourself before you.

We’re always talking about our, our companies or organizations, but it’s true for us as leaders if we’re not trying to disrupt our leadership style, right? That’s the whole thing. But again, we have to think about what we’re doing today. We have to anticipate what we’re gonna be doing in three years, right?

When I talk about like, Hey, for your industry, these are the top five use cases that are current going on. People are like, well, we’re not doing those things right? So they’re like, great, we’re gonna go run and try and do those things. And it’s like while you’re doing those things. Competition is leapfrogging ahead of you.

’cause they’re trying to do the next things right. And so to be an effective leader, an innovative leader, you be thinking about what’s the next set of things I should be doing as a leader to be successful.[00:47:00]

Maureen: Yeah, and I even more interesting is. Like Steve Jobs developed things I didn’t even know that I was gonna think I needed. How do we help we, those of us doing the research and the application, how do we move the field of leadership forward so that we have to offer the things leaders need so they don’t have to be an expert in leadership. They can continue to come and learn.

Neil: Yeah, that’s where your institute, I think, proves in valuable Maureen, because that’s what you’re really helping leaders do. And again, if you’re wondering where the whole world might be going, your organization might be going, where leadership might be going. AI is amazing at scenario planning. We as people suck at it, but AI is amazing.

So if you wanna anticipate what might be happening, have a powerful [00:48:00] tool. To leverage and then leverage the institute to figure out how you chart the path to that, you know, two or three year future. Adapt your leadership style and make it a reality.

Maureen: Thank you for that plug and. The partnership of the two of us and our organizations really does bring to bear the AI expertise and the human expertise for clients to have insight into the future, insight into the AI capabilities and solutions, and insight into the leadership and implementation. Lots of overlaps between us that help our clients. See the future for themselves and successfully create it. Neil, for our listeners, how do they find you?

Neil: Please [00:49:00] visit my website, which is just my name, neil sahota.com. If you’re looking for latest, greatest information, especially tactical things for your organization or your life, check out the what I share in my substack, which is neil sahota.substack.com. Of course you can find me on social media. Feel free to connect and follow me.

Maureen: Thank you for your brilliant insight. I so appreciate the depth of experience you have across the broad range of topics, not just and what’s happening in the machine learning space, but also. Practical implementation, real client stories and understanding the broader context of leadership and the humans who are being swept into this cycle. Some terrified on, some really excited.[00:50:00]

Neil: Well, my pleasure to share Maureen, but hopefully this, uh, gives people the, the little nudge to take that next step.

Maureen: Cool. And thank you to our listeners for joining Innovative Leadership Co-Creating our Future. Are you interested in elevating the quality of your leadership? The Innovative Leadership Institute offers best in class leadership development, executive advising, and org transformation services. Send me a note at inquiries@innovativeleadership.com. world’s most successful leaders are created here. Gimme that last line again. Okay. Send me a note. At inquiries@innovativeleadership.com. The world’s most successful leaders are created here.