The Different Altitudes of AI in Business

This transcript was created using AI tools and is not a verbatim, word-for-word transcript of the episode. Please forgive any errors or omissions from the finished product.

Courtney: [00:00:00] Out of all the areas where you could apply AI in your business — where should you? How do you prioritize the most important initiatives that will have the greatest impact on your business? And what does the latest Mission Impossible movie have to do with the recent executive order on AI? Today, we’ll talk through the answers to each of those questions and more.

Courtney: Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era. As always, I’m joined by Knownwell CEO David DeWolf, Chief Strategy Officer Pete Buer, and Chief Product Officer Mohan Rao. We also have a discussion with Dom Colasante, CEO of 2X, about the impact AI is already having on their marketing as a service business. But first, the news.

Pete Buer: [00:01:00] joins us, as always, to break down some of the latest AI headlines and how they apply to your business. Hey Pete, how are you?

Pete: Hi, Courtney. How are you?

Courtney: I’m doing good. So big news in the week, maybe the biggest news in all the land, uh, was about AI this week in the executive order issued by President Biden to provide guidance and new roles around AI.

We could have taken our pick; honestly, there were so many articles about this, but let’s look at this one from CNBC that, uh, headlines as Biden issues US’ first AI executive order requiring safety assessments, civil rights, guidance, research on labor market impact. Pete, I know that ink is barely dry on the executive order.

What’s the impact for business leaders, and what should they take away from this news?

Pete: So, thanks, Courtney. This is, of course, big [00:02:00] news. And, though it’s focused primarily on the government’s take on the use of AI, any kind of framework that governs how the government thinks will ultimately cascade to businesses as well. So, I broke things down into four parts. I did. This is a bit of a cover the coverage response because, of course, I’ve got my own views, but I wanted to see what the world was saying as well. And so, four parts, uh, to the positive, to the negative, to the objective, and to the ridiculous. First off, to the positive, um, the order gets kind of high marks for doing the job of rolling up, the content of several initiatives that have been underway at the same time to get to a single, clear view of… In particular, the three focus areas that you mentioned in the, uh, in the title.

And the sense I get from folks whose opinions I admire is that the interpretation is the government gets it. The government’s focused on the right [00:03:00] stuff, um, and you always feel better when that’s the case. Um, in particular, there’s a focus on guiding the individual agencies to undertake a review of how AI should be used in their, each of their individual areas to make government more efficient, more effective, right?

Like that is what businesses are all about right now. I’m glad to know that government’s doing the same thing.

Courtney: Okay, Pete, that was the positive. Give us the negative.

Pete: To the negative, there’s criticism around, um, the fact that maybe it’s not strong enough or prescriptive enough on the handling of issues of fairness and responsibility. Um, talks about, for instance, remediation of displaced workers’ situations sort of, after the fact, as opposed to what I would have liked to see is pushing harder on proactive management of worker situations ahead of the implementation of new technology.

Um, and I feel like I saw that, um, in [00:04:00] the, in the reviews, um, pretty extensively as well. For executives, like so long as this is the case, so long as, um, the government’s take on responsibility and, uh, ethical use of AI, so long as, as they’re light on it, well, we have to be heavy on it, right? We have to be the ones who are looking out in our businesses, uh, for the, the folks, um, who might suffer.

And we’ve been, as a firm, beating this drum for a while. To the, um, objective or realistic, uh, this is just an executive order, right? This is guidance, um, it doesn’t have real teeth until through some manner of bipartisan drive, you know, we get to legislation. And so, as we’ve also been saying all along, this is a slow and bumpy road that will kind of unfold before us across time.

Courtney: Okay. So that was the positive, negative, and objective. I’ve been holding my breath. What is the ridiculous?

Pete: There are a number of, [00:05:00] um, articles and increasingly, memes and cartoons about the fact that the coin dropped supposedly for President Biden on the threat of AI because he sat through Mission Impossible, the latest installation of, uh, of the movie and got to see himself also as the subject of a few deepfake, uh, AI renditions, and so, well, I figured whatever, uh, whatever it takes to get the job done, right, to draw attention to the, uh, to, to the challenge, and so.

For the executives listening, your mission, should you choose to accept it right, is to…

Courtney:

Yeah,

Pete: Digest all that’s going down and apply the important bits to your business.

Courtney: That’s so good. And now Pete, are you officially recommending that they take a gander at the latest Mission Impossible as well?

Pete: You know, I watched it with the family, and, yeah, like it does a fair job [00:06:00] of giving you some amount of anxiety, thinking about what kind of bad stuff could be going on out there in the world. So, to the extent that fear is a motivator, sure, I would have a look.

Courtney: Okay, Good to know. So, yeah, a pretty comprehensive executive order that came down this week. We should be expecting something from the EU here in the next week or so as well. So, it’ll be interesting to maybe compare the two pieces of news against each other. Pete, thanks for helping us break down the news and I’ll see you next week.

Pete: This podcast will self-destruct in five or four. So long, Courtney…

Courtney: Bye Pete.

Courtney: As a CEO or an executive, I know that trying to figure out how and where to use AI, it can be overwhelming. But don’t worry, I’ve got your back. That’s why I recently sat down with David DeWolf and Mohan Rao to talk about how executives should prioritize AI-related [00:07:00] opportunities. David, Mohan, welcome back to the show.

David: You’re not getting tired of us yet?

Courtney: Not at all. Not

David: Okay. Okay, good.

Courtney: I am excited to talk to you two about this. I’m excited every week,

David: I was gonna say, do you ever not say that? But okay. We’ll keep going.

Courtney: Mohan, you’re, you’re excited every week too, right?

Mohan: I’m super excited every week, and I think you say this to everybody, Courtney, not just me and David.

David: I’m pretty confident.

Courtney: Probably true, but today we are going to be talking about something that I feel really passionate about, and we’ve talked about it on this show a few times. We’ve mentioned it. We’ve even had some episodes where we’ve touched on it, but today I want to go in depth on this topic and that’s the altitudes of AI application within a business.

So obviously, we’re all familiar with… The individual use cases, and we’ve talked [00:08:00] some about the enterprise use cases and how we need to get ready for those, but I’d like to dive into that at a deeper level. So David, would you kick us off and just kind of explain what those different altitudes look like from your perspective?

David: Yeah, when I think about this, I think about the different altitudes of work that we actually do in business, right? And I think on a very rudimentary level, you go way back to the caveman. Um, and you can imagine this, the best, but we do manual labor. As human beings, right? And I think for decades, we have been talking about leveraging AI.

In some sort of fashion, um, in order to automate manual labor. We call that robotics, right? It’s so advanced. We’ve been talking about it for so long. We actually have a word for it. When I think about the wave of this generative AI that has hit us in 2023, what I think about is the next altitude where [00:09:00] AI is impacting our work, and that is what I have called just pure tech execution.

Right. This is taking the knowledge work that we do in businesses and it is making us personally more productive, or in some cases, right, very discreet business processes, making them more productive. And you’re right. We’ve talked about these a lot on the show. It is things like software engineering is a use case.

That’s talked about all the time. Can you make a software engineer more productive with their time by leveraging AI to augment their work? Yes, you can, right! Content production is another one. Medical research is another one. We can do that work faster, and it’s knowledge work. It’s intense knowledge work, okay?

The next altitude is where I think we’re starting to get to the horizon and look at what’s the next frontier that we have to tackle. And it’s my personal belief that this is actually where the biggest impact for AI in the [00:10:00] business will be. And that is how do we actually run our organizations? What are the… if execution is automating the personal productivity. The organizational productivity is the operations of the business. How do we leverage AI to run things? And this is the integration of all those discrete processes and people. How do we take the bureaucracy out, the administrivia, the coordination, the collaboration…

All of those are the operational aspects of business. And I think that’s the next altitude and the next frontier for AI. And it’s a… we’re at a really critical point because we’re just starting to tap the surface of what that might look like. But you hear it in the conversation about fear, right? What’s going to happen to jobs?

How are businesses going to be run in the future? People aren’t talking about the solutions and what that might look like, but they’re beginning to frame it. And I think that’s the next frontier. Right. After that, you have strategy work. It’s not the process. It’s not the [00:11:00] direction of people and how we work together.

It’s the actual designing of our entire value chain against how do we deliver differentiated value to the market. I’m thinking about our competitive differentiation. Shaping that strategy, I think, is then the next frontier. And then finally, I think we have ideology after that. When you think about the work that we do, this is the alignment of people.

This is values, purpose, and all that kind of thing. Um, you know, for now, my stance is the ideological work isn’t going away from the humans for some time. If anything, what the AI is doing is freeing us up to spend more time on that. Right? So those are the altitudes, right? We’ve got robotics and manual labor.

We’ve got execution. Operations, strategy and ideology.

Mohan: Got it. Is one more important than the other, or how do you think about this?

David: That’s a great question. Um, I don’t know if important is the word that I would use. Mohan, I think if I were framing this, I would talk about impact, right? I [00:12:00] think that’s what everybody’s grappling with. When we talk about applying AI to the enterprise and to organizations, it’s what is the impact going to be?

We are absolutely seeing how Generative AI in execution can impact individual processes and people and productivity. My stance is the biggest impact is actually going to come, especially from an efficiency and productivity perspective in the operations. If you go look at the data, data shows that the average knowledge worker is spending 85 of their week on cross-functional collaboration coordination meetings.

And if you just go talk to people in the workforce, what is everybody frustrated by? Right? It’s bureaucracy. It’s… I don’t have time to actually get my work done. I don’t have time to be productive. I think that’s going to be the big unlock of this next phase of the economy more than individual productivity.

Um, but the problems aren’t being solved yet. I think the hypotheses are just getting up there, and we’re testing them out. Um, when it comes to [00:13:00] effectiveness, I think strategy refining strategy may have the biggest impact. So, I look at it across the spectrum of impact from a productivity and efficiency perspective.

I believe the operations will have the biggest impact when we, we truly automate the knowledge work there. And then the knowledge work on strategy will be a lot smarter and make smarter strategic decisions when we automate that aspect. And that’ll have a big impact from an effectiveness perspective.

Courtney: You know, one of the reasons I wanted to talk about this topic today is because I think if you’re an executive right now and you don’t have awareness of these other altitudes, you’re thinking of, how do I get my organization ready for that execution level? And it makes sense because we, it’s easier to understand, and it’s easier to grasp and figure out.

Okay. Are the things that we need to do today to get ready for that? But if you don’t have an awareness of these other altitudes that you are the bigger opportunities, [00:14:00] potentially, those are the areas that you need to get your organization ready for today because they’re coming.

David: And we’ll be the most disruptive, right? I think it’s one thing to help me do my job faster. It’s another, and I think it’s what a lot of the fear is around. Like people just know this in their gut. Machines telling us how to do things better feels a little bit like, you know, the Droid bossing me around, and it’s a little bit scary.

So I think there’s a bigger change management process there, too, because it will fundamentally change the way we run our businesses. And we talked in one of the previous episodes about our data foundation and how we’re naturally getting more and more data-oriented. Well, this is talking data. We’ve been using them to, along with information, to create more insightful information and pull insights from it. We’re getting to a level where all of that data will become Intelligence, which is actually coming to the inferred conclusion that we’re used to human [00:15:00] beings make, and that’s where you will see in operations the machines starting to say, “You know this process.”

It’s designed, and here’s your bottleneck. And here’s how we need to dynamically in real time change this process, right? Here’s what you need to know. Here’s a judgment call that I am making as a machine before you, as a human being, have been able to digest all that data and turn it into a conclusion, right?

That…that feels a little bit more aggressive to us. And by the way, it’s what Amazon already does in their supply chain. It’s how they have made such an effective and efficient supply chain for mass distribution is being so close to the customer in the market and seeing so much data that they’re able to turn that into intelligence to make real-time machine-based decisions in the moment to optimize their supply dynamically managing

[00:16:00] Every aspect of business process… that’s what I’m talking about in operations that can be overwhelming for people to think about. Cause it’s, it’s fundamentally different than how we think right now.

Mohan: Now, it’s really funny that when you first started talking about altitudes, I kind of had a completely different frame about it, right? So, and, uh, and it totally makes sense the way you describe it. And it’s, completely organizational-wide. So, so, uh, it’s very cool the way you define it. But the way I thought of it initially, when you started talking about, was the leadership attitude.

David: Hmm.

Mohan: Right?

So if you read, uh, Ram Charan’s books, the Talent Masters or the Attackers Advantage, he talks about three levels of leadership attitude. This is self and not the organization. It’s about the 50, 000 feet, the 50 feet, and the five feet, uh, that’s relevant to a leader. Uh, you know, 50K is around big-picture thinking.

Possibility of disruptions and [00:17:00] such. 50 feet is more around concrete actions, planning, implementation… all of that stuff. And five feet is really, uh, the knowledge of yourself, self-awareness, uh, emotional capacity, and all of that. And, um, I wonder if there is a way to think of AI and this type of leadership altitude.

David: I think that’s another really interesting frame, uh, for sure. And I think it can help cross each of those. And I actually think there’s a little bit of a link between those three altitudes. And what I heard you say was execution, the personal aspect, operations, the organizational, and then the 50,000 foot view is almost the strategy, right?

And so there, there’s, almost a link there — between the organizational and then the personal. How does a leader lead into driving that change in an organization?

Mohan: I completely agree. You got to look at all the five levels that you described and then say, what does it mean for the self? [00:18:00] And at the, uh, in the perspective of the self, then you got to say, what is the 50K feet view? What’s the 50K, uh, 50 feet, and what’s the five feet, and just be able to connect that.

So because everyone is a leader, you got to lead from where you are. Um, and, um, you may, uh, impact one or more of strategy versus operations or execution, but you’ve got to be aware of the self. I mean, that’s where it starts from.

David: You know, Mohan, one of the things that I think you’re pointing out with this is how important it is for leaders that are leading through this change. To take a step back and have time to create mental models and frameworks and to think strategically about problems and change and what they’re going through. So often we get caught up in just the weeds, and we can’t see the forest from the trees right we’re just looking at that next tree in that next tree in the next tree, and with how [00:19:00] fast AI is hitting us I think that’s a little bit of what’s happening, right? People are focusing on that one thing they heard from somebody else that they’re executing on versus backing up and saying, how does this apply to me as a leader?

How does this apply to my organization? And I, my thinking across multiple altitudes, multiple horizons in order to drive the change that I need. And that may be the takeaway from this episode…Take a time out and take time to process and think about from different perspectives across different dimensions and across different horizons.

Courtney: Well, David, Mohan, I think this has been a really great discussion and for anybody listening, if you want to get a list of these different altitudes and a descriptions of what’s involved with each one, we’re going to have that up on our website at knownwell.com so you can find it there. Mohan, David, thanks for being with us today.

David: A lot of fun. Thanks so much.

Mohan: Courtney. See ya.[00:20:00] If the last segment had you nodding your head, I think you’ll be interested in our free AI assessment. It just takes 10 minutes to complete, and the results can be a game changer for your company.

Courtney: You’ll get customized, personalized analysis on the areas of your business you need to focus on to make sure your organization can take advantage of the many benefits of AI. Go to knownwell.com today to get started on your AI journey.

Dom Colasante is the CEO of 2X, a marketing-as-a-service company that helps customers operate with greater impact at far lower cost. He chatted with Pete Buer about how AI is already impacting their business and where he goes to learn about the latest and greatest in AI.

Pete: Don, we’re so excited to have you on the show. Thank you for being here today.

Dom: Thanks for having me, Pete. I’m excited. Yeah.

Pete: [00:21:00] Well, so as you know, um, our focus is on AI, and how, as a transformative technology, it can help companies to evolve operations in all areas of the business. We haven’t spent a ton of time talking about marketing on this podcast in the past. What are marketers sweating or looking for help on when it comes to AI?

Dom: Yeah. Well, first of all, every marketer is talking about this, thinking about it. Um, it’s, it’s become, you know, the topic in marketing and a lot of that’s related to content, uh, and creative, which I’m sure we’ll spend some time on. Maybe that’s since that’s kind of the obvious thing that, um, AI can impact me.

I’ll give you two examples where it’s, it’s other than that. Uh, one is around targeting. Uh, and I think that in the, in the current marketing world, um, at least in the B2B space, our buyer wants to be anonymous. They don’t want you to know who they are. They want to crawl around the internet, do their own research.

They don’t want to fill out a form. They don’t [00:22:00] want to tell you that they’re researching. They don’t want to talk to a salesperson. They want to consume information on their own, in their own digital journey. One, being able to see those signals, to know who those people are, in the dark funnel, as it’s been called is a very hard thing to do, and there are technologies out there that do that. But then being able to process and analyze that data and figure out which of those and people that are researching solutions are actually in a buy cycle, are actually in a statistically significant surge of activity that indicates they’re researching something they want to purchase.

You can see a lot of that data on the web, but how do you comb through it and prioritize it? Um, and then also, how do you make sure that those companies, individuals meet your ideal customer profile that look like your customers, that look like the kind of customers you want to acquire. And so there’s some really great AI solutions in the market.

Um, my favorite one is 6Sense. It is able to use AI to drive, um, that analytic engine and then the targeting from that to identify who’s in the dark funnel that’s worth [00:23:00] going after and almost give you an unfair advantage to know who’s anonymously operating and searching for what you do. So then you can market to them and reach out to them.

So that’s one really exciting use case I see

Pete: That’s very cool.

Dom: Yeah.

Pete: That’s very cool.
Dom: The, the, second one I thought I run into is that, uh, every marketer is struggling with, um, they have to get more work done and they have less resources than they’ve ever had. And this marketing resource paradox, as we call it, where you need to create impact, whether resources or skills or people or time or budget impact is engagement ROI.

You need resources to create impact. But you need impact to pay for resources. You have…

Pete: Yeah…

Dom: …an eg of how you get resources and impact. And then every marketer is in this problem right now where, surprise, you get less resources, and I need more impact than I’ve ever received because revenue is the real cure to our problem right now.

And so this sort of unsolvable resource limitation, um, AI solves that. It helps us do more work… [00:24:00] Bottleneck in marketing.

Pete: Can we hit numerator and denominator? I guess on the cost front. I think a lot of people make the mistake of assuming that, AI…

Dom: Use cases are necessarily big technology projects that require massive lift and organizational disruption, Yeah, not nearly as much as you think. And part of it is because I think a lot of the cost is in when folks are building new things and building proprietary models and training AI to do things that it hasn’t done. There’s some really great commercially available off the shelf tech that has the right methodology.

And what it needs to do is you need to plug in them. Well, what keywords am I looking for that are unique to me? What prospect profiles are important to me? And it can filter data that it already has. And it can prioritize information. Then it can go back and actually snap into your CRM that has information of what your best customers are, who retains the best, who are the larger deal cycles, who goes through the funnel at a faster velocity, and use your [00:25:00] data to train.

So it doesn’t require you to be a technologist and you to be a developer, you know, it really connects into where you are and, and I think it may just makes it more consumable, um, not a significant lift at all. Um, and really, frankly, a lift that you can put into the budget. You already have. Most marketers are already spending money on advertising.

And if you can get a 40 percent improvement in advertising effectiveness, or you can reduce your advertising budget by, 50 percent use some of that for technology instead of advertising spend and then get more output for actually less money And so it doesn’t actually cost more and the way we look at it…It’s a redeployment of where you’ve been spending money and wasting money and pointing that you know in a very way…

Pete: Yeah, that’s…

Dom: Some of these technologies have been around for a while that aren’t mature that are not new as some of the AI conversation

Pete: So I will mention on the website, um, a number of, uh, great stats on time savings, but reduction in build time, [00:26:00] 40 percent faster video production, 60 percent less writing time. Any other fun stats you’d throw out on top of all that?

Dom: One that we’re just starting to measure Um, is, um, employee satisfaction, sentiment, retention, burnout, um, you know, marketers are in this place I talked to before where they have more demands and more appetite from the CEO and the CRO and the CFO to deliver more contribution to revenue, and they have less resources.

And a lot of, unfortunately, a lot of that’s resulted in, well, the marketing team has to work harder. In fact, at least in, in the tech sector, we spent a lot of time. Most of those marketing teams have been reduced by 20 percent or more this year. And so the work didn’t get reduced, though. So everyone has to work harder and do more work.

And so it’s creating this sort of insurmountable problem for an employee to come to work every day and have to do more work than they ever did and that’s still not enough. They need to do more from there. And I think AI is, a cheat for that. It’s a way to get more work [00:27:00] done without doing more work.

And that dimension is, definitely quantifiable. Not in the short term. We need to look at. What was employee retention before? What is it after? What is employee satisfaction before? What is it after? How do we feel, you know, about things we can measure around employees being innovative and getting promoted, growing their skill set, and being engaged?

But I think there’s a real benefit to some of these technologies around, having employees more successful and not just successful in their contribution to the company, but successful in their own personal careers and their own mental health and their own excitement about what they do.

Pete: Dom, it’s such an honor to have been able to spend time with you. Uh, thank you so much for lending your expertise and taking us down into a space that we haven’t spent much time on before in marketing. So thank you so much.

Dom: It’s a fun discussion. It’s never been more exciting to be in marketing. So asking to really enable us to do our jobs even better.

Courtney: That’s it for [00:28:00] today’s episode of the show. Thanks as always for listening. And don’t forget to rate and review the show wherever you listen. Oh, and by the way, we are also on YouTube.

So if you want to watch the show, you can do it there. Also, wanted to remind you about our free AI assessment on knownwell. com.

Before we go, each week, we like to ask one of the popular AI tools what it thinks about this week’s episode. We couldn’t help but ask about Mission Impossible. So Bard, what do you think about how the latest Mission Impossible movie depicted AI?

Courtney: Okay, Bard, are you getting some royalties? Now you’re in the know, and we’ll see [00:29:00] you next week with more AI news, roundtable discussion, and interviews.