Erik Martinez: Tim and I recently went to MAICON, the Marketing Artificial Intelligence Conference in Cleveland, Ohio. And we learned a ton about marketing AI applications, AI governance and ethics, and developing an AI first approach to business.

We think it's important to discuss AI in today's world because the technology is not going away and companies that responsibly use the technology will gain a [00:01:00] significant competitive advantage. So, Tim, what were your initial thoughts on the conference?

Tim Curtis: This was my 2nd year attending. I think they've had a total of three conferences. They had one before COVID, which in some respects, almost doesn't count the world has changed so much, and then I had last year's conference. So, very, very impressed. It really is a special event. And what I mean by that is it's not an event where people are sort of unplugged and not engaged. It's an event where people come with a certain level of expectation of engagement. They're very curious. They're intellectually curious.

What I've found hosting events over the years, when people attend an event and they have an expectation to learn and they're eager to learn, it just creates a completely different dynamic. And I think that's what we experienced in Cleveland at MAICON this year. Just exceptionally well done. The conference nearly tripled in size this year. It just doesn't show any signs of slowing down. So, the energy level around what's happening was great. It is one of maybe two or three [00:02:00] conferences that I have on my calendar every year to attend, bar none. It's just that important for me as a member of the AI community is staying involved to that degree. What about you? This was your first time.

Erik Martinez: This was my first time, and I gotta say, it was a mind blowing experience. I came out of the first day of the conference with my head literally exploding from all the amazing information.

And I think the most important thing that I learned in the conference was that not only is the technology changing on a day to day basis, but the development of applications for business use cases is rapidly growing as well. The deployment of this technology can be an absolute game changer in your organization if you take the time and energy to kind of understand and start putting some building blocks in.

So, a good [00:03:00] example and a very, very simple example for me is, we have been testing out meeting recording tools. We've been doing this for a while, and these things are not new. I'm sure plenty of you have seen tools like Fireflies or Otter AI listening into your meetings. We've got a couple more ideas, and we've started testing them. And it is just really, really amazing that you can go through a 45-minute meeting, have a tool that intelligently summarizes that meeting with just a few clicks of a button. That is a very, very, very simple use case that we all live with every single day. And it speeds up the recap and the follow up process. That was one really critical thing.

The other really critical thing is that the technology is accessible. It is available to use. One of the running themes throughout the conference was that this is the worst AI that we will ever use, which I thought was kind of a funny statement. But [00:04:00] if you think about it, this technology is growing and the community is growing and the people developing new tools on the different language models is also growing. So, there are lots and lots and lots of potential applications of this technology in everyday business. We also learned really, really, really important not to use any of Google's AI tools.

Tim Curtis: At least not now.

Erik Martinez: They are a little bit behind. I know that may sound surprising to many of you as Google has rushed to roll out Bard. We had a session with a professor from the Wharton School of Business who studies this stuff and he's like, they're just a little bit behind because they put all their money into their search businesses, which is where they make their money. Makes perfect sense. But there's lots of great tools.

Tim Curtis: It's a great lesson too, when you take a step back and you look at Google and you recognize that they're an incumbent. But they're an incumbent that's depending on protecting [00:05:00] turf in terms of their paid media sales to the pay-per-click campaigns. So, they've not placed emphasis on AI for that reason. They've been complacent. That's a good reminder that no matter where you are, you can't be complacent.

You're right. The theme throughout the whole conference, and I really appreciated them taking the time to sort of vocalize this because they did a couple of times. Again, as Erik said, this is the least capable AI you will ever use. And if you really think about that, and we're sitting there looking at the capabilities of what AI is doing currently and what it has the potential to do, it sort of begins to really reframe everything that you think about business and the internal capabilities of how to upscale employees and how to hit new levels of efficiency and really allow them to be a part of the exploration of AI. AI is going to impact every knowledge worker the next year to two years.

There was an interesting stat they shared, 80% of what marketers and knowledge workers do every day will be intelligently automated to some degree in the next one to two [00:06:00] years. That's a big statement. But I think it's a correct statement when you look at exactly how the technology is being deployed. We don't often think about AI and interacting with AI on a daily basis. But if you have Alexa or Siri, you're engaging with AI. Amazon uses AI to help predict the next type of purchase you're going to make. YouTube suggests videos, Netflix suggests videos, Hulu suggests videos. Amazon Prime suggests videos. Those are all examples of AI at work with you.

The difference is we've reached a level of sophistication that you don't need to sit down and do code to pull those algorithms. They've created an interface to allow you to use those platforms, and the AI is working behind the scenes. And that's what is different about AI today than AI was a few years ago. And big tech is betting on the future of AI. So, we learned that. The awareness and adoption are accelerating, primarily, we think, because of the rollout of ChatGPT. That really [00:07:00] seems to be where the fuel sort of hit the fire, so to speak, just the amount of awareness and adoption that people were using and testing out ChatGPT.

One other very, very valuable lesson. I'm glad somebody articulated this and I think Paul Ritzer did early on, at least in the beginning session that Erik and I attended. Laws and regulations won't keep up with AI innovation. Period. The pace of acceleration is far beyond anything we had the advent of the Internet. This is on a completely different level in terms of the acceleration plane. The court system is slow and simply will not be able to keep up with AI innovation.

That also places us in a very, very interesting spot where we're having to kind of balance the innovations of AI, as well as the potential legal challenges of AI, including copyright. Best guess we can take knowing copyright law in one case law example is that AI cannot be deemed copyrightable. It has to be a human to be copyrightable. [00:08:00] So, that's going to be interesting as well. Those are just a couple other takeaways I had.

Erik Martinez: Yeah, I would add some things. You're going to hear some new terms in the near future, and you're already hearing some of these terms. Prompt engineering. There was a whole session on just learning how to properly structure the prompts for the AI to get the most out of it.

There was discussion on will AI replace writers. The reality is, it appears that way on the surface, but when you really dig into the nuance of what's going on, the writers are the most important people in the process. You have to have that human spark, innovation, the idea. The tool helps you write that faster and maybe clean it up and edit it quicker, but it's not a replacement for the writers themselves. It's not a replacement for the [00:09:00] innovation. People are the thinking behind what the AI can do. That was a really, really important thing because I think there's this fear about the tool taking people's jobs. The reality is any innovation throughout our history has changed the nature of work.

Just think about a computer. They gave this example in one of the sessions where back in the 40s and 50s there was a person whose job was to be a computer, and they were there just calculating things. And then we invented the calculator, and then we invented the computer as we know it today. The job no longer exists because it's not necessary.

So, the technology shouldn't be feared for taking jobs, it should be embraced to figure out what the next wave of work will look like, and how you can improve upon what you're doing today. So, there's this old adage [00:10:00] in business that you can have price, quality, or speed. Pick two of the three, right?

Tim Curtis: Yeah.

Erik Martinez: With some of these AI tools, what I learned is you might actually be able to push on all three this particular moment in time. I'm not going to say that's going to last forever. But this particular moment in time, you might be able to push on all three at the very same time if you embrace the technology, you test it, and deploy it in your businesses in a thoughtful way.

Tim, I want to ask you a question. If you had to pick one thing that you felt was most impactful that you learned at the MAICON, what would it be?

Tim Curtis: One thing that was most impactful. The first thing that was impactful to me in a positive way was I learned that I was much further along than I thought I was. When you talk about AI and machine learning and deep learning, and you start to get into all of the variations,[00:11:00] you begin to feel a little overwhelmed, right? You think, gosh, there's so much to learn and I'm not very far along in this.

When we got into some of the prompt engineering, I've actually been pretty advanced on the scale of prompt engineering, using a lot of really specific instructions and language in the prompt engineering. So, for me, that was sort of a good takeaway.

I think the thing that probably made me sit back and really forced me to process maybe a little bit differently this year than I did last year, and again, this is kind of a nod to the acceleration and the adoption of acceleration. Not only the acceleration of the tech, but the adoption of the acceleration, was the degree to which AI today is capable of delivering, what that capability level is.

There was an example or two that were thrown out about just from a coding perspective. How much the original AIs oftentimes were designed for coding. It made me really rethink everything in terms of timelines, in terms of how things can be scheduled. Yes, it's going to be disruptive, just like electricity [00:12:00] was disruptive to candlemakers. But you know, there was an adaptation and they went into different elements of lighting. I think that's kind of where we are. For leaders, we sat there and we recognized that we have to act now.

Are there potential harmful threats to business and society? Yes. Are there those same issues that could impact business? Yes. But the biggest takeaway, from that learning beyond the technology, how we have to rethink is that if you do not do this, it was pretty bleak. Basically, it's obsolescence. You're going to be obsolete if you don't lean into this from a company perspective and start to figure out how AI is going to work for you.

That to me really was what I walked away and spent the next week thinking about was how we adopt it.

Erik Martinez: Yeah. I think for me, I remember part of the talk from Megan Anderson, who is the head of marketing at Jasper, and she brought out these three points. In advertising, often the biggest budget wins. In content marketing, [00:13:00] often volume content wins. But with generative AI tools, the best ideas win. What that means is, all of a sudden, you have to compete on your innovation, and you allow the AI tools to help you implement whatever vision you have.

Humans are the center of all of this really amazing technology, but the tools are just tools. They can't do it on their own without human input and human thought and human innovation. And so whatever business problem you go out to solve, for us at Blue Tangerine, it's how do we do our work faster and better? Higher quality at a better pace. If we can do that, the outcomes for our clients improve. So, how do we go about solving for those particular problems?

And I just used one small example with the [00:14:00] recording tools that summarize the meetings. Many of you are clients on the podcast and you understand it's frustrating when your agency partner or your technology partners don't respond to you quickly, or don't follow up on the things you just talked about in that meeting. So, these tools help us with some of those things. They don't replace us. They help us with some of those things. So, Tim, what do you think is the most important fear to overcome when it comes to AI?

Tim Curtis: The most important fear to overcome with AI? Well, clearly the most important fear always comes from a place of personal, right? Overwhelmingly what you hear is, it's going to take my job. It's going to take my job. Really good example that was shared and I think it was Chris Penn actually, who shared this.

In 1746, spinsters spun [00:15:00] fabric into threads. In that year, the spinning Jenny was put into action, which basically was a large spinster that I think it said it automated the work and could do the work of up to ten spinsters. It was a master labor job and this development of technology brought it in to the mainstream. So, nine spinsters are now out of work, you know, one spinsters doing the job on the spinning Jenny, but additional work was needed for weavers. And so those spinsters became weavers because output increased. Thanks to the spinning Jenny, they were able to output more, so the job shifted a little bit.

But it still goes back to that Maslow's hierarchy of needs, right? The survivability. How am I going to survive this evolution? And there's a lot of people who have real, real deep seated fear about that. We have to look at what the impact is going to be and kind of come alongside and help assure because your'e right in your statement a few minutes ago.

On its own, AI is not capable [00:16:00] of outputting the best. It really takes the human ingenuity and the human creativity to work alongside AI. The term they're using for that, by the way, is augmented intelligence, and it's the combination of human intelligence and artificial intelligence that results in augmented intelligence. So, for me, that's the fear that people keep vocalizing.

There's also fears of weaponization. And I think those are very real fears. But it's not any different than perhaps, the advent of nuclear technology. Right? There's a definite fear and negativity in terms of the output of nuclear technology, which, of course, is atomic and nuclear weapons. But then, of course, there's all of the beneficial elements. You know, energy, nuclear medicine, space flight, all of those things that have come out of that as well. So, that's kind of where I think we're living.

But that basic human fear of being replaced continues to be what's voiced most. And I think that's why, as leaders, we have to bring our teams into that embrace of artificial intelligence and [00:17:00] allow them to play with it, to understand how it can benefit them in their roles. I keep coming back to that because I think that's what is the number one fear that seems to be cited by everybody.

Erik Martinez: So, Tim, this is an evolving and complicated environment and it's evolving very rapidly. What can a company do to get started? What's the very first thing, in your opinion, to get started in learning about AI and thinking about how to deploy it within their organization?

Tim Curtis: So, I think the first thing, and this is what I tell clients. For a little context, not only do we have the execution engine within the agency where we handle campaigns for people, but we also have more of a strategy group. And included in that is what we call a CMO practice where basically we go into the client's organization as a chief marketing officer. Sometimes we'll go in in a, what we call a chief strategic officer role, where you don't have the [00:18:00] personnel responsibilities of a CMO, but you're still delivering this strategy.

In those conversations, where I typically start is just like you're trying to make a sale through your website. It starts with awareness. So, going to the places where you can become aware of AI and aware of what's happening. That includes going to something like MAICON, spending your time by going out to the Marketing Artificial Intelligence Institute, which is the sponsor of MAICON, and really understanding what's capable.

They have some pretty cheap, I think, and one of them is actually free, intro to AI for marketers. It's a webinar kind of deal and you can kind of start to begin to be a little bit more familiar. Paul Roetzer and Mike Kaput from the Marketing AI Institute did a book, Marketing Artificial Intelligence: AI, Marketing, and the Future of Business. Both of us have the book. I think you just got the book. I've read it and it's kind of my guidebook in terms of, from a marketing perspective, where AI can be used.

[00:19:00] Once you start to get a sense of that, the first thing you need to do internally is to set up that AI council. Probably getting a small start, a core nucleus of people from a few disciplines, people that also have some intellectual curiosity around AI and learn together. Take some of those steps together. Read the book together, start to really get on the same page in terms of the capabilities.

Once you expose yourself to that, and you have the awareness, you then begin to look in different areas of the company for how you can map out your current workflows. Whether or not you have technology in place that manages workflows, you will have them. You will have workflows. They just haven't been documented. Documenting those workflows and what that process looks like can begin to give you a sense of where AI could potentially come in to help do some smart automation.

That's my approach to it. It seems to be working. You do hear people that say it was an easier to digest way to start. Again, because this is heavy stuff. [00:20:00] You can feel pretty overwhelmed quickly if you don't take small methodical steps like that. What about you? Have you had any thoughts on that or engaged in that way?

Erik Martinez: For us, the big question is who in the organization should own this. You know, one of the things I learned last week was somebody has to be the champion of the technology. And it doesn't matter what it is, what initiative you're driving in your business, somebody has to be champion of that initiative. In our organization, it's going to be me. And now I'm having conversations with my leadership team about things that we should be trying, things that we should be testing.

We haven't yet formed our AI council, but I think for us, our AI council is going to extend not only internally into the organization, but externally with the partners that we work with like CohereOne. Really staying in tune with the Marketing AI Institute and [00:21:00] some of the slack groups that they have as well. As Tim said, this can become really overwhelming. I attended a session that was 45 Tools in 45 Minutes. There are literally hundreds and hundreds of tools now out on the market that are using some level of AI.

So, if you think about that, that touches every single type of operation you have in your business. This conference was focused on marketing, which is what we do, but there is technology that impacts operations and product management and accounting and finance and all of those wonderful things. So, you could dive really, really deep into this and get lost in a sea of, wow, there is way too much to know here.

So, we're starting simply. We're having some conversations say, Hey, each department, I want you to try a tool and test it against what we're [00:22:00] doing today. See if it actually helps us do that better or not. Did we get a 50% improvement? Did we get a hundred percent improvement? Or is it off the charts? Or did we get nothing? We need to do some experimentation within our businesses in order to understand.

A good example, I already talked about the meeting tool, but another one that we are looking at is there is a tool that will take video and audio content and allow you to break it up into marketing campaigns into snackable content that you could then deploy in your social media in a matter of minutes. Not hours, minutes.

There's tools out there that can take a base version of an ad and create every other version that you need of that ad for the different places that you need to place those creatives. That's powerful stuff. And it reduces the burden on your [00:23:00] team if it actually works the way it's advertised. It reduces the burden on your team, wasting hours and hours and hours of manual labor to create those things and allows them to focus their energy on actually creating better content, better ads, not just doing the production.

Those are tools that you can find and we'll give you a short list in our show notes to talk about and look at. But those are ways that you could test the technology in small, relatively safe, relatively risk-free ways within your organization. And that's how I would start because that's how you're going to learn. And I agree with Tim, you need to go to the Marketing AI Institute and read their blogs and take their education courses. As he said, they're free.

Pick up the book by Paul Roetzer and Mike Kaput. Just start learning a little bit about it, and dedicate an hour or two a week, if that's all you have, to this endeavor and try something.[00:24:00] Tim, as we start to move to wrap up this episode, what are the last thoughts you have for our audience?

Tim Curtis: Kind of been thinking a little bit about this. You talked about the importance of finding someone to champion that. In some cases, it may be you that champions it, you build a team around you. In other situations, you find somebody. The big takeaway for me here in terms of finding somebody who has an intellectual curiosity about AI and is capable of leading understanding and adoption. Someone has to be the point person for AI technologies, and it's someone who has a motor and an appetite for academia insights and knowledge acquisition. They're driven by the pursuit of this. They want to get engaged. It stimulates their mind.

For leaders, regardless of where you are in your career, this is going to take some work on your part to dive in and become more intellectually curious yourself about AI. What's AI? What's machine learning? What's deep learning? [00:25:00] Beginning to really understand the implications of that because we are at a seminal point in technology and business. This is one of those pivot points in history, where the development of this is going to radically alter the landscape. We all bear responsibility to play that out. But it's going to be very, very important that we find the right people, whether that's ourselves or members of our team, to help drive this along.

Those are really the biggest elements of what that person needs to have, and they also need to be able to communicate well. They need to be able to effectively translate this vision to people who don't have it. At the end of the day, to me, that's the biggest takeaway about where we go from here and sort of leaving the listeners with something that they could ponder. Curious. What's yours?

Erik Martinez: I'm 100% with you, Tim. Dedicating an intellectually curious individual to discovering AI and helping solve business problems is really the critical role. In the [00:26:00] methodology that we have adopted here at Blue Tangerine just within the last couple of weeks, is that we're going to tackle small business problems first. Try these tools and focus on making something better before we move on. And it really is gonna take that dedicated person. But here's the thing, this person doesn't need to be a technologist. They don't need to be a computer scientist. They don't need to be the smartest person in the room. I'm not saying they shouldn't be smart. I'm saying they don't have to be a PhD in order to do this.

A wonderful example at the conference was a company called tomorrow.io, which provides weather data to companies and governments and stuff. And they use an AI driven approach to their technology. But what was really, really cool is that they're VC funded, they're growing very rapidly, and they have a really teeny tiny marketing team. And one of the four people on their marketing team [00:27:00] is dedicated to AI.

And she was a young lady who had never been exposed to this type of technology. And she, in combination with the team leaders from other departments within the organization, have managed to deploy this technology and improve the quality and the output and the pace of their marketing initiatives. It is really, really critical that you do not need to have a PhD doing this. It could be just a young person who has really, really innate curiosity and a willingness to learn to make this happen.

Tim Curtis: In that example, Erik, I don't know if you remember, the audience had to raise their hands in terms when he was giving the output of what they were doing as an organization. We had to guess the number of people in the marketing department. Easily, easily, 80% of the people in the room guessed between 75 and over 100 employees. [00:28:00] And it was what, four? Yeah.

Erik Martinez: It can be done. It can be done intelligently and it can be done simply. And you just have to put some focus on it. So, I think that's all we're going to leave you with today. There's so much to unpack and over the next few months, we are going to make a dedicated effort to get more AI oriented experts on the podcast so that you can listen to how their developing the technology and what business problems that they're trying to solve. So that you can take some of that learning and apply it back to your particular business situation. That's it for today's episode of the Digital Velocity Podcast.

I'm Erik Martinez from Blue Tangerine.

Tim Curtis: And I'm Tim Curtis from CohereOne.

Erik Martinez: Y'all have a great day. Thank you. [00:29:00]