[00:00:00] Speaker A: If you've ever felt overwhelmed trying to keep up with AI or you're unsure how to lead your team through the shift, this episode is for you. Nick Cawthon has worked at the intersection of design, UX and technology since the early days of the Internet, starting at AltaVista and today consulting with global brands on their AI integration. In this conversation, he compares the AI shift to past waves of tech transformation. Stay tuned to hear why AI isn't a shortcut and to hear about the new AI Maturity assessment Nick has built to help organizations gauge their AI adoption against similar organizations.
Hello everyone, I'm Paxton Gray, CEO of 97th Floor.
97th Floor is a digital marketing agency built to deliver world class organic and paid channel strategies for mid level and enterprise organizations. Thank you so much for joining us today for another episode of the Campaign.
The Campaign is a marketing podcast about better knowing your audience, innovating beyond best practice, and converting visitors into customers. You can find past episodes of the campaign on YouTube, iTunes, Spotify, and at 97th floor.com.
today's guest is Nick Cawthon. Nick helps design teams stay ahead of the curve with their AI transformation. He has been curating self assessments for UX and design teams at Gauge IO. His goal is to help analyze industry trends and remove barriers to adoption.
Nick founded Gage in 2001 in the San Francisco Bay Area to help organizations with evidence based strategy and product decisions. Clients have grown to include Electronic Arts, Genetech, Airbnb, Adobe and many others.
Nick is a professor in Data Literacy and Visualization in the Design Strategy MBA program at his alma mater, California College of the Arts. In this episode, we are going to cover why most AI adoption struggles come down to culture, not capability, what AI Amnesty is and why your team needs it. And we'll cover how to evaluate and upgrade your team's AI maturity without blowing up your current workflows. Plus, Nick is going to give us a sneak peek at a new tool he's been building to benchmark where your team stands in AI Adoption Curve and what to do next. Let's get into it.
All right, Nick, thank you so much for joining us today. I'm excited to talk with you.
[00:02:26] Speaker B: Hey Pax, thanks for having me on.
[00:02:29] Speaker A: So I think it'd be great to talk about your maybe career and what you're doing today as the context for this conversation.
[00:02:38] Speaker B: Yeah, I have been fortunate enough to be raised in the San Francisco Bay Area. I came out of school in the late 1990s.
I was a child who had exposure to the early models of Apple computers Being in our backyard and in coming back from university there was this upswing of this thing called the Internet where in the garages and workshops of Silicon Valley was starting to really take hold in the industry, amongst the community, amongst my fellow graduates. And I remember coming and sitting home at the dinner table and telling my dad, hey, I got this job at this company called altavista and look how much I'm making. And my dad was in the last five years of his career as a university professor and he said, you're making more than I am now. At the end of my career, you're making it more than the first job that you've gotten out of college. Now that job didn't last for more than 18 months because as the nature of the Internet and.com boom and bust, you know, things happen and AltaVista becomes Google and the rest is history.
But it was that kind of upswell and feeling that there's change at foot that I'd love to talk about from a strategic perspective today because I feel that there are similar motions going on 2024, 2025.
And that's really exciting to me to live it all over again.
[00:04:02] Speaker A: I love that. Let's talk about those motions. What do you feel like is going on that's similar to those days?
[00:04:07] Speaker B: Yeah. If you've ever flown into San Francisco International Airport and taken the short highway ride into downtown, it is this array of billboards.
And somebody who travels frequently and see these billboards often, there is a certain amount of groupthink and echo chamber that happens on these billboards where every six months there's a new buzzword.
I'm sure you can name as many as I can.
Cloud, Bitcoin, NFTs, Edge, Peer to peer. It's all this sort of cycle of people who want investment for their companies buying a billboard or using the buzzwords that they know are going to get investors excited and the technology that we're still trying to grok and understand how it works. And so naturally I myself and others were jaded to to what this hype cycle was going to produce because say what you will about Bitcoin, it hasn't really changed my life very much. Not a speculative guy, regardless of what you might hear. And, and so with AI, it really wasn't anything that registered up until the ability to see the wide ranging impact that it could have, the breadth of acceptance potentially that it might have across different kinds of organizations and workflows.
It felt different. It feels different.
And that is something that is fairly new at least in my world, I've worked with language models and a lot of research, qualitative data and how to parse things that are normally imperceptible to human beings as a measure of strategy and design decisions.
But this is our ability to now transform our workflow. Pax, you're old enough to remember Digital Transformation 1.0 when we went from pen and paper to spreadsheets and word docs and how there were those who said, I think I'm just going to stay the way I am and keep my business comfortable.
Then 2010 gentleman by Luke Wrobleski gave this quote about mobile first and and from a UX and design community. It was this mind shift of we're not designing for 640 x 480 screens anymore. We're designing for a new handheld device and a new medium and a new form factor. And so as we think about interaction design and UX and marketing and positioning and media, like, how does this mobile first mantra start to shift our approach and our strategy to digital?
And then lastly, this notion of, well, what if there is no interface? What if it is a language model instead of a ui? And how does that position the way we position ourselves and our brands?
[00:06:55] Speaker A: Right. Yeah. I mean, ChatGPT's agent that just launched a couple weeks ago has implications, like some pretty big implications for the future of the Internet as that continues to develop.
I'm reminded of Seth Godin famously tells this story of when the Internet came about and he said, Larry Page and Sergey Brin, they saw the Internet and said, let's index it, let's build a search engine.
And then he said, what Seth Godin was working on at the same time was an index, but it was a book and it was like a catalog. And he said, they saw the Internet and said, let's build a search engine. I saw the Internet and said, let's let me, I'm going to write a book. And he said, you know, guess who won? Obviously them.
And so I, you know, that brings to mind this concept of you can't look at the new with, you know, the eyes of where you've been, like a complete clearing of the slate and building from scratch. So my question for you is, if you were leading, leading a team within a company in this time where, you know, we're looking at potentially like a big pivot to how commerce works online, how might you build that team today? Who would you have on your staff to ensure that your organization is going to be best set up for what's Coming.
[00:08:23] Speaker B: I'm going to challenge the question because as a leader, I can't just clean slate. I've got a staff that's present and engaged and comfortable with what they're doing.
It's how would I level up that staff? How would I repurpose those skills that are already in place so that they can be upskilled for the future? Great.
[00:08:43] Speaker A: Yeah, I love it.
[00:08:44] Speaker B: We have a county of San Mateo, which is the in between SFO and San Francisco. That's the county of San Mateo, where you, if you have to do work with the county, if you want to do work with the county, you cannot eliminate any jobs through AI. There's a mandate to saying you need to repurpose the people that would be transcribing and translating town hall meetings. You need to retrain them to edit transcripts and publish documents on the web. You can't eliminate positions, despite San Mateo county being where a lot of these companies got their start.
And I, I, I love that manner of thinking because it is to acknowledge what we're good at doing as individuals, as team, and then figuring out how we can make our new tools amplify that.
[00:09:38] Speaker A: Yeah. So, and for the record, like, I feel like the clearing the slate is more figurative than literal.
And I think it's a good exercise.
Not necessarily, say, clear the slate, but to say, hypothetically, if you were starting from scratch, if you had nobody on staff, who would you need? And then say, now, with my existing staff, what do they need to get to that ideal of where we're going? And that may be augmenting their skills or maybe hiring additional people or whatever. So just for the record, that's kind of sure.
[00:10:12] Speaker B: And you used a good word there, augmenting. I think that if we look at this from a textual standpoint, is that from copywriters and strategists and those who have have to make signal from noise, is that how do you augment their process?
I have had a client come across my desk in the last six months that has a business that I know nothing about. And in a former day, what I would do is I would spend a lot of time googling and downloading files and printing them out and highlighting them, and that process has changed considerably.
Where in this case, because we want the transparency and the citation of source, the nature of the business demands it, is that we're spinning up our own knowledge base, own knowledge graph in a retrievable augmented generation. It's a rag, which is your own language model that you can manipulate and Change and have it change to be the voice of the client. And in our case citations and reference can be transparent about how it's coming up with these outputs. And so if there's anybody that works in the world of words, I'm going to say that fast three times that needs to make common sense.
To be able to augment them with a model that can amplify them would be how I would transform that aspect of it.
And that takes a junior to go and find the right sources and the right files for which to index and to tag and to put in the references so that it's clear that takes the grunt manual work of somebody that might be coming out of school and wants to know that process and how that these, these words get parsed and that there's a nor more mid or senior level to know the prompt engineering involved with trying to get to a campaign concept or a marketing concept or to see an audit. The share of the voice it's called, it's the language model's voice to know that you've got different models that say different things about different brands. And so the voice about our brand is suggesting this so we can then emphasize a strategy to amplify or to go in a different direction. So I think that kind of parsing of, of how if you believe that prompting is going to replace searching in the next five to 10 years and this statistics show that it's, it's increasingly be being adopted then figuring out the strategy and the copy and, and how to position it is is going to be something that I would train on that side of the coin.
On the other side of the coin is the visual and the interactive. And that's where my world has been and it's been something that we've seen a degradation. I'll say back when I described that utopian early 2000s of this sort of windfall of a new medium called the Internet, subjectivity was running rampant. And your design was awesome because it has all these skeuomorphic leather patterns and it looked like this and it felt like that. And everybody had their own subjective expression of how they wanted the Internet to look.
It was beautiful and it was weird and it was very non standard.
But with mobile, with the consolidation of the industry, with the commoditization of design and interaction design, things began to take shape in the form of patterns. And Google began Project Kennedy which was to say if it's a Google product it has to look the same, it has to follow these patterns. And Microsoft had the same thing and IBM had Carbon. And we've seen these patterns get figured out, whether it be tab rows or buttons or dropdowns. There's just a standard now to how we communicate visually on the web, and I, I think even more so, which is a separate conversation about how we design for agents versus human beings. But as we stay in the sort of building of a team to know what tools are required for which place in the process, wireframes are now at our fingertips where if we don't want to attach to a brand extension visually and we just want to showcase the. The structure of the app, that can be done in minutes or hours rather than days or weeks.
And so a technologist, a digital technologist that knows creatively, here's how we go from this part of our thought process of how might we design for something to near production ready code is something that I think is an essential skill set for visual designers. I had a conversation with the creative director, executive creative director. This Guy's in his 50s, he works in New York, and he came into a freelance gig at another agency as he's in between jobs.
And he said that he brought in image generation tools like midjourney in the storyboarding concept, where he was amplifying his own process to showcase ideas for, in this case, TV campaigns, and knew how to keep the characters consistent in between shots of the storyboard, which was something that was hard to do maybe nine to 12 months ago, and was able to feel like he had a much better generative process of. Here's all these ideas. And I know I've been rambling for the last minute or two, but I want to punctuate this with a concept that one of my colleagues, Jesse James Garrett, had mentioned just last week. And that's this notion of amnesty, of AI Amnesty, in whatever field or process that you're in, is to allow it not to feel like you're cheating because you do these things, because you do this thing is to be transparent and be a mentor and to be questioning of the process and to say, look, we're trying to figure out this transformation together.
I'm not making it seem like anything other because amnesty is important for adoption.
[00:16:30] Speaker A: Yeah, I think that's a really good point. I've been talking with some people about that concept of adoption within a team.
And amnesty is not one of the points that has been brought up.
It's been presented as kind of like endorsement or in some cases, kind of like mandate, which I don't necessarily love. But that concept of amnesty, I think.
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[email protected] LetsTalk what's up guys?
[00:18:15] Speaker D: Nathan Hooper here, account executive 97Floor and today I'm bringing you the latest in marketing and AI news.
First up, is your e commerce site ready for AI shoppers? A Swiss business leader recently ran an experiment where he had ChatGPT agents try to shop on the top 50 e commerce sites in Switzerland. The biggest sites in Switzerland. Many of these sites were blocked by captcha settings and robots txt files. If you're running an e comm site, now is a good time to check your captcha settings and robots txt to make sure you're not actually turning away AI powered shopping as this continues to pick up momentum and become more and more popular. Next up TikTok. They are making it easier to track what happens after someone clicks on your ad. They just rolled out what's called Engage Session new tool for advertisers without using a pixel.
It shows whether someone spends at least 10 seconds on your site after clicking on an ad. This is a huge deal for all businesses targeting gen Z where TikTok has become the search engine of choice. The results so far of using Engaged Session are showing lower ad costs and longer site visits. Absolutely worth trying this out if you're running ads on TikTok. Finally, podcast ads, they are exploding. New research is showing that 78% of markers are now advertising on podcasts, up from 59% last year. And listeners are engaged. Most people are catching up on missed episodes, and the average listener is following three different shows each week. If you've been thinking about podcast ads but you haven't taken the plunge yet, now might be the right time to get started before it gets too popular and too big. Hit us up. Nicenout fl.com let's schedule some kind of chat about how we can take advantage of this growing channel. Now back to the show.
[00:19:55] Speaker A: They also talked about dedication of resources.
And I still have. I feel like I've seen within organizations, when you have leaders stand up and say, hey, listen, please, please use AI. Please use it. Here's resources to use it.
There's still resistance and friction to it, and I've been wondering about where that friction can come from within teams. I think there's going to be some, you know, a concept of inertia that they have to fight against.
There's also incentive. You know, I think it's extremely inefficient to begin with. Even though the whole promise of AI is efficiency, it starts off as very inefficient as you start to figure out how I can use this. So overcoming that hurdle.
And then I think there's potential for a lot of people in the workforce to feel like, well, why do I want to drive this forward when it seems like the end game here is you don't need me anymore.
[00:20:57] Speaker B: Yeah.
[00:20:58] Speaker A: You know, so, like, what's the incentive ultimately for them to help pioneer this? And how do you overcome those? So I'm curious, have you seen that same friction? Why. Why do teams still not kind of, like, dive in even though they're given, like, permission, they're given resources to do it and asked to do it. Like, what. What else causes those that resistance?
[00:21:18] Speaker B: I. It's hard. I. As anybody who's tried to cheat on a test, it's hard to cheat. You got to sort of like you're worried about it and you're fighting against it.
Using these generative tools to make the fidelity of the idea that you want to communicate is extremely difficult. And it's a learning curve, and you have to stay curious and patient and confident that your. Your process will see Its way through to an end deliverable, that makes sense, but the next time it'll be faster and the next time it'll be faster and next time. So there is a fallacy of speed with this technology. And I may be so I may be talking too general because there are so many different tools within this tool belt, but there is a fallacy that we can go much faster. Now it may be true in five years that productivity scale may, may increase drastically, but that, you know, that notion of, that notion of speed will be automatic, I think is not quite true yet. As for the resistance, the story I'd like to tell is I, as consultant, as an agency like yourself, we get exposed to a lot of different people who have different backgrounds. And there's one that I work with that doesn't trust the cloud.
And that wave of transformation with SaaS products and cloud based platforms was one that she met with, with distrust. Much like you see a lot of people not trusting these tools, these generative tools or the transparency and privacy aspects of them, is that when working with this individual, it had to be attachments to email, it had to be version file. There needed to be a trust of seeing an icon on a deskt and knowing that your data is safe. And so I think that we're feeling that same thing as like, no, in this case it constrained her because she used spreadsheets for time tracking and budgetary needs and things that now there are CRM platforms and management software that can take the place of a cell based approach. Her tool set was much more limited. I think the analogy is true again today, now, 15 years later, after maybe that cloud transformation was taking place, is that there are things that can do this for you much faster if you allow that trust and that transparency to be a suspense of disbelief.
[00:23:39] Speaker A: That's interesting, that cloud transformation, yes, I do remember when that was big and that was everywhere and people were moving to getting their servers out of their buildings and that was big. And today it's not even talked about, you know, like people entering in the workforce, many of them probably don't even realize that they're in, you know, everything's in the cloud. But yeah, I mean if I were to throw my laptop away, I literally lose nothing other than the inconvenience of having to replace my laptop. But no data whatsoever is stored locally.
And so that leads me to this, this thought of, with AI adoption and staying ahead of the curve, the common advice is to say take what you're doing and see, you know, what can be augmented by AI And I, I don't think that's wrong.
But what's not sitting well with me on that is when we, when the Internet came along, there were people who said, okay, can I take what I'm doing? And what. How can the Internet play with that? And you got these kind of like weird, archaic kind of versions of websites that, you know, eventually a generation came along and they didn't say, what can I do with the Internet? It was just, the Internet is what is. It's like it was a complete paradigm shift rather than an application of technology, if that makes sense. So, yeah. So I'm wondering, is there a way to shortcut that in your mind? I mean, I don't know if anyone really has the answer. That's kind of a big question.
But what's the best way to kind of approach that and not get left behind?
[00:25:21] Speaker B: Yeah. Not to be that generation that. That old man. Old man on the porch who shakes their fist at clouds.
Not, not cloud computing. Just cloud.
[00:25:31] Speaker A: Yeah, great.
[00:25:32] Speaker B: Clouds in general.
Yeah. It's interesting. I've got two young boys here, and their first exposure to technology is a voice assistant, which within the next couple of months is going to have Gemini built in where it can do more simple things than turning off and on devices within our house.
And with these adoptions of a lot of these agents, a lot of the instructions are coming through voice. There's certainly been a trend on Mac Whisperer or speaking to an algorithm to execute a prompt versus typing it out.
And it's interesting to see a younger generation being increasingly detached from the awkwardness of pointing and clicking and typing and having a mouse. And I alluded to it earlier about this. Are we designing for agents or are we designing for humans anymore? And with this notion of, well, you know, there are services that we can stand up and execute while we're walking around our daily lives.
That's a big leap of faith for me.
I like the point click, drag type metaphor that I've been doing my entire career, but there are others that, that may reject that. And so my, my level of patience and adoption. I like to consider myself somebody who, who's at the adopting edge, but I don't, I don't know how to overcome those internal perceptions of I'm not ready for this or I'm not comfortable with this.
Going back to the organizational standpoint, I think what we'll see now is greater collaboration between departments where if we have traditional agencies and development shops, if we're all going to be swimming in the same pool Using the same tools, there's going to be a much tighter iteration of how is this working, how does it affect this? And it's not so much of a handoff anymore as it is a side by side and a self mentorship. To say this is how I would see this working and this is how it's actually working that's been crucial for me over the last year is to have that mentorship of application development and UX development and all that prototype stuff that I didn't traditionally have to worry about.
[00:27:53] Speaker A: Yeah, tapping into group, kind of groups of minds is going to definitely help us move faster. And you have been working on a tool to help teams. Do you want to tell us about that?
[00:28:08] Speaker B: Yeah, I'll tell you about it from a couple different levels like design are my people UX and interaction design is what I know and I, as you alluded to about the organizational leader who has to look at what their team looks like.
I was coming off an engagement where I had a profound sense of dread for the design team.
I was brought in by the VP of Product.
I use generative tools based upon the code base of the company to create production level prototypes that we could test and sort of explore the UX around and was able to skip the whole FIGMA process.
And they had a team of eight to 10 that were used to that manufacturing process of abstractions, of interfaces for which were to be handed off to developers.
I said that flow is resource intensive and slow and low fidelity.
How do you get an assessment of where they are in their maturity, AI adoption maturity and what kind of barriers might be in place and what kind of recommendations you could make in terms of training and adoption for that.
And so that was the impetus of to say, look, these are my people and don't let them out, don't leave them to die. Like, make sure that they know where they can, where they can be improved. And that's the retraining aspect versus the redoing.
And so it's been an examination of what kind of recommendations and comparisons can be made across industries, across similar team sizes and organization sizes and then the categorization. Is it culture?
Is it fear? Is it the process is that the data is not right? Is it that we don't have integrations into other services so that we can use these tools? And those are some areas of investigation that this survey goes into.
Um, now that being said, I've taken it on myself to spin this up using generative tools and seeing where that fault lies, especially in the qualitative Responses about motivations and reflections.
And so that's been a learning process for me as well.
[00:30:31] Speaker A: So what is the output for somebody taking this survey? Like what can they expect to gain from this?
[00:30:39] Speaker B: Well, that's a great question, Paxton. It's never going to cost money to take, but the reflection is going to be where we stand as an industry. Where do I stand as an organization or as a team? But what are we seeing industry wide based upon levels of seniority, based upon size and to be able to say this is something that we're finding in common. We can segment our answers and our responses to say that this adoption is occurring here among sizes that have the resources, are they nimble enough to be able to adopt new tools or are these enterprise companies just able to take it on the chin until that workforce turns over and maybe they bring in those new perspectives and new tools and change from within.
[00:31:21] Speaker A: Interesting. So what are the main areas that you're evaluating in this survey to measure whether or not somebody is like AI ready?
[00:31:31] Speaker B: Yeah, first of all, what have you done currently? Are you doing it in ideation or are you currently going workflows? Are you using it in production? And so that understanding of what's current landscape, there's also perceptions of reasons of why this isn't working. Is it the process, is it approval?
I talked about the data, the maturity of how you can integrate design, UX design team tools with other portions of your agency. Is it a licensing thing?
Are you just able to use Copilot? And that's the extent of your exposure because your enterprise has that relationship with Microsoft and there's really no room for all of these startups that are now pushing, pushing, pushing innovation at a very fast rate.
And then lastly, this notion of culture and you and I have touched upon it in our conversation of like we've seen cultures resistant to change, not feeling like they have amnesty to fail or to try or to to innovate on their own and that are there ethical considerations with the use of AI at their organization and if so how. And I try to ask for some success stories as well as some failure stories and get some opinions on how they feel about different aspect of each of these categories.
And so it gives you a nice tidy score per section as well as all together and then breaks everything down in comparison to similar industry, similar organization size and similar team size.
And yeah, by the time this podcast hits your ears, faithful listener, we will make sure that the link is in the show notes and that you can contribute to the cause and we will Then again, share back out what we're seeing from a segmentation and factor analysis.
[00:33:23] Speaker A: I love it. So I have seen, I've seen the landing page for the survey. I love the design.
I haven't had a chance to take it yet. So I'm curious, are the.
[00:33:35] Speaker B: Just.
[00:33:35] Speaker A: This is maybe a little too nuts and bolts, but are the questions for the survey, are they like open text or are they a rating? And I'm curious.
Yeah, how does the.
[00:33:49] Speaker B: A good survey has a mix of both.
Has both sort of demographic questions as well as behavioral and perception questions. And then the open input, and this is a great avenue of exploration, can then start to take the language and the verbiage that people are using to describe different conditions and aspects of their workplace and use of AI and start to train itself. It's like this is how people are talking about different categories. And that's the exciting part about it to me is that again, with a model that you can have that this sort of flywheel is that to really speak in the language that you're receiving.
And I, I've looked.
That's the OpenAI integration. And I look for that to be really interesting. Is. Is how we begin to, to describe our current workplace. That transformation I love.
[00:34:43] Speaker A: I mean, that's kind of why I was asking. I was, I was curious if you're using AI to interpret open like freeform answers. It's like, man, that I hadn't even thought. The entire survey industry has an op like massive opportunities here because it's always been qualitative or quantitative and there's restrictions and limitations to both. AI kind of breaks down those walls.
[00:35:06] Speaker B: So anyway, it does. So, yeah, thank you for helping me plug that. Know it comes from a good pl place in my heart because my people are your people and that I want to see us upskill and all adopt through training and leveling up.
[00:35:23] Speaker A: Yeah.
Well, Nick, thank you so much for, for being on the show. This has been a great conversation.
What is the best way. So again, we're going to plug the survey. We will put those, when that's available, we'll put those in the show notes and make that available for listeners.
How else would you like people to connect with you?
[00:35:42] Speaker B: You can find me at gauge, IO G, A, U, G, E, I O or on LinkedIn or Medium.
I'm around.
So again, thank you for having me. It's been a pleasure to talk to you and your audience.
[00:35:57] Speaker A: Likewise. Thank you so much, Nick.
That is it for today, everybody. If you enjoyed this episode, please consider leaving us a five star rating and subscribe so that you don't miss future episodes. Subscribe Big thank you to Nick Cawthon for joining us today. You can Find Nick on LinkedIn if you want to talk with him. More about UX and AI Some major takeaways from this episode. Number one, AI adoption isn't just about tools, it's about trust. Teams need amnesty to experiment and fail as they learn. Number two, don't just plug AI into whatever you're already doing. Ask how your workflows should completely change, similar to what happened during the rise of mobile or cloud computing. Number three, you can't manage what you don't measure. Nix AI Maturity Survey gives teams a way to evaluate their current state and see how to retrain for AI.
You can find past episodes of the campaign and marketing tools and
[email protected] also, you can learn more about the agency and get in touch with a marketing specialist if you want support for your own marketing campaigns. That's all for now. Thank you for listening and we'll see you back here next week. Until then, keep innovating, keep converting.
[00:37:00] Speaker B: SA.
