Marketing in the New World of AI: Embracing the Future While Staying Human

In a world where AI isn’t just a tool but an autonomous collaborator, marketing is on the cusp of true reinvention. Join Authentic’s Chief Marketing Officers and AI experts as we discuss how to move beyond automation and content generation to explore the rise of agentic AI—systems that plan, optimize, and adapt campaigns in real time, working alongside human strategists as creative confidants and decision-making partners. 

This session unpacks how marketers can go from scaling efficiency to orchestrating entirely new experiences, discuss novel approaches to hyper-personalization and omnichannel integration, and set the stage for building trust in AI-driven brand strategies.

Key Takeaways

• Strategic decision-making requires insights that AI cannot provide, necessitating human expertise in interpreting data and context.
• AI’s unprecedented speed in testing allows for rapid strategic iteration while emphasizing the necessity of human understanding in business fundamentals.
• AI adoption is advancing rapidly in small-medium companies compared to enterprises.
• AI tools can categorize and analyze large volumes of content quickly, revealing patterns and gaps that inform future content strategies.
• Organizations should weigh the risks and rewards of using public AI tools against the need for privacy and data security, implementing guidelines for responsible usage.

Webinar Transcription

Opening & Context Setting

Jessica Berg: Hey everybody. Welcome. I know we have a couple super punctual people on the line already, so we’re so excited to have you with us and I will maybe give it a minute for other people to join and then I’ll kick us off. But really excited to have this conversation. Hope you’re all having a great Wednesday. 

Okay man, here we go. So we have a really chill, jam packed conversation to fit in here. So I’m going to get started and just let folks trickle in while I introduce the topic and get our panelists introduced as well. But welcome. You have arrived in the Authentic while staying human and I’m super excited to have this conversation. My name is Jessica Berg. I am the Director of Business Development for Authentic and I get the distinction of having the distinct pleasure of working with our Chief Marketing Officers and meeting with CEOs and leadership teams every day and week to talk about their business issues. And AI comes up multiple times a day. 

So this is really timely for me and I know each of our panelists has a great perspective to share and everybody has a slightly different angle on this work and the cultures in which they’ve done this work. So that’s going to be fantastic. Just from a kind of housekeeping note, we did some prep for this and noticed pretty quickly that nailing the breadth and the depth of this topic is tough. So I’m going to be doing my utmost to keep us on time and just acknowledge that every single one of these questions could be a whole webinar. So please feel free if there’s something that you want to go deeper on, or if you have a question about, feel free to leverage the Q and A feature at the bottom of the webinar screen to add questions in. 

We will save time for dedicated Q and A at the end, but many of you submitted really thoughtful, fantastic questions in your registration. So I’ve got some Q and A teed up already. We’re ready to go for that. But don’t hesitate to add new questions if something occurs to you or you want us touch on something more deeply. And we will do our best to cover as much as we can. I’m going to let the panelists introduce themselves and so I will touch on you to go first, Ruth. 

Ruth Glaser: Okay, great. Thanks, Jess. Hi everyone, I’m Ruth Glaser. I’m a fractional CMO with Authentic and I work primarily with small to medium sized businesses, so that means I don’t have the luxury of theoretical marketing. You know, everything that I do has to deliver measurable results and it usually needs to happen yesterday and it usually needs to happen on a really small budget. So I’m sure a lot of you are dealing with similar things. Over the last 20 years, I’ve led marketing for everything from tech startups to hospitality companies to retail brands. From launching new businesses, I’ve helped grow brands and even help companies expand into new markets. So what I’m really excited about, Jess, with this AI moment is that the tools that used to require enterprise level budgets and dedicated teams are now accessible to literally anyone. 

So it’s really exciting to be on this webinar with you all and I’m looking forward to sharing how we can deliver some of these Fortune 500 level marketing strategies at SMB scale. 

Jessica Berg: Amazing. Thank you, Ruth. Jenna, how about you go next? 

Jenna Gilday: Hi, I’m Jenna Ttetje Gilday. It’s nice to meet you. For me, there’s really two things that have driven my career. And the first is I love solving interesting consumer or business challenges. And the second is leading through change. So for me, I’ve intentionally worked in a breadth of different industries. Everything from automotive, apparel, beauty, consumer packaged goods, financial services, E commerce and retail. And this includes early in my career I worked agency side for agencies like BBDO, Fallon, Carmichael Lynch, on a variety of clients including Harley Davidson, Citigroup and Hormel Foods. Then after earning my MBA from the Carlson School of Management, I switched over to the corporate side. So I’ve spent the bulk of my career really focused on driving brands, products and services and business results for large corporations. 

This included at Target I was a Director of marketing, Wells Fargo where I served as a senior Vice President and head of Brand strategy and then@chewy.com where I was the head of integrated marketing. 

Jessica Berg: Thanks for being here Jenna. And Carter. Last but not least, awesome. 

Carter Jensen: Well, thanks so much for having me, Jess. My name is Carter Jensen. I lead curriculum and innovation at the Uncommon Business. The Uncommon Business we focus on bringing AI to life for small to mid sized companies. And we find that this is just an incredible time where businesses of all shapes and sizes are really finding unique ways in order to leverage this to really get ahead. As you mentioned Ruth, before this role I led AI innovation and acceleration in marketing at General Mills and so was there for the last five years, really riding the AI wave, integrating that across the organization and recently left there to join the Uncommon Business as we continue to grow. So very excited to be here and thanks for having me. 

Jessica Berg: Thank you. Yeah, it’s been really fun. We have learned a ton from the Uncommon business ourselves at Authentic and just everybody is trying to learn as fastly, as fast and efficiently as they can as all this stuff changes around us. So thank you for taking the time to be part of it, Carter. So setting the table a little bit for our first question, I’ll let the panelists kind of gather their thoughts around the first question. 

I’m going to tee up, but I just wanted to set the table or lean into the context of this conversation a little bit by sharing some inside baseball about Authentic, that we love, some puns and we love to joke that our CEO Jennifer is truly a gifted wordplay artist of the pace with which she can come up with catchy things or assonance in naming things, is bananas. So we at Authentic, as we have internally invested in AI tools and leveraged tools to make our client work higher quality, faster, all those things, and are deeply committed to being human, being strategic, thoughtful business leaders that value high trust relationships, we’ve started to dub our AI use authentic intelligence, not just artificial intelligence. So just wanted to share that and feel free to borrow it in your own organization if you’d like to. 

But at that, like with that grounding that it’s our goal to really help you understand practical use of AI and maybe how to think differently about the use of AI as a marketer or in your organization, while also, you know, keeping that humanity first, like making sure that you’re not losing the real brand and the culture and the voice of your work and the people you are serving just by diving so far into the automation technology that you lose sight of those things. So I’m going to kick off with maybe a basic question of, for a panelist, how can marketers shift their AI use from just being a productivity tool, like doing the same things faster, into being really a thought partner or a strategic tool to work differently. 

And I’ll maybe tap you again to go first, Ruth, in that I know in some of your client work you have used AI to analyze competitive data differently or to really frame your content strategies at clients differently. And I would just love to have you maybe kick off and share some examples. 

Strategic AI Implementation vs Productivity Tools

Ruth Glaser: Yeah, thanks. Well, one of my very favorite examples is a client they had been blogging consistently for I think it was eight or nine years. So that meant they literally had hundreds of blog posts. And you know, prior to AI, a comprehensive content audit would have required me to go through each of those blog posts and at least skim them. And skimming hundreds would take, excuse me, would take weeks. You know, and then I’d have to come up with the categories and put them into categories and start to look for patterns. So with AI, I was able to upload the content and the performance data. And it took me 30 seconds to get started instead of several days. What I got in return was the initial categorization of all those hundreds of blogs. And that’s where I began iterating. 

So that was just the first step. And I started to ask which of these topics drive engagement versus conversions? Where are there gaps in our content in our funnel? And each question got deeper and got us closer to real insight. So in a few hours of that back and forth, we’d identified several really solid content pillars and opportunities. Then that became the foundation of our next quarter’s content strategy. So that’s really what I mean by an AI architect. I’m not just using it to save time, though it did save me literally weeks of time. I’m using it to expand what’s possible. 

So instead of, you know, spending all that time on data, gathering data, you know, just some of the input, some of the admin type things that you need to do, I get to spend my time interpreting results, thinking about strategy and really focusing on client growth. 

Jessica Berg: That’s awesome. Cool. I think either of you could go next, but do you want to kind of expand on that, Carter? Because I know you’ve seen a lot of different client use cases, good and bad, for these types of projects. 

Carter Jensen: For sure. Yeah. And I’ll double down on what Ruth said. It’s a great example of how, you know, you can take a huge amount of data, really synthesize it down to take action. I’ll kind of hit on the competitive side, which I think has been really interesting specifically in the last six months. We always leverage a variety of AI tools. And again, the common theme you’re going to see throughout this entire conversation is, and Jen and Ruth both talked about in their intro, these are $20 a month tools. This is not some enterprise magic that you have to pay thousands of dollars a seat for. But what we’ve actually employed is using both GROK and Perplexity. 

And the reason these are interesting is because they have access to really kind of real world data, whether it’s through the X platform or through online in just a little bit of a differentiated way than ChatGPT does. And what we’ll do is we’ll run competitive reports for our clients every single week so they can understand exactly what’s happening in the market for not only their competitor, but also their target audiences, which is really interesting. And what that does is it allows you to get out of that anxiety circle of what’s everyone else doing? I’m so focused on my business, I didn’t get my head out of the sand. I need to look around and what are we doing? 

And just getting that cadence of research and that cadence of really kind of that understanding has been differentiated for our clients to start to actually see what are new opportunities that you might have missed in the market? What’s shifting out there that you need to react to? What are your competitors doing that you might not have thought about? And the most important, how can you differentiate yourself from your competition while also serving that shifting consumer landscape in an interesting way? So again, taking what Ruth said, looking kind of backwards and categorizing it and then even making that better by looking forwards into unique consumer insights that you might have missed as you’re so focused on building your business. 

Jessica Berg: And Jenna, for like, one of the best examples that you shared when we were preparing for this was around that just bigger organization challenges with sometimes implementing some of these things that there’s maybe the desire to. But there’s more policies and procedures to be followed. Can you speak to that a little bit? 

Jenna Gilday: Yeah, I can talk to a couple things. And I think one thing, like a big company, they can decide what they want for a job. They could buy new technology. Right. They could customize things more easily. But as you start to think of the implementation, just the peer infrastructure and hierarchy does create some challenges. So as you think of, if you’re a large organization with multiple business units that are structured differently, you’re going to have pay grades and job descriptions. And as you start evolving in what you’re doing, they want to make sure they’re doing that in an equitable way. Right. So there’s just the time of determining what is the structure, how does that impact the employees, the roles, how do you define those? And so there’s a bit more planning and transition that needs to happen. 

The bigger the organization is, the other component is looking at the upscale of talent. Right. So if you’re adopting new technology, how are you training people? If you have several hundred thousand employees, it is going to take time to get everybody where they need to be. And there used to be kind of a guideline when I was on the corporate side, as you think of big changes, the kind of 20, 60, 20 rule, so 20% of people will totally embrace change. And they’re all in 60% of people are going to be a little bit hesitant and it’s like, what does this mean for me? And 20% are really going to be against it and fighting it. 

So as you think of managing those varieties of points of view through change, people are going to learn at different paces and need different levels of engagement. And then I think just that balance between the speed and the responsibility of implementation, as you think of being responsible and accountable to your employees, is something to consider. And then lastly, there will be roles through AI that can be eliminated, but there might be new roles that come up too. So as you’re thinking of how you are structuring, how are you redefining expectations? But in a big organization, just being really clear in those expectations, clearly defining the roles, providing the training to get there, to create that path forward, to get everybody to the right kind of starting point. 

Ground-Up vs. Top-Down AI Adoption

Jessica Berg: Yeah, that is fair. When you’ve got a big team and not everybody is on the same path of excitement, adoption, all those things. So yeah, I guess similar area or similar topic, but taking a little bit deeper, how can you talk about your experiences or what you’ve noticed for marketing organizations embracing true reinvention as opposed to just putting AI on top of existing processes. And maybe I’ll go, let’s see, maybe I’ll go back to you, Jenna, kicking us off. 

Jenna Gilday: Yeah, that sounds great. I think, you know, as part of it is from like big company perspective, as you think of your marketing structure, if you’re relooking at your structure and you’re looking at where you’ve been the last 10 years, you might not be looking at it through the right lens because you need to think about how AI can complement the existing workforce. I think right now there’s a lot of people that think it is a supplement. Right. So here’s my job. I can do parts of my job faster with AI, but if you’re truly finding innovative solutions, AI can be a compliment. And finding that clear lane for what will I own with some strategic oversight and then what do the employees own? And less of just layering it into the roles, but finding those clear lanes where they can live. 

The other thing where I think companies can move right away is the ability to test and reiterate strategies at unprecedented speed and scale. I think the days of the traditional ad agencies taking six to 12 months from the initial kickoff to having something in the market are something that just companies aren’t willing to wait for. And it doesn’t need to take that long. This would also apply to organizations on how quickly you can respond to market changes, to kind of what’s happening in social. If you have an image problem, right, like how quickly are you reacting, how are you resonating, how are you gathering that information at a quicker speed so that you can address it? And then the last is thinking about enterprise strategic planning. So most companies have very formal planning processes, but how can AI assist in that process? 

And that can help from diagnostic tools to kind of predictive engines. So thinking of everything from identifying purchase behavior to social and cultural signals to competitive patterns, scenario planning and roi, those are all things through the planning process that at times can be very laborious. So how can these AI tools help speed that up and get to more meaningful insights quicker? 

Jessica Berg: That’s all, I mean that’s a lot, but it’s so yeah, you think of the power and impact across a whole organization, especially of those sizes that you’re talking about. It’s incredible. So amazing. Maybe taking more of that small organization view, Ruth, like, can you share some more of those competitive examples you were thinking about? 

Ruth Glaser: Sure. You know, one of the things I always tell clients is that AI doesn’t do the work for you. You still need to know what needs to get done and how to validate whatever it is that you’re producing. So the things that I reinforce with clients about the things that need to stay human, you really need to understand the business. I mean, that’s the foundation of it all. Right. You need to understand what’s unique about your business against the competitive set and then where to make the focus and the strategic decision of what you’re going to focus on. So for example, AI is not going to tell your manufacturing client that they shouldn’t be chasing social media followers right now because they’re losing 60% of their qualified leads. So it’s better to start by shoring up your sales process first. 

AI is not going to have that kind of feedback for you. So you know how it has helped me in terms of strategy development. I think Jenna touched on speed, which is a game changer, but she’s absolutely right. It makes people more impatient. It’s like how Amazon trained us all to want things the next day. AI has similarly sped up how quickly people are willing to wait to get things in the market. Some of those things where I, I really find it valuable are, you know, you can test strategic hypotheses in real time. So for example, you can analyze the competitor content patterns just like we did on our own. You could do that on all your competitors as well. 

You can identify market gaps, product gaps in minutes that used to take days, if not weeks and you can prototype some different approaches really quickly. So you know, for that if we go back to my blog analysis example, we didn’t just categorize the content. We identified strategic directions that had the most white space and that’s where our opportunity and our focus really. You know, I think the biggest thing for me strategically is that I get to explore more strategic options and present clients with more thoroughly researched recommendations. And I’ve been able to really test the parameters of what it is we’re trying to get done and how we’re going to do it before we even get to the roadmap phase and the, the planning phase. 

Jessica Berg: Yeah, I’ve, we talk a lot about with authentic that everything is a hypothesis until it hits the market even, you know, but it’s cool to see how you can do a, you can have a much tighter hypothesis if you’re able to model some of those things out or test it ahead of time. So that’s amazing. And Carter, I feel like you’re the, maybe the person who I’ve heard speak the most about the power of using AI as a strategic thought partner instead of just five minute tasks. So what have you seen in organizations where they’re really kind of adjusting or really reinventing their processes? 

Carter Jensen: Yeah, for sure. Jenna and Ruth both had incredible examples and focused specifically on a few specific use cases. For me, I have this really interesting perspective on this because I come from a Fortune 500 company where some things work, some things didn’t to now seeing small and mid sized companies really adopt it. And I think the biggest thing that teams need to try to understand and figure out is it’s kind of this. Either you come in tops down or bottoms up. Now a tops down mentality to AI is where you’re looking at very specific installations of it. 

At General Mills we launched an AI brief writer. Very okay cool. Like we launched a system that you know, makes images for. Okay cool. Those are all really interesting. But what we’re focusing on there and what actually went wrong there is that you’re focusing on individual use cases that someone’s going to tap into at certain points in time throughout their role rather than transforming the entire organization to think AI first. 

And that’s where we kind of think of this Ground up. Now, eventually you’re going to get to the brief writer, eventually you’re going to get to AI image. But if teams don’t know the fundamentals of this software, right, or of the system such as, you know, prompting and always going to AI, always trying to think of how can AI help me solve this? They’re never going to see the adoption of the benefit. And I think this is the biggest difference between arguably this is actually a true delineation of small and mid sized companies who are truly adopting AI from the ground up versus enterprise companies who can pay a ton of money for spot solutions, right? Some fancy brief writer or some fancy whatever. 

The amount of times, and apologies if there’s anyone from a consultancy on the call, but the amount of times we’ve paid a Bain or McKinsey to come in and identify the opportunities for AI, it’s endless. But you never have the adoption, you never have the transformation you’re looking for. The ground up mentality is we basically say anyone with a laptop, right? I don’t care if you’re a marketing coordinator or copywriter, whatever, you need to understand the basics because then what you’re doing is you’re starting every problem with AI, you’re starting every problem with these new tools, these new superpowers that you’re then able to take on some of the examples that Ruth and Jenna talked about and I think this gap is widening every single day with enterprises just installing their own little point slides, solutions, etc. 

You’re going to see a little bit of ROI come from those. But what a 10 person AI enabled marketing team can do, I would say is equivalent to a hundred person not AI enabled marketing team at a large corporation just because of the speed difference and because of the tools they have at their disposal at any single day. And so that’s the real delineation I see is I do see these companies who are truly going from the ground up, transforming their business with, you know, this kind of AI first mentality are just going to outpace everyone else who is trying to either A do spot solutions or B, not fully implement it in a way that’s actually going to beneficial. 

So that is the biggest differentiator and also the successful strategy here actually is a lot cheaper than the point solution because you’re spending less money on these enterprise tools that you don’t even know are going to work. And I honestly think there was a recent study that came out this last week where it’s like AI adoption at large enterprises. Has slowed. And that’s really interesting because really what you’re seeing is these smaller mid sized companies or teams who can act in that kind of agile way are just going to lap these guys left and right. And I think these big companies aren’t going to know what hit them here soon when they realize that a small team can really outpace their massive group of marketing experts. 

Jessica Berg: Which is fun and heartening for small, medium sized businesses to have that. 

Carter Jensen: But that doesn’t mean that enterprises can’t shift to that. You know, I just think their standard, you know, way of working is the, oh, we’re going to invest in this one tool, this one thing, or maybe we’ll do some L and D work on the other side. But you know, as Jenna mentioned that 20, 60, 20, it’s very accurate. But I would say that most enterprises that I work with are so early in that journey that they haven’t even gotten to that point yet. 

And I think that’s just a massive miss when I go to small companies or mid sized companies or big companies who have this embraced. We’re sitting with Claude and ChatGPT on our second monitors all day long. 

And I know that sounds trivial, but that’s the difference between a 10x and a 1x kind of change. 

And it’s this idea that, you know, that is really where the transformation is going to come from to start from the ground up. And then the one last quote I’ll bring is that when you think about those point solutions, what I always find is people closest to the problem have the best solutions. 

And so the amount of companies that I’ve gone into, where the best ideas come from the associate copywriter, the best ideas come from the warehouse manager, the best ideas came from the junior account manager. Because you know what, they’re the closest to the problem. And if they can live and breathe and start with AI first, they’re going to come up with the most impactful solutions and you can then highlight those as they come to life versus coming top down and thinking that an executive team knows what’s actually happening on the ground floor. So a little bit of a soapbox, but again that gap is just massive right now and it’s a huge opportunity for small and mid sized businesses or large enterprises who can truly think AI first and not just go into these point solutions that are ultimately a trap. 

Jessica Berg: That’s awesome. Thank you. I mean there’s, yeah, we could hire five follow up questions, but I will stay on task. 

Carter Jensen: All good. 

Authenticity vs. Automation Balance

Jessica Berg: Now, moving into. I mean, just setting the table a little bit with that, who’s doing what, the scale kind of how to think about real transformation instead of just productivity. Let’s dig into that. Balancing automation with authenticity, that’s such a big question. There is definitely tremendous opportunity and power to automate things, to grab and scrape data at unprecedented scales and really mimic human stuff with AI, maybe in ways that are truly new and disruptive. And so we can get into the ethics part of that in our next question. So we will set that aside. But apart from the ethics, how can you avoid overdoing that automation at the expense of your real human relationships or the authenticity of your brand? 

Carter Jensen: And yeah, Jessica, wouldn’t you mind if I jump in and answer that one quickly? And then I’ll let Jenna and Ruth. So one of the lines we talk about is scaling your genius, right? It’s this idea of how do you look throughout your day and figure out where you make an outsized impact and how do you make that the largest majority of your day? Now, I think if we all sat back and audited what we do all day, how much of that is actually your zone of genius? And the reality is it’s probably pretty small, right? And so I’ll tell an advertising story here really quick just because I know Angeno and I have some common agency background. 

But when I was working at Fallon for a while, I was always a little perplexed with what kind of the lead creative directors would do all day. And we can all kind of laugh about that. But at the end of the day, the genius that they brought to the table was the differential thinking that came up with taglines like, we have the meat to transform an entire QSR restaurant. Now, when you think about that scenario, how much time are they actually able to dedicate to that deep thinking in their zone of genius? 

It’s pretty small because what are they doing? They’re doing research, they’re doing billing, they’re doing admin work. They’re talking to the clients, they’re writing emails. They’re constantly in this kind of world of offload or activity stuff that isn’t their zone of genius. And so the first step is like, okay, let’s first get all of that stuff off our to do list, right? If your zone of genius is meeting with high value clients, if your zone of genius is creativity, if your zone of genius is seeing around corners for your business, first of all, let’s get rid of everything else and a lot of Those types of tasks can be automated away, and those are things that are fine to be automated. 

And then when we go a little closer, it gets a little like, again, closer to the bone. But those types, if I go back to my story, like, there’s no reason why we have to hire a market research firm now to get a quick breath on, you know, what Gen Z audience in Southern Texas thinks about. We now have the tool to get that in a matter of minutes. And so you’re seeing them, yes, offload all of those admin tasks, all the stuff that in your zone of genius, but then amplifying that genius by having access to information super quickly. So if we use that framework to answer your question, Jessica, the reality is your zone of genius is yours. 

That is something that you have to identify and really double down on because no one can replicate that. But the job of us is to implement automation, AI, to not only support, but to focus in on that. How does that 10% of your day become the 80% of the day? And we see that people who become, and companies who become kind of AI first quickly get to that zone of genius, which. That’s where you hit hyperscale. That’s where you hit 10x growth. Because then everyone is focused on what makes them different, what makes them a genius and magical. What are you the best in the world at? And that’s where the real differentiation comes in. And that’s where I think you should look at that human element of focusing on that zone of genius while looking to automation to take care of everything else. 

Ethical Considerations & Data Privacy

Jessica Berg: And as much as it’s like we don’t. It’s not the intention for the tone to be big organizations versus small organizations at all. But like navigating that in a company like Jenna, in our prep, you shared that you were part of a team where 30,000 different people had access to editing things or like, you know, really protecting your brand voice or having some consistency and control over that in the AI world. Can you speak to that too? 

Jenna Gilday: Yeah. So I do believe the strategic inputs require human analysis and input. Right. So things like, what are your business growth plans, your unique value proposition to customers, your brand differentiation, that kind of creative genius that Carter was talking about. Right? That creative tone. Look, feel how it comes to life. Those are things that you still need humans to own and input. But there are more tactical opportunities to lean into automation. Thinking of media buying, ad optimization, ad set sizing, some of those like, more tactical executional things within marketing that could move more Quickly as we think of the brand and guardrails that brand that AI can help. I do think there are some interesting tools right now, especially for small mid sized companies to provide guardrails for your brand. And I think that’s like catching outliers offering content. 

But I do think at large organizations, given the number of people that touch things in the scale that it’s not the only solution. I think it’s a good solution to have. But you still need brand guidelines, education, people to oversee that creative process and input to ensure that what you’re putting in the marketplace represents your brand, but also represents what’s going on in the world. Right. Your brand doesn’t exist in isolation from what’s happening. So that human oversight at a high level of creative concept and strategy I think is still extremely important. And then as they move forward, balancing that automation efficiency and maintaining those customer connections will help just ensure that relevant, meaningful and differentiated marketing. But over time there will be more and more AI tools that can help kind of with the brand management in tone and look and feel. 

So I think it will continue to evolve. 

Jessica Berg: Yeah. How have you seen your clients, Ruth? 

Ruth Glaser: Yeah, well my decision framework that I use for this is really pretty straightforward. It’s what’s the cost of getting it wrong. So for really low stakes, high volume tasks, you, I think others have mentioned resizing photos for different platforms, scheduling posts that have already been approved, generating subject lines for AB testing. All of that can run on autopilot because if it’s slightly off, it’s really not going to damage our relationship with our customer, our clients. But anything that touches the customer that directly needs human oversight. And I just don’t see that going away. 

I think a lot of the, you know, we’ve all read stories in the last couple of years here about AI gone wrong and AI mishaps and you know, I would never trust AI to draft a response, for example to a customer review without my, and posting it without my first reviewing it. So there are things where if it’s going to have a big impact potentially on my target audience, I want a human in there. And then there are other things like going back to, you need to really understand your business and have that experience to know what to do. So AI can help you to analyze competitor pricing, it can help you run different models. 

But that strategic decision about how to actually respond to the competitive pricing set, there are so many different factors that go into that and that’s where you need the human to really drive that decision making process where AI can help to support the decision making. And so I guess the middle ground for me and where I see my SMB clients be most successful is putting some of those brand guardrails into AI to help the marketers stay on brand and having AI to help to generate some things, but always having a human validate before it goes out. Because we’ve also all had experience where AI has just hallucinated a completely alternative reality. We’re like, what? I have no idea what you’re talking about. So AI still can give great options, but humans need to make the final call. 

Carter Jensen: Ruth, I love that. And I’ll just give a quick example. We always talk about humans in the loop, right? That you know, and I love the analogy of what’s the cost of getting it wrong? One of the more common kinds of systems that, you know, people who kind of go through our classes put into place is basically an agent for your inbox, right? And specifically in a sales role where you may have hundreds of notes coming in a day where you just like at the end of the day you don’t respond to them, where obviously you don’t want an autoresponder just going crazy, right? But what we’ve built, again, human in the loop, Ruth, what’s the cost of getting that wrong? It’s pretty big. But what a lot of our students build is a system that auto drafts emails, right? 

So it’s this idea of that specific human in the loop. But even that is going to eliminate 90% of the time that those customer service representatives are actually using. So now instead of running 24, 7, the 8 hour shift, wakes up at 9 and they see that they received 120 notes last night. Well, there’s already drafts for every single one of those notes already drafted, right? And so they’re going through one by one and instead of trying to draft and find the information etc. That’s all been taken care of, right? And there’s a perfect draft sitting in the inbox. But again, that human in the loop, it didn’t automatically send it. You still have that human in the loop. Now eventually they might see that hey, we’re at a 99% success rate. The cost of getting this wrong, not as big of a deal. 

They might take off the human in the loop. They might just say, hey, send it all good and there’s a lot of middle ground there. So when you think of an AI system, just because sending a wrong email is costly doesn’t mean you can’t automate it to a degree. 

And I think that’s important to think about for all processes of. Yeah. You know, it can make subject lines. Well, you should probably take a look at those subject lines before you send them. 

And that idea of 90% to full automation is a really delicate line. 

Jenna Gilday: I love that example, Carter, because people move kind of from being the author to the editor. Right. And you think of how much time that saves in a day or even. 

Jessica Berg: For like going deeper into that customer service example, Carter, that like, how much input would that customer service person need to initiate to create that perfect draft? Like, is it pulling from the. Like, does that thing know what the customer bought? Did it analyze their message to see what degree of mad they were? Like, there’s so many things that AI can actually. Yeah, just. 

Carter Jensen: It gets better. 

Jessica Berg: Because it’s simple when you say it, but the power of it, like those are the layers of automation that can really be transformative. But yes, the person is reading it and sending it like that. 

Carter Jensen: Well, think about it from a marketing standpoint too. If you have a creative building an ad, well, that creative is in their bubble, right. You know, that creativity is building something based on their perceived experiences, etc. Well, what I can do is it can go look at what are the emotional triggers from that specific user audience. What are the 17 ads that a specific demographic has actually engaged with. What are the different aspects of those ads that really resonated? And then how does that create a brief that’s absolutely perfect versus a human who can just be like, oh, I think this kind of worked last time based on the year end review we got from our media agency. It’s like, no, I’ve looked and this is, you know, for this demographic here, the 15 ads that work here, the 15 that don’t. 

And now here’s your brief. Because we know what is already happening. It’s able to access so much more information, be so much better than we could ever be again, focusing on that zone of genius. 

I don’t want a customer service person sitting in our CRM all day to answer one email. Hey, but an AI can really do that well. 

And so how are you implementing this in a way that actually humans couldn’t even do in a timely way? 

Jessica Berg: Love that. Amazing. Yeah, we could. There’s so much more there too. But I don’t want to miss kind of getting to that ethical side. There’s authenticity or like Ruth’s. I love that articulation of the cost of getting it wrong or like making something seem less human or cringy versus what’s really ethical or unethical in your industry, you know, for the type of relationships you have with your customer. And some of this is new territory and some of it is like old hat for career marketers. And I would just love to dig into a little bit about all of your collective views and experiences on data privacy. Definitely. 

Leveraging these big, large language models can introduce some bias within algorithms or bias of the research that’s coming back to you, even for organizations like ours, big or small, of where are you being transparent of what AI is doing versus what humans are doing and do people care about that? This is a lot. It’s a lot of different things. But who would want to jump in to share some of your thinking? 

Jenna Gilday: I can jump in quick. Just as I think of from big companies, I do see a parallel to like 10, 15 years ago where ethical questions were coming up with first party data. Right. So think at the time, it’s like there were many examples in the market, something like if you know someone is pregnant before their friends and family do, is that something you should be using? And so there was a shift at that time moving away from first party to third party data. Because as you think of it through the customer lens, when you go from being helpful and relevant to feeling like you know things about me you probably shouldn’t, and you’re using it in ways that I don’t know if I support that becomes kind of a slippery slope for companies. 

So I think there’s something we can learn from 10, 15 years ago. But then the issue now too, as you talk about AI is it does just really amplify existing Data capabilities by 10x. Right. So then the magnitude of how quickly it can move and the data, there’s just greater responsibility as you think of that application kind of theoretically. 

Jessica Berg: Love that. 

Carter Jensen: Yeah, I’m probably a little bit. Go ahead, Ruth. I have a, probably a little bit more of an antagonistic point of view on this. 

Ruth Glaser: Okay, I’ll go first then. You know, regarding data privacy, I think SMB clients might actually have a little bit of an advantage in that they’re not trying to scrape every piece of customer data. You know, I think you’d have to be a pretty large enterprise to understand buying patterns enough to know that someone’s pregnant before their loved ones do. And we know that’s a real example. So, the SMBs I’ve worked with really focused on the first party data and that permission, you know, from that’s been earned through real relationships and that hasn’t changed in my opinion. I think some people have a big topic about the, you know, transparency of AI. I’ve never had AI create something that I could then post without any intervention. 

So you know, some people will advocate for labeling it as AI, but I think you really want to think about the wording on that if that’s the route that you choose to go for transparency. The algorithm bit is really tricky I think but at SMB level I think it’s manageable. I’m not sure how you would deal with this at the enterprise level but you know when I’m setting up systems for content or customer segmentation I’m always auditing the outputs. You know, are we accidentally, are we unintentionally excluding certain customer groups from this or certain buying behaviors? You know, I’m always looking I guess like Carter said to be the antagonist. What’s missing, what’s wrong, you know again that’s where that human in the loop comes into play. 

So just staying on top of that and it’s so really the in my opinion for SMBs the key is to build in regular human review checkpoints so that you can edit something, modify something before it goes out into the world and especially when it’s something that your customers or potential customers are going to experience, you want to make sure that’s the best experience possible. 

Jessica Berg: And I, I just want to use this as an opportunity to chime in. I know I’ll maybe save it for what you don’t want to say if you’re going to cover it, Carter, but that idea of even using AI as a built-in thought partner challenger sometimes it’s so simple. But folks that I know use AI every day are like here’s what I think is right based on what I know. What am I missing? Sometimes those questions too when you turn it into a person to poke holes or a thought partner in that way can be really powerful as well. Where do you feel like you as the key leader in a team Ruth do some of those process interventions or like add human intervention.

Ruth Glaser: Or you know what, you put me on the spot here, Jess. I’m not coming up with a specific example but what you said really resonated and I think that it’s a really valuable tip for people if they have not been doing that is to invite AI to poke holes in your theory or, you know, to give you, how could I improve this? Like you said, what am I missing? All of those things are great strategies to get the best quality product, ultimately. 

Jessica Berg: Awesome. Cool. Well, Carter?

Carter Jensen: Yeah, yeah, and I’ll be quick because there’s a million different points that you respond to. And, and I think you’re right in asking that question. Jessica is in, you know, we teach that all the time of how do you really push? 

And how do you find those not agreeable terms? And how do you think differently? And coming from that, I think, you know, to focus one part of the conversation around really kind of this bias perspective. 

AI is biased. And I think again, my kind of push on that is your creatives are very biased themselves. 

Like, how many times have we had to, you know, try to think about what, you know, expecting mother might want or what is a busy parent look again. And you know, at times you’re really good at doing that because you are that person. 

But oftentimes when you’re sitting in a room of creative strategists, everyone looks the same and they come from a pretty generic background. 

Not to poke holes in us. So I think it’s just, it’s. I think we’re missing the root of the problem when we think about AI as being biased. Like, naturally, all our creatives are biased. They come from the same place. Usually you’re all sitting in one city with similar backgrounds. And to think that, you know, getting more information, even if it is maybe a little bit different, tinted with, you know, bias versus just staying in our own bubble. I would say that AI should be more of a, you know, an additional point of research that’s going to make you less biased in those creative situations versus just kind of relying on everyone’s shared past experience, which is often, like I said, pretty common. 

And so I’ve always really kind of cringed at this idea that AI is biased. Not that I don’t think it’s true, but I think that we missed the core part, that we’re all biased. Bias. 

And when you get all of us together to try to think of creative solutions and creative messaging that meets some target audience that isn’t ourselves, which we all do. 

That’s a problem in itself. And so I think that to not use AI because we think it’s biased isn’t. 

Implementation Tools & Resources

Jessica Berg: There’s so many different things in that too. I want to touch on. But like, just a super quick follow up question for you, Carter, because some of this came out in our prep call and I thought it was, it helped me think a little bit about the kind of permission structure or for potential customers that are having trouble with the idea of AI doing so many things for them. You had a great example around Amazon’s use of recommending products or like, where can a customer have a better experience with your brand or your business because AI is being used versus. But yeah, finding the line for their ability to agree to that. Do you mind just mentioning that? 

Carter Jensen: Yeah, Jessica’s mentioning, you know, we’re talking a lot in the prep calls, a little bit about how much information is too much information and how personalized is too personalized. I think we kind of came back to the traditional advertising conversation of personalization and the creepiness factor. But Amazon, if you guys haven’t used it, actually has a AI built into it for shopping. It’s called Roll Rufus. If you’re on desktop, it’s in the top left corner. You can click it and chat with it. And over the last couple weeks they’ve rolled out an update where they’re very specific and very upfront about the personalization it’s doing. 

So my kids just went back to school. We were looking for backpacks. Okay. I asked Best Backpacks to go back to school. And yes, of course, it’s going to base that opinion on your entire purchase history that Amazon knows about you. But they actually came out and said it. They said, you know, in the chat response, it basically says, hey, based on your past search history, we see that you like, you know, mid range products that are well built with organic fabric or whatever it was. 

And because of those preferences that we’ve detected, here are the recommendations. And then I had an opportunity to push back. But I thought it was just really interesting how upfront they were within those recommendation stack of basically being and saying out loud, not, hey, we’re using AI to scrape your data, whatever, but in a very human way saying, hey, we noticed that you like this. 

Like, you know, and you know what? They’re, they’re very. Right, right. Because they know more about you than you know about yourself at the end of the day. But it was just an interesting strategy to actually think about how do you bring that upfront to be very, you know, focused on how it adds value versus the fact of, you know, we’ve scanned your last 3,000 purchases and, you know, sure looks like you do need a new backpack. You know, whatever it might be. 

So I just thought that was a really great example of how Amazon leading with AI shopping is doing this in a unique way. 

Jessica Berg: No, thank you. Yeah, it’s like you. You touched on those things, but that underlying story, I feel like illustrates it really well. So thank you for that. I. I’m going to get myself ready to fire some Q and A questions. 

But while I kind of shift gears or maybe give our audience a chance to add their questions in the Q and A feature like Plug to do that. Now, any guard rails or tools or just other things around the ethics of what you’re doing in your teams and your work that you think might be helpful for our audience to think about or follow up on. It could be a guardrail, could be a tool. 

Carter Jensen: Get everyone a ChatGPT account. It’s $20 a month. You spent more on lunch and learn that you did last week. And then monitor usage and incentivize with a carrot, not a stick, to use that all day, every day. Our top students who graduate from our classes are on it four plus hours a day, amplifying their genius. But you should be using it at least a few times throughout the day. And it’s that cadence and that repetition backed with the right education that’s going to truly transform. So I don’t know if that was the right answer to your question, but you gave me an open floor and I said it. 

Jenna Gilday: Well, I think you know what guardrails one is thinking of. Like, are you labeling it appropriate? Like Carter, the great example of Amazon, but it was clear, like they’re using your history and information to make recommendations. The other is thinking of sensitive areas. I brought up an example of if. If someone is pregnant, if you’re talking about your children, if you’re talking about your finances, if you’re talking about people’s personal health, those areas that maybe have a bit more sensitivity. Where other areas, like purchasing a backpack, there’s probably a lot more openness. So also just taking into context the sensitivity of the area you’re talking about. 

Jessica Berg: And you were gonna. I don’t know if that was the same spot you were gonna cover, Ruth. 

Ruth Glaser: But yeah, I think I’ll. Yeah, it’s been covered. I don’t need. 

Jessica Berg: Okay, well, diving into Q & A, I’m gonna start and feel free to maybe stick to quick answers, but we can dig deeper if we have time. What are the best resources for that? All of you are using it to stay current in AI marketing because it really feels like there’s a new tool every day or at least three new features in existing tools. So do you have any tips? 

Ruth Glaser: I don’t know if this is exactly what you’re looking for. It kind of dovetails into what Carter was saying though. I think just digging in and using it is the best way to become familiar with it. So I started to build custom GPTs and then I started, like Carter mentioned earlier, thinking about AI first. I was starting to see opportunities in my own personal life. So I’m a bicyclist that’s part of a club. So I created this whole governance framework for my club using AI and it helped me to learn different things. Similarly, I just organized my pantry and I put all my inventory into AI so that it can help me not waste food and do so. There are just different things that you can do. There are so many applications. 

So I think the more that you use it and it doesn’t always have to be for work, in fact some of the non-work stuff can bring you some really great aha. Moments to then turn around and bring to your work. I think that’s the number one way to really become fluent in AI. 

Jessica Berg: Do you have thoughts on this Carter? Of like how do you. I mean especially that this is your business. 

Carter Jensen: Yeah, for sure. And I’ve seen both sides of this, right. I came from the corporate world and now actually helping teams do this. And Ruth, you’re exactly right. You know, it’s like getting in there and trying. There is a line between usage and seeing the magic and becoming addicted. 

And I think everyone knows what side of the line they’re on, right? And we call this an AI offloader where you’re just replacing Google with ChatGPT every now and then or an AI architect who knows how to use these systems in order to truly focus on your genius. And access is the first thing of course, like get in there and try it. But educating people and empowering people with the tools and the strategies and stuff just to get over that line. And we talk about this like anyone with a laptop can do this and should be doing this by finding a way to educate and empower your teams in order to get this done. 

And that’s what we do all day, every day at the Uncommon Business is figuring out I don’t care if you’re a manufacturing company or an HVAC company or a creative agency or you’re working for Harley Davidson or Care doesn’t matter. There is that magic line and it’s so close. If you’re just using ChatGPT once or twice a week, maybe once, twice a day, you’re not addicted yet. You haven’t seen that line. And that line is so powerful. And I’ve seen it both at my Fortune 500 work and I’ve seen it every single day within these small businesses. The second these teams get over that line, like it’s that 10x growth. And that is what is truly differentiated when you think about driving adoption within this kind of category. 

Jenna Gilday: One thing I would add too is if you haven’t been engaging with it, there are lots of training options out there, right? So obviously there’s training sessions companies can do, but there’s more technical training, there’s through university training just to get a general baseline. So if you feel like you’re behind and like just dabbling in it isn’t going to get you there. Like there are opportunities to kind of just level up that would make you more capable of engaging with the tools on a more regular basis. 

Jessica Berg: That’s good. Everybody, how I’m jumping around a little bit because we haven’t covered this one at all yet, that it is fair that AI is so powerful already, but the platforms themselves are still potentially in their infancy. If you are an organization that is building on top of AI tools or considering large investments in, you know, your own proprietary stuff, how do you think about what’s good to do now versus things you should wait and see while the technology evolves. 

Carter, that’s a good one for you too because you’ve seen it recently in both ways. 

Carter Jensen: Sorry, I was in the Q and A answering questions. Jessica, I don’t know. So you’re asking how the technology’s evolved? 

Investment Strategy & Proprietary Development

Jessica Berg: Well, just like if you were a business today that is contemplating creating something custom or investing in something that is a bigger expense today versus waiting a year or you know, like when should folks really think about that? Especially for companies that want to build proprietary stuff with AI. 

Carter Jensen: Yeah, I would be careful about proprietary. There’s so many great services out there now that are offering just like the best solutions at a pretty cheap rate. I will go back to this idea of foundations, right? You need to get every single person with a laptop AI trained to some degree. And then what you’re going to end up seeing, this is a real full circle moment, right? I talked about earlier, the people closest to the problems are going to have the best solutions. 

Don’t kind of come in from the top and think a new AI copywriting tool for a half million dollars a year is going to solve all your problems because it definitely will not. I’ve done that far too many times. 

The $20 chat GPT subscription could do really everything that I, you know, built at General Mills, but better. And that is the subscription. Yes, of course, but also an AI trained AI architect. That type of person behind the scenes is so powerful. So I wouldn’t like to invest into AI because we’re waiting for technology to evolve. It is here. And so many companies are far in front of people already because they’ve adopted it. The best time to invest was a year ago. The second best time to do it is now. 

And I think that is just so important and I would much rather see you invest in foundational tools like ChatGPT, Claude or whatever version of that you want to go into than finding a one off solution. That one off solution might come into focus in a couple months after you’ve fully found what’s going to be the most impactful. But start with the basics. Start with using these systems. Start with empowering your teams. Let your employees expense the $20 a month. You won’t believe how much confidence controversy that sometimes brings. But again this is going to be 10x your business and you’re going to spend less on this than you did at your, you know, catering last week. And so it’s just so important. Get the tools, get the training and then go from there. 

Ruth Glaser: So I, that’s such a great point. Carter answered a question in the Q and A and he just brought it up too. I think a handful of my favorite tools obviously ChatGPT, I like Claude even better than Chat GPT. So if you haven’t tried that, take a look. Perplexity is outstanding for research. Carter mentioned GROK as a favorite. So those are, you know, those are kind of the big ones but there are so many specialized tools it’s almost overwhelming what you can purchase now. So yeah, starting and again diving in with the lower cost platforms to begin with. I think spend a few months in those and then you’ll start to have a good sense for, you know, what can be automated, what you can automate versus maybe you need to start looking for a solution for. 

Jessica Berg: Yeah and this is like a little bit of, gets a little bit into some of the data privacy or like intellectual property. Everybody double Clicks on what Carter shared about allowing your employees to, you know, pay, like use, pay for kind of authorizing that they can use AI tools themselves. But anybody wants to touch on the private, like being using a private corporate kind of under your own data security umbrella, GPT versus just the publicly available GPTs. I can chime in on that. 

Jenna Gilday: But yeah, I mean, if you’re using OpenAI, that data then exists for anyone else to access. Right. So I think there is a just base level training. And Carter, I’m sure you could jump into more detail, but if you’re putting it out in open AI, it will exist in OpenAI for anyone else to pull that data from. 

Jessica Berg: And, and Carter, or. Yeah, whether Carter, you want to jump on that or Ruth, I know you’ve built GPTs within authentic, within your own client environments to protect their intellectual property. Like anything you’d add to that. 

Ruth Glaser: Yeah, well, in the two instances that you mentioned, the intellectual property is really the key service or the key product of those organizations. And when that’s the case, then definitely, you know, you run into trade secret issues. Although I’m not, I don’t have a lot of faith in OpenAI, so they might be using it anyhow. But I, Yeah, if there are things you don’t want, you wouldn’t tell your competitors. I would use a private local license. 

Carter Jensen: I’m gonna have the completely different opinion on this. And that’s fine. That’s right here. Risk versus reward. Like, let’s just think about what the risk versus the reward is here. We don’t, we don’t, you know, we don’t monitor every email that our employees send. We don’t monitor every Google search that they send and train to not upload your financial statements before the quarterly earnings call. Yes. But I worry and I see so many companies stuck in this privacy loop beyond getting after it, that it’s so important. And the $20 a month tools you can turn off, data training, you know, you can do those types of things. So, there’s just general hygiene stuff to stick by. But I would do the audit. What is the risk? What is the reward? 

Do we have another year to truly figure out the perfect privacy solution, or can we just be responsible adults and ensure that we’re not sending the quarterly statements and the proprietary stuff beforehand? So I’m not going to say that anyone is doing it wrong or anyone’s wrong, but I just like, I would highly encourage you to think about what is the risk versus reward here and the reward on the other side is 10x growth. The risk is potentially leaking something, you know, and no one wants that. But I just think it’s really important to think about. 

Jessica Berg: That’s a great place to stop. We blew through the time, so thank you also for jumping in. Just responding to that question in the chat or the Q and A Carter, but want to say thank you to everybody for taking the time to be with us. Don’t want to hold you up as you go on to the next things in your day, but love this conversation. And thank you so much to our panelists for sharing all of your wisdom.