Human Driven AI’s Jennifer Jones-Mitchell spoke with BusinessRadio about how Generative AI helps marketers automate tasks, augment skills gaps and improve campaign performance.
- What is Generative AI and how is it different from AI?
- How does it work, how does Generative AI think?
- How can marketers train Generative AI?
- What are future trends around GAI?
Listen to the broadcast here:
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Below is the full transcript:
Intro: [00:00:04] Broadcasting live from the Business RadioX Studios in Atlanta, Georgia. It’s time for Atlanta Business Radio. Brought to you by on pay. Atlanta’s New standard in payroll. Now, here’s your host.
Lee Kantor: [00:00:24] Lee Kantor here another episode of Atlanta Business Radio, and this is going to be a good one. But before we get started, it’s important to recognize our sponsor, Onpay. Without them, we couldn’t be sharing these important stories. Today on Atlanta Business Radio, we have Jennifer Jones Mitchell with Human Driven. Ai, welcome.
Jennifer Jones Mitchell: [00:00:44] Thank you. Thank you so much for having me.
Lee Kantor: [00:00:47] I am so excited to be chatting with you today. Before we get too far into things, tell us about human driven AI, how you servant folks.
Jennifer Jones Mitchell: [00:00:54] Well, at its core, it’s a knowledge hub for marketers and companies who want to learn how to apply generative AI to their work, their articles, podcasts, master classes, workshops, things like that. And I also lead AI transformation strategies for agencies and brand marketing teams.
Lee Kantor: [00:01:13] So what’s your backstory? How’d you get involved with this?
Jennifer Jones Mitchell: [00:01:17] Well, I’ve been involved in marketing communications for 30 years now, and I’ve always been one to embrace emerging technologies. I was one of the early voices of social media back in 2007, 2008. And, you know, really for the past, I’d say eight, 8 or 9 months, I’ve been watching the emergence of generative AI tools and using them in my own marketing campaigns. And just, you know, I would talk to colleagues and clients and people who either are afraid of generative AI or they don’t understand how to use it. And it just sparked for me. I need to help people understand the value of these tools, the language and the mind of AI so that they can get the most out of it. Because like it or not, it’s here. So I just didn’t want my friends and colleagues to get left behind. And that was kind of the impetus.
Lee Kantor: [00:02:12] Now, AI has been around for a while now. In fact, a lot of folks, I mean, they have an Alexa in their house that they’ve been talking to, getting answers to questions for years. Can you maybe explain the difference between the AI that we’ve been talking to Alexa and Siri with and this generative, generative AI that you’re talking about now? Maybe define some terms and explain how these things are the same and different.
Jennifer Jones Mitchell: [00:02:41] Certainly, yeah. I mean, generative AI basically means AI that has been trained to generate something for you. So ChatGPT or Claude, these types of tools can generate articles or new ideas. Dall-e and Midjourney can generate images for you. So that’s what generative AI really means. But yeah, to your point, AI’s been a part of our lives, our daily lives for a very long time. Every time you use Google Maps or Waze to get somewhere, every time you use autocomplete in your searches or in your texts. It’s all AI. But yeah, the difference is really now we have all of these commercially available tools that can help us to operationalize efficiencies, particularly around marketing, which is my focus. I’m not an engineer, I’m not a software AI engineer. I just help people use these generative AI tools and develop the right tech stack to achieve their goals.
Lee Kantor: [00:03:47] Now, some of these tools right now, like ChatGPT, there’s free versions and some of them are kind of more they’re more like specialists and they, they do a certain thing for certain people and they are paid versions. Is this something that you help folks with is to say, okay, if you want to just kind of test it out, here’s some free ways you can do this, and here are some prompts that may help you achieve what you’re trying to do. But if you want to really make a bigger impact, you’re going to have to build kind of a tech stack around with certain tools to help you get to where you want to go.
Jennifer Jones Mitchell: [00:04:22] Yeah, absolutely. That’s really the difference between a workshop and an AI transformation strategy. A workshop is still customized, of course, to the people I’m talking to, but it is more about showing them the mind, the language of generative AI, how to use these tools in general, and then the AI transformation strategy. That’s about identifying those opportunities to automate tasks and augment skills gaps, build that tech stack that serves their specific needs, as well as developing company guidelines and policies around AI usage. It’s interesting. I like to think actually of generative AI more as an employee than a tool. I’ll give you an example. So many of my marketing colleagues used to say, Yeah, you know, I asked ChatGPT to write an article and it was fine, but I still had to proof it and edit it and to. Am. I always say, okay, if you ask an employee to write an article for a client, do you just blindly pass that off to the client or do you proof it? Do you edit it? Do you make sure that it is the best it can be? And that’s the way you have to look at these GUI tools. They are only as good as the inputs you give them. So that’s why in the workshop it’s about understanding the mind of AI. What do you need to tell it in order to get the right outputs that serve your goals?
Lee Kantor: [00:05:56] So now along those lines though, if we’re going to continue that metaphor about the AI being an employee at some point, can you stop checking their work or is it something that at this stage you’re going to have to check their work? They’re basically doing a good or a better and better first draft of something that you need, and it’s going to always take a human to kind of go over it to make sure that everything is just the way you’d like it.
Jennifer Jones Mitchell: [00:06:23] Well, I do.
Jennifer Jones Mitchell: [00:06:24] Think you should still check the work, but I have found that I need to give fewer and fewer edits to it the more you train it. One of the biggest mistakes that people make when using ChatGPT or Claude too, which I actually prefer to ChatGPT people will have one conversation with it and just keep adding to it. You want to start a new chat for different topics and that’s how you train it. So, you know, for example, I can train, you know, I write a lot of articles on behalf of clients because I still have PR consulting as well. And so I can train ChatGPT to write in the voice of a client. And all you do is you feed in an article written by that client. You ask it to the AI to analyze it and to recognize it as X client’s voice. And then I found if you do 2 or 3 of those and save that query, then it becomes easier and easier because I can just go to ChatGPT and say, Write this, turn these bullet points into an article in the style writing style of X client. So the more you work with it I guess is the shorter answer. The more you work with it, the better it is.
Lee Kantor: [00:07:43] Now when you’re working with a like a cloud or a ChatGPT in that form, is that is it going to remember that client over time, or is that something you need kind of a specific tool that you’re paying for that is is you’re building kind of that the the large language library of your own kind of unique needs rather than kind of a general purpose AI tool.
Jennifer Jones Mitchell: [00:08:11] Yeah, absolutely. That’s why you want to set up a different chat conversation for each task in that sense. And then within that chat conversation it will remember that writing style and it will improve with each new version of content that it creates. It’s like a lot of people will open up a chat, GPT chat, and this is someone else’s example, but it’s such a good one. They’ll be talking about quantum physics and then they’ll ask in that same chat for a recipe about Fettuccine Alfredo. Well, that AI chat is now trying to connect the dots between quantum physics and Fettuccine Alfredo So you really do want to have a separate chat for each task and you can save them and go back to them. And that’s how you train around specific tasks.
Lee Kantor: [00:09:04] Now, is it possible, like, for example, I’ve been doing podcasting for many, many years. I have a podcast that I do tips on. Me and my partner talk about tips and we have thousands of tips. Could I upload all of the the tips into a chat, into a chat and then it have and then we transcribe it. So there’s a machine transcription of all those words, could that be its own library? And then I could basically say, okay, now you come up with these ideas because you have pretty much everything I know in this chat.
Jennifer Jones Mitchell: [00:09:40] Yes. And that’s an excellent use of the tool. Absolutely. I also want to say, you know, a lot of people only think of these tools as content creation creators, and they are. But I’ve brainstormed solutions in these tools. I’ve brainstormed solutions to business problems, to marketing problems. It’ll come up with campaign ideas. I mean, there really is no limit to what you can ask these tools to do for you. You just do have to remember that generative AI tools were trained on the internet and everything on the Internet was created by humans. So there is an inherent bias. There is a chance that these tools will be wrong. So that’s why I do say you still need to. Look at it and proof it and make sure that it’s accurate. I like to ask for sources in an article. Please provide sources and examples, but I’ve found sometimes it’ll make up sources. So there’s still a lot of improvement in some of these tools. But again, it’s not just about content creation. There are generative AI tools that help with project management, that help you with pricing both B2C and B2B pricing. So there are just so many tools and that’s why it comes down to you want to understand what is your current state of AI and what is your future state and then what are the tools that that make the most sense for your specific needs.
Lee Kantor: [00:11:07] Now, a core element of all of these chats that I’ve seen so far is the ability to ask the right prompt or to ask the right question in the right way to get the result that you’re really looking for. How important is that skill to really be able to ask good questions and to really narrow down focus and give parameters when it comes to AI to really wring out the most value for this?
Jennifer Jones Mitchell: [00:11:37] It’s absolutely critical. I was giving a speech a couple of weeks ago and I told the audience, if everyone in this room asked ChatGPT to write an article about the top ten digital marketing trends for 2023, and that’s all we asked it to do. We would all end up with the same article and everyone would put it out there and we would just be lost in this sea of sameness. But if you ask that same question, right, an article, will you write an article about the top digital marketing trends of 2023 from a company perspective of this in the voice of this with the brand personality of that and give it a creative brief, let it know who, who is it writing for or who’s the audience. Give it everything it needs. That’s how you get something that is truly unique and and will truly serve your goals.
Lee Kantor: [00:12:33] So in a good prompt, how many parameters is there a rule of thumb like, okay, try to give it a minimum of three, but as many as ten parameters when coming up with a prompt so that you’re getting a better result.
Jennifer Jones Mitchell: [00:12:49] I mean, it really depends on what it is that you’re after. Do you remember Boolean logic back in the day? Yeah. You almost want to take that approach where you’re saying, I want something that is like this but not like this, like this and this. Similar to this, but not like that. You really want to have an in-depth string of prompts, but you can also, once you get the output, you can say, Oh gee, I forgot to tell it to do this. You can always improve upon it. I just recommend that you do that within that same conversation. Otherwise you’re going to be starting from scratch. So again, you want to teach it in each chat how to improve the output.
Lee Kantor: [00:13:31] So you mentioned that your work is primarily in marketing. If somebody is new to this at all, what are some of the kind of the basic things they should be doing to just test the waters and get a feel for some of the benefits of playing around in this space?
Jennifer Jones Mitchell: [00:13:50] Well, it’s exactly what you said. Play around with it. Start Start testing these tools, Play with certainly ChatGPT. I did mention I like Claude two better. I think the output is more human like. And Claude too, by the way, will actually give you prompts. I asked Claude to the other day to put an outline together for an upcoming podcast and it asked me What’s the audience? So again, to me that’s a way that it is far better than ChatGPT because it helps you. It actually prompts you to give it the information. But yeah, start playing around with these tools, see which ones really work for you. Read about, you know, visit human driven ai.com and read about some of the tools. But it really comes down to identifying the areas that can be automated or augmented with the right tools. You don’t want to just jump on every shiny new thing. You really do want to understand the value of each tool.
Lee Kantor: [00:14:54] Now, speaking of shiny new things, is this a shiny new thing that is going to be here, or is it a shiny new thing that may be, you know, I don’t want to, you know, like the metaverse was a shiny new thing. And and that was something everybody was like, oh, this is it. You know, this is going to be part of my everyday life. And it, you know, it’s still there and it’s doing interesting things, but it’s not kind of embedded in our life as maybe some people. Predicted when it first came out. Is this a shiny new thing that is going to be kind of just part of our day to day life? Especially if you’re in business nowadays?
Jennifer Jones Mitchell: [00:15:32] Yeah, absolutely. Make no mistake. Ai is changing everything. It will impact the way business is done at every single level. Again, I know it’s easy for people to think, Oh, it’s a content generator, it’s an image generator, but there are so many different AI tools. You know, I’m really impressed lately with Clickup, which is a project management tool powered by AI. We’ve all been there where you set up your whole timeline and your project and you’ve got all your teams and their tasks are all set up in a system, and then you’re suddenly told, Yeah, everything’s being delayed six weeks. Well, with one click of a button, your entire timeline can be adjusted in this tool. So again, it’s so much more than just generating content. But I do want to say something you said about the metaverse, because Zuckerberg may have been early with the metaverse, but he’s not wrong. We are absolutely headed toward XR, which is kind of a bucket for all different realities, augmented reality, virtual realities and the metaverse. We are going to see more and more in the XR realm very, very soon. We’re already seeing it with if you want to try on some clothes at Neiman’s, you can sit on your in your sofa and have your avatar. Not a cartoon, but an actual almost hologram of yourself with your dimensions trying on clothes. If you want to go to the Super Bowl, you can’t afford a ticket very, very soon you’ll pop on your headset and you can sit in the stands and watch the Super Bowl in the metaverse. Turn your head. There’s your buddy sitting next to you in the stands. He’s on his couch. You’re on his couch on your couch. But you’re all part of this reality that is coming very, very soon. And it’s the power and adoption of AI that’s going to lead to the metaverse.
Lee Kantor: [00:17:29] So when you’re working with your clients, you mentioned several different ways to engage with you. Can you go over those again and really explain the difference between them?
Jennifer Jones Mitchell: [00:17:39] Sure. Well, I can do in-person or virtual workshops, and this is custom to the client, you know, whether it’s an agency or a brand marketing team and it’s custom to the types of clients that they have because the needs of an agency that serves B2B clients versus B2C versus both, it’s all different. But I put together a workshop where I help you understand the mind and language of these GUI tools, how to talk to them, how to not just, Oh, here’s a list of good prompts to use, but rather how to craft the ask, how to craft the prompts, how to think through giving it what you need. Because I want you to be able to do more than just regurgitate a list of prompts that I give you. So that’s the workshops. And then the AI transformation strategy is far more in depth. It’s where I audit your teams. I identify those opportunities for automation. I look for those skills gaps that can be filled in by generative AI. You know, look for those operational efficiencies, look for data because so many companies and agencies have all this customer data that that’s being gathered through AI tools, but they don’t know how to use it. So I help them to operationalize that data for improved and personalized customer engagement. And then of course, those time saving and cost saving assistance through creative content generation. And then the last step of it is developing kind of company guidelines and policies to help really operationalize across the entire company. How you use generative AI tools, how we handle data privacy issues, how we handle, you know, all the risks that are associated with it as well, because you want to make sure you are not just strategic in your application, but you have an ethical application of GUI tools.
Lee Kantor: [00:19:42] Can you share a story of maybe one of the people or companies you work with that you don’t have to name their name, but maybe share the challenge that they were coming to you with and and how you helped them get to a new level.
Jennifer Jones Mitchell: [00:19:55] Well, just recently, like with an agency, one of the first things I like to do is look at their timesheets. Agencies, of course, have to track all their time. And I immediately found a number of areas where we could automate tasks that the agency was spending a lot of time doing. So, you know, identifying those those aha moments where you’re like, Yeah, you could have an AI tool. Achieve this for you. Also working with them on ways to recognize research and how to brainstorm in generative AI. That’s a big aha moment usually for the marketers that I work with because they just think of it as ask it to achieve and do this one task. But you can really have conversations with these tools that can kind of break you out of your normal approach to things. So just showing them how to use the tools in a new way. Always spark something in terms of application of it.
Lee Kantor: [00:21:05] Now, you mentioned a couple of the tools. Are there other. Can you list some of the kind of the tools that you your go to tools or the go to for marketers nowadays that you think should at least be experimented and played with?
Jennifer Jones Mitchell: [00:21:19] Well, absolutely. I’m a big fan as I mentioned of Claude two. I think it’s it’s far more human than ChatGPT. I mentioned Clickup anybody who’s trying to do project management. What I also like about Clickup is it has prompts, I think, over 100 different role based prompts. So as you’re building out your client campaign or some larger in-depth project, it, you can choose, let’s say engineering and it will have prompts not as I’m not an engineer, so I don’t inherently know what all the tasks I need to assign to an engineer for this specific campaign, but it will have prompts that will come up and say, write a technical spec or create a test plan. So it really helps you to map out your entire project management timeline. Price fix is one that I use a lot just in terms of developing my own B2B pricing for solutions. It basically reviews the market and competitive landscape and then helps you assist with your pricing. And then Wiser is another one that I’ve been playing with a lot on the B2C side. It captures real time retail data both online and in store, and it will help you develop your pricing strategies based on how your B2B B2C product is doing across the entire retail marketplace, which we know is, you know, beyond just the Tripoli.
Jennifer Jones Mitchell: [00:22:54] It looks at in-store, it looks at how resellers are pricing your products as well as competitors and gives you that real time data that helps you with your own pricing strategies. Beyond that, of course, I really love Mid-journey. I think it’s an incredible creator of images and I think that a lot of marketers also need to look at tools that they’re already using because a lot of existing tools are now adding generative AI features within them. For example, I already use Canva as a tool to help me create different graphics and images, particularly in social media. But with one click of a button, Canva will take your bullet points and turn that into a PowerPoint presentation. I can’t tell you how many hours marketers spend formatting decks to be able to have Canva, and there are a number of other tools that do it as well. But to have them create a beautiful PowerPoint deck for you in seconds, it’s just the time. Savings is is incredible.
Lee Kantor: [00:24:02] Now, when companies come to you, what is the typical point of entry? Like, are they coming to you to just get general information or are they coming to you to solve a problem?
Jennifer Jones Mitchell: [00:24:16] It’s both. Usually so far it starts with a workshop and then once their teams start using the generative AI tools, then they usually come back and say, okay, we understand the value, but we don’t understand how to get to this future state of AI. We need someone particularly to help us identify and test all of the tools because there are so many out there and some of them are really, really good and some of them are new companies that really haven’t tested to fruition yet. So a lot of times it comes down to we just don’t know which tools we should be using and we need help with that. And I always back that up and say, okay, let’s look at the strategy first. Let’s look at what we’re trying to achieve and not just give them a list of tools, but rather a true transformation strategy to get there.
Lee Kantor: [00:25:12] So if somebody wants to connect with you have a more in depth conversation. What is the coordinates?
Jennifer Jones Mitchell: [00:25:19] They can email me at Jennifer at Human Driven AOL.com or just visit the site human driven AI.
Lee Kantor: [00:25:25] Well, Jennifer, thank you so much for sharing your story. You’re doing important work and we appreciate you.
Jennifer Jones Mitchell: [00:25:30] Thank you so much for having me. I really appreciate it.
Lee Kantor: [00:25:33] All right. This is Lee Kantor. We’ll see you next time on Atlanta Business Radio.
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