How AI Can Augment Thought Leadership | Stephanie Grayson | 503

How do you polish good ideas and get them in front of the right audiences? And, well, what makes a good idea anyway? Today I sit down with Stephanie Grayson. She's an experienced B2B content marketer and thought leadership practitioner. She's practiced these arts in the world of agency marketing, large consulting houses, enterprise-scale software, and advisory to firms. She's also an AI enthusiast. And so we're going to explore how AI can augment humans in thought leadership practice without replacing them. I'm Bill Sherman, and you're listening to Leveraging Thought Leadership. Ready? Let's begin. Welcome to the show, Stephanie.

Thank you.

So we're going to talk about a number of things, but I think a good place to start is you've been in the world of AI for a while now and you've seen it evolving. And I wanna have a conversation to begin with around AI and thought leadership. So for organizations that are starting to think about how does AI fit into this piece of the puzzle, what would you say?

So I think a really good place to start that conversation is talking about the differences of where AI could be useful or perhaps not as useful when we look at the differences between content marketing and thought leadership, right? Because there are important differences between those two. There are a whole bunch of different features that, you know, we could talk about, you know, in terms of what are the differences. But I think a good shorthand would be something like content marketing is very useful to solve pain points of today. And thought leadership is going to open a conversation as to what we can do for business strategy and execution for tomorrow. And I think also that an important feature is that the content marketing is a problem solver. At least it can be in its most effective form. Thought leadership doesn't necessarily have to solve something today, but what it does is it positions the company reputationally and otherwise for leadership. Whereas content marketing is more positioning you in terms of product authority. So I think those are very important distinctions, and that is why I will go ahead and just say very clearly, I think AI will be more useful and applicable for content marketing than it will be useful and applicable for thought leadership.

And I want to distinguish between those two in a moment here. But you said something about content marketing as problem solver. I think one of the things that we could talk about for thought leadership is that it's problem revealer or opportunity revealer for your audiences in some ways. And if you sort of lay those out, those are entirely different tasks.

Very much so. You, you put it very excellently. And also, it is a different type of mechanism that moves decision makers. So I'm just going to go ahead and I'll throw a little factoid out there.

Go for it.

You know, there was a fantastic B2B thought leadership study that was performed jointly between LinkedIn and Edelman a couple of years ago, and what they came to discover is that 88% of C-level decision makers believe that thought leadership influences their opinions of a company. And that strong thought leadership content not only strengthens the company's reputation, but also positively impacts things like RFP invitations, wins, you know, pricing, sales, right? And it's an interesting insight because so many times we think of content marketing's relationship to sales. But we think perhaps a little less about the relationship, or at least the direct relationship between thought leadership and sales, but it is to be had there. So it's very interesting to hear about the power of thought leadership done that way. And if done well, AI is not going to solely be able to accomplish the kind of thought leadership that these C-level decision makers are responding to.

And I wanna put at least an asterisk after that statement and say yet, right? Because we look 10, 20 years out in the future, AI may be able to do more and amazing things. However, I like the distinction here on connecting thought leadership to sales because I think that's part of the essential piece. That sometimes gets missed. Because it's easy to focus on content marketing and say, okay, we're trying to generate leads, get invited for proposals or RFPs. We're trying to increase our win rate, all of those things, content marketing, let's funnel to product solution sales. And it's very easy for the product team and the sales team and the marketing team to be working together on today. But I think of it as a little bit of, if you think in sales, the difference between hunting and farming, right?

Mm-hmm.

Hunting, you're trying to bring something in today. Farming, you have a longer horizon in a sales process. And I think thought leadership sits in that second category of farming more than hunting.

Well, it's interesting because where hunting can come into play, so I, I love this analogy you're making with farming and hunting. But part of what I think is so much fun about thought leadership is sort of an aspect of hunting in that you're hunting in some way for that novel idea or seeing around corners, right?

Absolutely.

Yep. So, you know, there is an element, you know, of hunting in that, that you are at least open, maybe not actively hunting, but perhaps passively being open to really exploring and discovering perhaps, you know, something that will be the next— it could be a new idea, but it also could be a new approach to existing structures or existing processes that has novelty to it. And that's kind of the seeing around corners part. If you take a look at a lot of successful B2B solutions, ventures, whatever you want to, want to call them, depending on the situation, you might see that it's not always reinventing the wheel, right? A lot of times some of the really successful services and products come from existing situations, but done differently or done in a novel way or done in a way that solves pain.

Turning the problem on a 45-degree angle or flipping it upside down and saying, well, let's think about this in a new way.

Absolutely. And sometimes it's solving pain where it's very obvious that the marketplace is open to having that pain solved or something to be, you know, expedited or made more efficient. And sometimes I think, you know, the really interesting things happen when you're offering something that wasn't offered before to place on top existing structures or processes and people didn't even know they needed it. So, you know, sometimes you think about category changers And you think about, you know, let's even say like an Uber, right? Like, I wasn't really sure when Uber came out that I would ever be using something called Uber Eats to get food delivered to me. I, I, you know, or for example, Amazon, who started out in books. I mean, if someone told Amazon to just stay in their lane, stick to books, I mean, that's not the world we're living in today where Amazon touches so much, so many things that we do in our everyday lives in so many different categories. So you have pivots. You have all sorts of different things. And I think here novelty is the keyword. And I want to say something that I thought was really— I saw something that was very compelling in The Wall Street Journal, a profile of a math professor named Po-Shen Loh. And he is actually touring the country right now apparently, talking about the power of humanity in mathematics leadership. And when asked about AIs, like, you know, generative AI, like ChatGPT, he said something really interesting. And he said, I'll paraphrase, but basically he said, you know, these generative AI machines are very powerful tools at repeating things that already have been done many times before. And, you know, I think that speaks to the thirst for novelty and innovation that comes with thought leadership that is highly effective.

Well, and this— you mentioned category creation. Another piece is entrepreneurship and starting and launching a company around a unique vision. And I think that is in the tech startup space, one of the places where thought leadership and startup culture align very well. You have founders with a vision and they're trying to turn that category creation. You were mentioning Uber, and now we think of Uber as a giant. But if you go back, I was thinking back as you were talking about it, I think their original positioning and branding, or at least the first that I was aware of, was sort of like everyone's black car. And that's still a very small category because unless you're in the major metros, and used to ordering black car service to begin with, you know, saying everyone's black car doesn't speak to you, right? And so how do you get people to realize there's a better way? And I think that's one of the foundational challenges from startup culture. And that piece of repetition, you absolutely need to repeat for thought leadership, but you need to repeat things which are new rather than whatever everybody else has been saying.

Yes. And I think, you know, one of the most important things about thought leadership is that it gives you pause, right? Great thought leadership should stop, you know, really stop you in your tracks for a moment and say, now that, that is an interesting idea, or that is an interesting thought. And so just circling back to the question you asked about, you know, sort of where AI will be helpful. And of course, you know, to your point, I'm speaking about AI where we are today in 2023. I do not have a crystal ball, although, you know, it is interesting because I too am a consumer of thought leadership, reading up constantly on where people, you know, very deep into data science and the AI space are thinking where we might go and soon with the further development and sophistication of AI. But speaking as we are today in 2023, I think that it is for this reason that, you know, thought leadership is this conversation starter where we're thinking of something novel. It's not just a reorganization and repetition of things that are already out there, right? There's nothing I can kind of feed into. Like, there's no, there's no training data that the generative AI will have access to if this is a really fresh idea until you feed it that idea, right? But these, these ideas that are coming out are originating with humans. And yes, of course, if you have great ideas and you give them as training data and other types of things for generative AI, it can learn and it can learn to reason and things like that in the future. And even now, right, we're starting to see elements of that. We're starting to see that even though ChatGPT is the media darling, right, we're starting to see also a lot of excitement around something called AI agents, right? So you have things like AutoGPT and other types of things where instead of being task-focused, it is, it is more of a suite of things where it can prompt itself, right? So let's say ChatGPT, you might have a human who's prompting AI, hey, can you, you know, suggest a listicle of 5 things about a certain topic or etc., etc. Whereas if you're working with an AI agent, instead of you prompting it for every little thing, you're going to kind of give it, let's say, an, uh, a goal. And then the goal means that the agent will then break it down and prompt itself into, you know, but still has to go through the process and you see it kind of, you know, quote unquote thinking right about each piece, assigning itself each prompt and then executing on each prompt. And I think in terms of the future, that's going to be the interesting thing that we'll want to watch. And also that is a concern as well, because things like bias can creep in and will, right? Because if it's learning from humans that, you know, we are not perfect, right? Humans are not perfect and come with their own set of, you know, bias. Also, you know, that AI hallucinations, as they're called, is, is an issue where An AI can very confidently, very confidently, in fact, I mean, if you read it, sounds like it's sure, hallucinate things that either haven't happened, right? You have that lawyer who tried to use it and where it's—

That's exactly the example I was thinking of. So go ahead and tell that story for us.

Don't exist, right? A lawyer erroneously tried to defend a client by citing cases offered to to him regarding case precedents that really didn't exist, but the AI generated them very confidently. That's something we need to look out for.

And then the judge said, "Hey, your opposing counsel can't find these cases. Can you provide the transcripts?" They went back to the AI, the AI generated the transcript or the documents. And made them look real. So they went two layers deep down a rabbit hole of hallucination, right? And it wound up being in some real-world trouble of having to appear before the judge and explain why they thought this was a good idea, right?

Yeah, and I think it really speaks to why human involvement will continue to be, now and in the future, a very important thing that, you know, the humans working with AI, right, augmenting with AI, but not replacing themselves with AI completely because who is minding the store here, right? I mean, I know personally when I've used several different AI tools, generative tools that I have had, for example, links that where I go to click them and I'm getting error pages or that they don't exist. So you absolutely must have a human in the loop because thought leadership done well can mean amazing things for business. Thought leadership done poorly, or if there's inaccuracies, you know, can really ruin reputation, um, in a big way if people feel that they can't trust what's coming from the company in terms of their thought leadership.

Well, and from a thought leadership creation perspective, I think one of the things that you can use AI now, at least some of the tools is as a research assistant. If I were to put it in an academic setting, I would say, go give me an annotated bibliography of what people are saying out there and who are the voices and what are their points of view and take. I think you can task it with that to get a good snapshot of an ecosystem of conversation. But you then have to validate and go, is this real or hallucination? Who do I agree with, where are they sort of going, what is their direction. But there are limitations. It's sort of like having an intern or a research assistant at this point. Mm-hmm.

You know, look, even if you weren't a research assistant, there are reasons why we need one— you know, not just one person minding the data and minding the resource. You know, whenever you have an important piece of thought leadership, that is being put out there by a company, I would hope that more than one person looked at that. And I— absolutely, I would hope that more than one person checked on it. So I think in general, AI or human, really, if you're working on an important piece of thought leadership, a few different sets of eyes should be looking at that.

Well, and it depends on the size and scale of the content, right? So you may have someone who is a distinguished expert in your organization, maybe they're technical expert and they have deep domain expertise and they practice thought leadership. If they get on LinkedIn and they post something based on a conversation or something like that, that's totally fair. But if you're going into mid to long form, then, and something where you're actually claiming research or you're claiming backed by data rather than subject matter expertise, Yeah, you want multiple eyes on that. In fact—

Yeah, perhaps that's my background. I was speaking about it more from a company level, anywhere from a small, medium, to large size company. If a company is putting things out there and you have more than one person available to work on it, that's really best practices, right? You want to have people looking at that. Oh, absolutely.

Absolutely.

But sure, if you want to put out something you're opining on LinkedIn, yeah, absolutely. But then it's on that person who's solo opining on LinkedIn you know, please check your sources, make sure your citations actually exist and that you're getting your statistics right and so on and so forth. Even before, you know, our, our podcast taping today, you know, I wanted to make sure that I got the authors of that B2B thought leadership report right. I went and I double-checked that it was Edelman and LinkedIn who put it out, et cetera, et cetera. Went to the original source, you know, looked through it several times to make sure I got my data right. So you have to do these things, but it is not a responsibility to put onto the AI unmonitored.

You can't skip doing the homework that's needed to be done, right? You still have to do the legwork on that. If you're enjoying this episode of Leveraging Thought Leadership, please make sure to subscribe. If you'd like to help spread the word about our podcast, please leave a 5-star review at ratethispodcast.com/LTL and share it with your friends. We're available on Apple Podcasts and on all major listening apps, as well as thoughtleadershipleverage.com/podcast. And so you talked about from your perspective, and most of our listeners are practicing thought leadership from an organizational perspective.

Mm-hmm.

But you've been in several different roles across your career. One, from content marketing into thought leadership, but you've been in boutique agency world, you've been in large house consulting, one of the biggest houses managing some of their thought leadership. You've also worked with large tech companies and their thought leadership, and now you're advising smaller firms, VC-backed startups, et cetera. And I wanna ask you about some of that journey. How has the world of thought leadership opened up over the course of your career, given that you came from content marketing to begin with?

Yeah. Well, even before my content marketing, I had an editorial background, right? Mm-hmm. So at the time that I was making the shift over from editorial to content marketing, that was kind of a happening, right? There was a big, a big wave of— I would say a large wave of former journalists, digital journalists, editors, etc., who were finding new homes at some of the places that you talked about, right? Consulting firms, boutique agencies, companies. And these are former journalists taking that expertise and sensibility and now coming sort of, you know, some people would say it's the dark side. That was kind of a joke, right? But I don't think it's the dark side at all. I think it's just a different, a different way to utilize your skill set. But I think the good training that comes from that about checking your sources and, and making sure, you know, what you're doing is, is meticulous, all those things serve thought leadership and content marketing very well. It kind of ensures, because you've had that kind of training and experience, that you're not going to do a sloppy job and that you are, you know, you're taking it seriously in terms of double, triple checking, crossing your T's, dotting your I's. But in terms of the content marketing journey, I think that it was a very interesting time when I was at a boutique agency which was just on the verge of being acquired by quite a large kind of legacy player that, you know, why all of a sudden was a legacy player interested in an acquisition of a boutique content marketing firm or acquihires, and so on and so forth. So at the consultancy, you might see things like acquihires, or, you know, of content marketing and thought leadership leaders. And so why is that? And I think this comes back to, you know, something that we talked about before, that there is a connection to sales. I mean, you know, again, you know, we, we always, we always focus on why content marketing has, you know, a directly, you know, and a very obviously discoverable path to sales. Yeah.

You talk about the funnel, you talk about lead generation and you know, what's the next step in the process in your call to action.

Right, right. It's right. Exactly. Like even just that there is a funnel. Well, there's not that same kind of obvious funnel for thought leadership yet. I even talked about, you know, at the top of this podcast about that there have been studies, you know, done that say very clearly that thought leadership can influence at the highest levels of decision makers who have the budget to approve things like, you know, projects, sales, and pricing and things like that. And so I do think in the future, maybe one of the ways that AI can be useful in not so much generative AI, but in a, in a analytical way, right? Because machine learning and such as like, you know, large language models and things, machine learning is a subset of AI, right? AI can do so many things. But I think aside from those things, AI in general, perhaps there will be some way in the future that we can get more great data on how thought leadership directly impacted sales. Because I think that some of those datasets are very large and perhaps hard, or let's say labor intensive, in terms of a lot of people hours to, you know, do. So I think that AI might be maybe something we can tap for the future to figure out, you know, better analyses to find out how thought leadership was useful.

Well, and you put out the concept of attribution and sales attribution, right? And between marketing and the sales team and product and research, there's always sort of a debate on what was the thing that helped nudge and is this— do we get 5% credit? Do we get 10% credit? You know, and you're fighting over credit on a sale, right? I think the ability to track and look at large datasets incredibly useful. But you also then suggest something from the analytics point of view that for thought leadership, I think, would be super helpful is the ability to frame a hypothesis as someone practicing thought leadership and then have basically AI go search through massive data sets to look and see, does that hypothesis play out? So that you could spend the human time asking the questions and the smart questions. I wonder if, right?

Yeah, I mean, it would be great to not be as in the dark as some people feel about showing the fruits of that thought leadership labor. So yeah, I think that would be a welcome addition. And that does not mean at all the relationship of having the AI write thought leadership for you.

No, no.

It would be a tool akin to— I guess a good analogy would be how an accountant uses a calculator, right? Right. So I would be very concerned if my accountant called me up and said, I just want you to know that this year when I do your taxes, I'm giving it completely over to the AI and I'm not going to have any human involvement at all, or minimal human involvement in the strategy yet. I'm just going to give it over to the AI, so I'm still going to charge you the same. And, and I would say to the accountant, are you kidding me, right? And on the other side of that, if my accountant called me and said, by the way, there's like a super new calculator that I can use, it's state of the art, and I've elected to not use that in my practice, I would also question that as well and say to the accountant, well, doesn't that put you at a disadvantage if there are all these new sophisticated tools out there and you're eyes wide open electing not to use them in your practice, well, that's, that doesn't seem like a very strategic move. So I think again, you know, it's harmony, right, of the human beings utilizing AI as very sophisticated and effective tools to help them to augment but not to replace. And also, you know, again, to, to really be wary and, you know, mindful of things like bias, inaccuracies. These are really important questions that are coming up right now that people are looking at that I think are really, really key, especially when it comes to company reputation.

Well, and they are thorny questions that are not answered quickly or easily and almost require not only individual introspection sometimes, but also societal self-awareness of what training data are we feeding a system, right?

Mm-hmm. Yep.

And that's going to take a while to sort out at the very least. So as we begin to wrap up, I want to ask you a question I usually close with, which is this. You've been in the world of thought leadership now for a while. What advice would you give your younger self, either when you were in content marketing or going back to editorial, to help you prepare to be better practicing thought leadership?

Okay, I feel so strongly about this that it's just going to roll off my lips.

Go for it.

Have the, the fortitude and bravery to fight for quality over quantity. There will be forces at play, I'll just leave it like that, where you will feel pressure as a professional to produce quantity where you know that a quality piece of content is really where it's at. And it will be up to you to advocate for quality over quantity content. And sometimes to do so will require bravery on your part.

I think your comment on quality is incredibly useful because here's what— you can create a lot of low-value pieces and just sort of churn and burn and just keep ginning them up. But if you create one good piece and one high-quality piece, you can repurpose it again and again, different formats, different perspectives, different modalities. That will have a life and a usefulness much longer than saying, hey, did we put something out today?

Absolutely. Absolutely. And also, as we continue to incorporate things like generative AI in our practice, I think people will also have a taste and a thirst for things that don't sound like things that were obviously created, like listicles from generative AI, which usually are the kinds of the things you're seeing on the quantity side. So I think that in some ways, as we become more sensitive and knowledgeable about the kind of content that generative AI can create, it will create even more of a thirst for human innovation, human novelty, those thought leadership pieces that are very forward-thinking, that look around corners. We will be even more thirsty for those things moving forward.

So Stephanie, I want to thank you for joining us for this conversation, and I want to ask you a question. If someone wants to catch up with you, how did they do so? Where do they find you?

Yes, the best place to find me is on LinkedIn, so it's linkedin.com/in/stephanie_lgrayson.

Fantastic. Thank you, Stephanie.

Thank you so much.

If you're interested in organizational thought leadership, then I invite you to subscribe to the OrgTL newsletter. Each month, we talk about the people who create, curate, and deploy thought leadership on behalf of their organizations. Go to the website orgtl.com and choose join our newsletter. I'll leave a link to the website as well as my LinkedIn profile in the show notes. Thanks for listening, and I look forward to hearing what you thought of the show.