You Ask, I Answer: Generative AI and Public Relations, Part 2 of 5

In this episode, this is part two of five of an interview I did with Stephanie Moore of Kent State University about generative AI in public relations. Excellent. So, how has the incorporation of AI tools affected the risk the roles and the responsibilities of your team members at our firm? Everyone is expected to use AI. Everyone is expected to find as many efficiencies as possible and be as productive as possible.

Um, because we our our model is value-based, right? We want to uh the way we build things, the way we we do projects and things is all value-based because you're not paying for how long it takes me to do something. You're paying for the final outcome. Um, and as a result, we want people to use AI as much as they possibly can, still fact-check it, still make sure that the output is good. Uh, in the same way, the the way we think of AI is this it is the world's smartest intern, right?

It's the intern just graduated, they have 255 PhDs, they've got a PhD and everything, but they're still an intern. They still don't know your company, they don't still know your clients, they still don't know how you do things. So you would never say to an intern, oh, intern, hey, go write me your press release. Right, you never do that. You would give the intern a creative brief.

Say, here's what I want you to do. Follow these steps exactly. The intern does it, great. You've got a high quality output. The same thing is true for AI.

If you think of it as a the world's smartest intern, you will get really great results out of it. And that's what we teach our staff. That's awesome. Um, so you kind of already got at this a little bit, but in terms of the benefits, what do you think are the most significant benefits of using AI in in the field? So all technologies are measured on three factors: save time, save money, make money, right?

AI saves enormous amounts of time. So the difference between a 66-hour book pitch or a one minute and 52-second book pitch of and the outputs are about the same quality, is a massive time savings. Most PR agencies, this is a this is actually a very serious problem for many PR agencies. Most PR agencies bill by the hour. They have an agency blended rate.

Like our agency blender rates, $182 an hour. Well, Jem and I did the task in five dollars and sixty-six minutes of work. So your your bill rate as an agency, your ability to make revenue if you're billing by the hour is severely endangered by AI. You must switch to value-based billing immediately. However, um for companies that that do figure that out, they can save money.

Some of them we will be very regressive and say, okay, let's fire as many people as we possibly can. PR firms that are say managed by, oh, I don't know, private equity firms. Um, we'll be firing people as fast as they possibly can because that's how you increase profit margins. And all those firms run on net margin. Um and then make money is this is the thing that again, PR folks don't realize the power of these tools.

They are the AI tools are skill levelers, meaning that they give you skills you don't have. So Suno, for example, the audio company, um, can make songs, like it can make halfway decent songs. I have made custom songs for clients um live on stage and they've been stunned by it. Like, I can't play music, I don't play any instruments, you don't want to hear me sing, but the tool can do it. I know how to prompt the tool to create high-quality outputs.

So anything that is within the domain of communications at all is on the table for a skillful PR firm to say, well, we offer that too. Hey, you want um analyst relations. Hey, we offer that too because we have an AI model that can skillfully ingest all these things. Hey, you want corporate strategy. We have that too.

Um, I was showing an example earlier today in a talk I was giving where I took all of the job listings of Novartis, uh, the pharmaceutical company and all the job listings of Pfizer, and I said to a language model, digest this down. These are 4,000 job listings. Tell me the corporate strategy for each of these companies for the next 12 to 18 months because you never hire for something you don't care about. You only hire things that are critical to your mission. Otherwise, you'll find an agency or a contractor.

Um, and the tool put together a 20 page business strategic business analysis analysis that is as good quality as anything you would get out of McKenzie or Bain. Um, and your firm could offer that. Your firm could offer that as a value add to your services. So it's a question of do you know what to ask the tools? Do you know how to think not like a PR person, but like a communicator and a strategist.

And then can you get the tools to do it? Love that. I think that's great. That also gives me some um ideas for again prompt engineering to teach our students. So we'll talk about that a little bit.

So you kind of talked about the effectiveness and the efficiency, you know, sort of in the public relations um field. What about uh what type of advantages does AI offer in terms of data analytics or data analysis and audience targeting? It depends on the kind of AI you're talking about. There's three different classes, right? There's regression based AI, which is like, hey, do uplift modeling.

This is, for example, how you measure public relations. You say, I have all this background activity in you know, ads running and emails, and I have the data from that in my various marketing systems. And hey, we got a placement in the Wall Street Journal on this date, and we know these things have a decay rating of about three days. Do uplift modeling. Find out how much of the delta between what was before, during, and after, we can attribute to that accounting for everything else.

So that's a very that form of modeling has been around for eight years now. We were doing that at my old shop. Um, this classification modeling, which is um, hey, I've got uh a great big pile of data, and I need to organize it, I need to analyze it. Um, social media sentiment analysis, for example, is very, very common uh for that, and something that you you would want to see people using when it comes to data analysis. Where generative AI comes into play is that it is extremely good at qualitative processing of text.

If you have a big pile of unstructured text uh that you need to analyze and understand, these are the the best tools to do it. Real simple example, I was doing a project for a client um two days ago, and this client's a fairly well-known client. Uh, I said, let me go see what the community has to say. So I went over to the Reddit forum that is uh about that particular industry, and I downloaded uh 2,000 posts and like 4,000 comments about this thing, stuffed it into Google's Gemini, and said, Distill out the top line trends and then the emerging trends in what people are saying about this client. And it spit out the analysis, handed it to the client.

The client's like, that's uncomfortable. Um, I said, Yep, sure is, but that's what's happening in the data. Now, how long would it have taken me to read 6,000 posts and comments? It certainly would not have taken me 90 seconds. That's how long it took Gemini to process all that, and then another two minutes to do the analysis the way I wanted it.

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