If you mention the Simpsons, you’ve got my attention. That’s how it all started.
Alex Cassidy of UK digital PR agency Distinctly wrote a post about how they were trying to use ChatGPT to build creative campaigns. Their first “campaign” was Simpsons-themed.
Fast-forward about a year and the Distinctly team documented all of their learnings about using AI in an agency in an excellent white paper entitled ‘Integrating AI processes into Digital PR’—How Distinctly took a phased approach to adopting AI,’ which you can download here.
In this episode of the BuzzStream podcast, I’m joined by Matt Foster, the Digital PR Manager at Distinctly, to discuss their white paper and how agencies can (and should) integrate AI into their processes.
Transcript
Here’s the slightly-edited transcript from our talk.
Why was it essential to integrate AI into your processes at Distinctly?
Matt: We might call it the AI minefields.
Yeah, in terms of the processes, we decided it was better to start AI integration into the team fairly early on. There are two parts to that, really one part with the internal capabilities, so making sure that we’re evolving our service and team empowerment so the team knows what they’re doing on these AI platforms.
Secondly, we need to make sure that we’re up to date with the impact that AI is having on the search landscape with AI overviews. On the AI overviews front with a search landscape, we know that marketing teams and marketing professionals that I’ve spoken to, not just clients but at conferences and outside of the working day, come to agencies as the source of advice, the source of expertise, and.
Knowledge is at the forefront of that innovation, and we need to understand the changes happening in the space so we can advise on the best next steps. We’re working with a wider, distinctly organic team to understand the changes in the AI landscape.
But mainly with the first point regarding internal development, which is what we focused on for the AI white paper you mentioned at the top. It’s really all about benefits for the team’s productivity and removing those admin tasks that might get in the way of creative thinking.
So we can improve our service and ensure quality delivery. I think that’s something that teams are doing across the board, and I’m sure there are definitely others.
The digital PR team’s doing it, and other agencies are doing it. What we found specifically is that it’s giving our team the power to innovate through using AI and providing access to the platforms and the fundamental knowledge.
I guess to boil it down, we’re teaching the team to fish, to use that old phrase. So yeah, that was the reason we went in headfirst and developed this. We started in early 2023 when the explosion happened, and that’s when we thought we’d get our acts together and start to develop this.
Vince: Yeah, so it seems like there’s a two-part goal from this. There’s the empowerment of the team, but then there’s also like the knowledge you can provide clients. On AI overviews, correct?
Like with AI overviews, I’m curious if there are any kind of major takeaways that you’d love to share, maybe some tips or learnings, because I, I don’t think that the paper, the white paper itself really focuses too much on that, but I feel like it’s an interesting thing.
I know we weren’t planning on talking about this, but it sparks my interest as we’re talking right now.
It’s changing every day, obviously, and by the time this comes out, it might be a bit different. But I’m curious if there are any specific things or new guidelines or ways that your team thinks about creating content that might be relevant to the changing AI overview landscape.
How has AI changed the way your agency thinks?
Matt: Yeah, sprung this one on me a little bit, Vince, but yeah, no, that’s good. That’s good. That’s what we’re here for. In terms of why it’s changing, we are, we’re conscious of the way that it’s changing reporting in reporting into clients and reporting our value. We know it’s opened up a new field of reporting where we’re not necessarily just reporting on exposure in organic results.
So share a voice in organic results. It means that we’re now looking at the data coming from AI overviews and how much referral traffic we might be getting from platforms like LLMs, ChattyPT being the obvious one, or Gemini.
Fundamentally, we’re speaking to clients and starting to open up the conversation that is opening up now.
This is another metric that we’re going to need to track, and there’s a new traffic source coming to the website when we’re thinking about brands being linked on the AI overviews. But then there’s another side of things when we’re talking about the PR element to it specifically.
It’s not necessarily just links coming from the AI overviews. It’s also the information that’s being featured in the overviews where we know that it’s more likely to be informational content, and there was a little bit a few months ago. A good example is that we run data-led campaigns quite a lot for certain clients because we know we can leverage them over a long period of time, et cetera.
And it’s useful to approach them from multiple angles.
With AI featuring this informational content, we’re opening ourselves up with data-led study reports to be featured more in those overviews. It opens the question as to whether we move our priority towards these like report led pieces of content where we’re actually, we’re trying to create newsrooms within our client website rather than doing Maybe the more fun, creative approach, maybe a fun landing page, maybe there’s a value difference between the two of those.
I’m not saying one’s right or one’s wrong, but yeah, it opens that question. I suppose a good quick example of where it opened that up is in one of the campaigns that we did, which was a data-led campaign. We put a press release out there to the news.
It was featured in the news, and then it was covered by a competitor website in their news section. And actually we’re ranking highly for the For a good relevant search term around the study, but in the AI overview, our competitor, because they’ve featured the press release that they’ve been summarized and linked to in the AI overview.
The question that arises is whether we should totally own all of our output in terms of putting press material on our client website, as well as the onsite report, as well as the content, or yeah, are there any intricacies to this that we can start to control? Yes,
Vince: Matt. Tell me that.
Just I want to make sure I caught that. So you publish it on your client’s website, and your competitor features it in their blog or news section. And the competitor was the one that’s showing up in the AI overview.
Matt: Yeah, this is it’s a competitor who covered the news story. So we promoted the content to press.
With a press release, we got that covered as a news story, and then the competitor covered it in their news section as industry-relevant news. The competitor was then featured in the AI overviews under a highly relevant search term.
Vince: Yeah, it reminds me of the issue with syndication, right?
I’ve seen this a lot: You can get something syndicated, but then Google, even if it’s canonicalized, the original Google will sometimes choose a new canonical. So say you publish something. Get a syndicated post. Sometimes, a syndicated post will outrank the original, which obviously is not great, but that kind of reminds me of a little bit of what’s happening here.
And yeah, I don’t know if there is a great way to control that yet. It seems like people are still trying to understand how LLMs work. You and I actually spoke about this a bit before, but it sounds like I love this idea of data-driven PR these days. I talk about that a lot. I’ve seen that happen for us at BuzzStream, and that’s why I’m leaning into that as much data as possible.
You know, the large language models you read all the time are running out of content, right? They’re running out of things to teach and train the language on, and there’s this idea of information gain, and you should be constantly creating new information that I can pull out.
So I love that.
And, I think, in a way, it can potentially tie into the 2nd half of our conversation and the white paper itself.
So, let’s jump over to that. I want to start integrating AI processes into digital PR again. This was a white paper that you guys did. There are kind of three sections, I think of, like the initial kind of onboarding, how you started it, and then you get more into what exactly you learned from it.
I would love to get your top-level learnings because it feels like this is something that other agencies and in-house teams can really learn a lot from. I’d love to get your take on what agencies or in-house teams can learn from this if you had to boil it down into a few action items.
Can you share some top-level learnings from your AI Whitepaper?
Matt: Yeah. So what can they learn from the AI white paper specifically? Yes. Yes. I would say the number one learning from it is to encourage an ecosystem. I would warn against the thinking that AI is going to be a new product output or a new service line or necessarily a new top to bottom way of doing something.
I think with our learnings over the last year, we’re finding that the real innovation, which is useful every day within our team is happening within the team. So it’s individual team members who have been taught to have a fundamental knowledge of how to use these platforms of the. output from these platforms, quality output from the platforms look like, and then with that fundamental knowledge, they’re able to go through their working day with the thought in the background that I’m doing this task, which is taking me X amount of time, but actually, if I just consult an LLM, then I might be able to have a weirdly a conversation with this AI machine, but actually to solve this issue to complete this task in strangely a bit more of a humanistic way by having that conversation.
Yeah, I think the main thing would be that is, is to really encourage that ecosystem of everyday innovation, make sure the team is. is up to a certain standard of familiarity with the platform.
Vince: Matt, sorry to interrupt. I want to make sure listeners know when we talk about AI and LLMs that you, your team used are we talking mainly ChatGPT?
Were you dabbling in Gemini, Perplexity?
What AI technology did you use for this study?
Matt: We, so for the white paper and in general, ChatGPT is probably the most used across the team. In the early stages of adopting it within the team. with the team, we just pushed everything that way. We pushed everything towards ChatGVT. There was always the conversations around Gemini started doing XYZ or Claude has started doing XYZ.
Claude is meant to be the better one for actual language output in terms of being more human. But in, in terms of the learning process, we found that Just focusing on one, it helped put the focus in one place with the team and it could be consistent across everything.
Vince: Yeah, it seems like ChatGPT is also where most of the tools you see are based, so it’s the kind of idea that, and I was told this at my previous job before I started BuzzStream, I was working in an agency.
We had a similar push to try to integrate AI into the systems, into the processes, I should say. And it was like, oh, we could use X, Y, Z. Tool, but ultimately, all of those tools are built off of chat GPT and open AI. So it’s better off just learning how that works and learning the prompts, and that’s what most of these tools seem to do: take the prompting off of the plate.
They have very good prompts set up, yeah. So I love that. And one of the things that we talked about—I think in the white paper—and you and I spoke about was, aside from the knowledge, right? Like your team learned a lot at the onset, but then there are some kind of actionable, tangible results.
And 1 of them you talked about was creating unique tools. That was 1 of the things that came out of it. And 1 of the ones. What you mentioned was the Headline Grabber tool. I’d love to hear just like a brief take on what that is. And then if there was anything else that kind of came out of it tool wise.
What’s the Headline Grabber tool you’ve created with AI?
Matt: So yeah. The Headline Grabber tool was developed internally at Distinctly. It was used and hosted on the Distinctly website. So anybody can access that. And really it was created with the idea that We could create something for digital PR professionals to create or retarget headlines to different publications and different niches.
And more generally, just to bounce ideas off, I think it was the thought process wherein, instead of trying to reinvent the whole campaign, it’s just the single element that we need to improve the efficiency of. So we know that PR teams are regularly retargeting headlines to different publications, whether that’s tabloids or broadsheets, taking the top level.
So, how can we improve its efficiency? Yeah, it’s accessible on the Distinctly website. And to be honest, when you were saying about the tools made out of simple prompts, when you know how it actually works, it is. It’s just a very simple prompt in the backend where the specific parameters were already edited for anybody.
anybody in that. But yeah, if anybody’s just coming onto AI and just learning how to use it, then it’s then yeah, it’s a nice little tool to be able to change your outreach process.
Vince: Yeah. I’ve built plenty of these kind of custom GPTs, I think is what they call them in chat GPT.
Now that I’m finding myself getting more. Used to integrating that in my workflow. Every time I create a podcast like this, like I will ask chat GPT to write the description, I’ll feed it, my whole transcription of our chat and then with some time codes, pick out the time codes, write me a brief blurb or summary.
You usually have to go in and tweak it a bit, but it’s, it just is a shortcut, right? Like you, you don’t. I’m starting to find the things that it does well, and it’s that kind of stuff. But I’ll also do, write me some, give me some headline ideas. And maybe they’re not great ideas, but at least spark something, and it gets me there.
And I love the idea that you said, I forget exactly how you said it, but It made me think of like just having a buddy chat GPT is AI is like your buddy that you can just balance ideas off of bounce things. I use it all the time when I’m writing. It’s like, how can I write this more clearly?
Just. Having another person in the room almost who’s can be smart but also it’s like a very basic, just idea machine, right? I want to ask too, cause I wrote this note down as you were talking, this doesn’t seem now that. AI is, I feel like when AI first came out, a lot of people thought, a lot of agencies, especially, were like, oh, man, this is going to streamline everything.
We’re going to be able to cut costs. We’re going to be able to, have all these new service offerings. And it doesn’t seem like that is the case, right? Is that kind of what you gathered? It’s not necessarily like a cost saving thing. That’s really gonna. Cut costs for agencies and maybe it’s going to cut down some of the time, but for the most part maybe it helps more with efficiency, but if anything, it just seems to be like, we’ll level up the quality of everyone’s work.
Matt: Yeah, I think that’s the main, that’s the main finding from it is the quality, but then of course, agencies product is time as well. Yeah it’s probably somewhere in between. to be honest.
Vince: Yeah. Have you seen, you’ve felt those gains? Like time, you’re, the people actually doing the work, do they feel like they’re cutting down the time it takes to do tasks using AI?
What kinds of gains did you find from AI?
Matt: think there’s an element of that, and I think the, how I’d describe it is that individuals professionals have more time to do the good stuff. It’s the administrative elements, it’s the admin elements. Which, chatGPT, other LLMs are. removing time from which is only a good thing.
It’s only a positive thing because it means that we can be more creative. We can, like you say, we can improve the quality of the work. We can innovate on new service lines. We can serve clients better. We can have longer conversations with clients and really get into what the what that. core offerings are, which of course do to a great extent anyway.
But I suppose a very small example of that is the what do you call them now? So note takers from meetings, that very micro example of just being more present in a meeting instead of having to dip away and take notes or have. Account executive or somebody else working on the account in those meeting taking the notes.
Even if we don’t change that format, where there’s a manager and an executive in the meeting, it means that with the meeting not with the account executive not having to take notes from that meeting, that they are learning a lot more just by being present and by, by being in that meeting. So it’s those little elements where we are seeing the use cases for it.
Definitely. And it’s just a case of making sure that it’s integrated in the team and it’s integrated responsibly as well, because I think there’s taken the note taking example as one, sometimes there’s going to be there’s going to be questions from clients on things like data security, as an example, with using AI note takers.
So it will often be for those that have used it before will know it’s usually another. individual attends the meeting, which is named something weird. And the client might have a question with what’s this guy doing?
Vince: Fireflies or yeah, I’ve had fireflies. I forget the other one. Parrot.
Matt: Yeah, exactly.
Exactly. Yeah, that can be, it’s about education at the end of the day and it’s about making sure that your policy is in place. The use of these tools can work within a framework but yeah, to get back to your original point that there’s definitely a long term gain, which we can see with.
with how quality will improve from using these tools.
Vince: Yeah that’s a good segue to one of the other takeaways that you had in the white paper that I thought was really interesting of using the tool talking about I, I don’t know if this is necessarily like a service offering, but it sounds like something that you use now in your processes, or in your, like a tactical piece, but this idea of using AI for media analyses.
You talked about summarizing media calendars from previous years to help understand maybe it’s a specific industry, like what, what gets published or, who’s doing what are the big holidays, the trends, that, that sort of thing. Could you elaborate a little bit on that?
Cause that’s really interesting to me.
How do you use AI for media analyses?
Matt: Yeah, absolutely. And just to cover it off from the very start, I probably missold it slightly. Calendar analysis that’s clumsy wording, but I’ll explain exactly what it is because I think it’s I think it’s a really good use of AI.
We found it very useful anyway. Its uses cross over with competitor analysis, which is another element that we spoke about as well.
So, media analysis and competitive analysis each contribute to our existing approach.
It’s not necessarily a service line but a product that we deliver, and it can generally be split into three elements being used by the team.
So, first, we’ve got the media analysis for thought leadership and reactive opportunities. Second, we’ve got the competitor review analysis, which optimizes PR positioning and can also benefit website content. Third, there’s competitor link analysis. All of these leverage competitor data to benchmark and improve what we can do for each client.
To answer your question on the media analysis side of things, it’s really about answering the question of where competitors are being featured in the press and for what topics.
The approach for this is just requiring a basic prompt with simple information on competitors, brand name, team members acting as spokespeople, and we can speak to this LLM.
And asked to summarize media coverage which features quotes from competitors and present it in a format, which we find is very important when speaking to LLMs, otherwise it would just spit out paragraphs. Yeah asking them to summarize the media coverage and then look back over the last 12 months for insights on seasonality as well.
So what articles are being, where are competitors being featured in what months and in what publications. From that, we really just find that it removes the need for this deep dive data set analysis or spending time on, on backlink analysis tools, exporting into spreadsheets, needing, almost needing a data scientist to take findings from it.
This means that access to this information can be done almost as we’re going through campaigns. So, it doesn’t need a competitor analysis every quarter or every month, however often you’d like to do it. It can be done by a team member who’s actively doing outreach, and they can have a quick look.
They can speak to the LLM to see how the competitors are doing it and how we can benchmark and improve. And if we took the example, what would we have gotten from that?
We’ve got the basic information on where competitors are being featured in the news over the last 12 months. We can continue that interaction with the LLM and ask it let’s pull the headlines being used Featuring these competitors, let’s identify the common phrases being used in headlines or in the articles or featuring competitors.
And then we can use these to try and replicate the common phrases in what we’re doing. So if we know that it’s engaged media in the past in this industry, it means that we can, okay, how can we use that? And how can we better it? How can we go one step further? And really, if we’re getting a slice of that competitive coverage over the next 12 months, as well as the work that we’ve been doing in the previous 12 months, then it just means that we’re making those incremental gains.
Reporting, clients care about competitors let’s say. So yeah it’s a double win on that front. So that’s the approach to that.
Vince: Yeah, that sounds really cool. I would love to get a snapshot. I feel like I’ve tried this before. I’ll export the anchor text or something of a competitor’s backlinks.
I imagine you had to do a great deal of honing, categorizing your tool. Because that’s one thing I feel like ChatGPT often is, it can be all over the map, they call. If I ask them to categorize these backlinks into the types of websites, some of them will be. They’ll put them all in a bucket just called like general or something.
And yeah, I imagine it’s a lot of work in the back end of that. But that sounds like a cool tool. So, the last main part before I want to get into kind of the latter half of this conversation of integrating AI, like some of your tips for integrating into the agency or your team.
But one interesting thing—and tell me if I got this right—was using AI to prototype campaign ideas when you pitch them to clients. Is that something that I get right? Is that taking that from the white paper?
Can you talk about using AI for prototyping campaign ideas for clients?
Matt: Yeah. Yeah. At a at a basic level, The details that we included from that is I’m sure anybody working in PR or digital PR will have had a scenario where they really believe in an idea.
They go to a client, pitch it to the client, and it’s it hasn’t conveyed it hasn’t quite landed. You know it’s a great idea, but maybe it’s a bit too creative for them, or maybe they just can’t quite get there. So really all we were saying with that is, It’s using generative AI for specifically for things like imagery.
If we can convey an idea better with the use of imagery, it means that we don’t have to have somebody mock up the imagery or have somebody spend time on creating the imagery when it’s not actually going to be used for a campaign. We need to look at quicker solutions to that. So generative.
Vince: I love that.
And is that something that you use, like our graphic design? Is your design team at the helm of that, either even though they’re not, mocking it up are, or is it the prs who are just feeding dolly or whatever mid journey, whatever image generator you use.
Matt: It is generally the PRs leading, that is, the people who are creating the slide decks and making that final pitch to clients.
It would generally be those creating those, there would be a consultation internally in terms of, I don’t know, can this be improved? But yeah it’s really one of those time saving things, which also, like we say with the. Improving the quality, we’re improving the quality of the slide decks or the proposals which go to client to convey the idea better.
And that little edge might be the thing that changes it. It means that someone gets signed up.
Vince: Yeah, I love that. I worked at an agency for a long time, and probably the most frustrating part is when you do have a great idea and you just can’t seem to get on the same page with the client for whatever reason.
Or, sometimes, you’re looking for examples of something that exists, which can take a long time. Like you’re trying to find a similar example, right? I run into that still with, BuzzStream content when I’m writing a blog post, I’m looking for, what is that one, piece of content that I saw that was similar to this and this industry, but yeah, being able to have that shortcut to, digging around, uh, I think that’s great.
Okay. Matt, let’s quickly jump to the second half of this. And there are a couple of key things that stood out to me about integrating AI into Distinctly. The very first thing that you did was surveyed everybody on their knowledge level. And at the end, you surveyed again.
Tell me a little bit about why that was so important in this process of teaching the team about AI.
Why did you survey everyone on their knowledge level?
Matt: Yeah, so like you say, right at the very start, I surveyed the team, and it was a straightforward questionnaire, really to understand what skills were within the team already and where the gaps were. So what that enabled us to do was to, I suppose it’s best described by when we were going into this AI initiative, we wanted to make sure that it was as team led as possible because we were aware that it’s, We were all learning together that the world was almost learning together at this point.
So there were going to be some people who’ve experimented with it already, whether that’s to create an image or to maybe create an article or support them in whatever way. So we wanted to understand what skill sets were across the team and where that really helped was the people who had already developed some skill sets just through experimentation.
We could look to them to lead some of the training sessions across the team. It helped that it wasn’t a top-down training. It was more of an okay, let’s learn from each other. So then when we get into the end of the first phase, which is the first quarter, the first three months, we’re targeting all being at relative zero.
So we’re all at the same level, and we’ve all learned from each other how to do each of these AI skill sets. When we say AI skill sets, we can split them out into things like support in press release writing, image creation, and all the different facets that you can imagine it can be applied to.
So yeah, that’s where we started off from, and that’s where it was useful. The secondary benefit to it is that when we came to the end of the second quarter, the second phase, when we’d gone through more structured workshops and more learning and team sharing, it meant we could survey the team again with the same questionnaire, and then we could start to figure out, okay, where’s the understanding growing?
Where might there still be gaps? There are always going to be some gaps in some places, but yeah, we could start to see the progression of the team from Survey One to Survey Two, which was amazing to see. We actually saw that the largest progress progression was among the executives in the team.
That was great to see. What we’ve done is we’ve pulled everyone up to a good standard of understanding, which helped to lay the foundations for what I was saying before, which was encouraging innovation. Across the team, we were then at a point where digital PR executives were conducting the outreach, feeding back from journalists, building media lists, etc.
They were the ones with the skill set to identify where Chat GPT or other LLMs, AI could support their work. So yeah, it was a beneficial process.
Vince: Yeah, I like that. That stood out to me. I get a couple quick hit questions here, but the one is really standing out to me.
As I hear you talk about this, I put myself in your shoes when I was at an agency, a team manager, time was always working against you, right? For the one hand, everything is based off of, billable hours, right? And an agency, especially an agency, billable hours, but even if you’re working in-house, you have your work that has to be done for the daily task of your job, right?
You’re writing content, pitching an initiative like this, and speaking candidly, it could be tough to push through, right? It could be tough to motivate people to work outside the bounds of their job title or their everyday duties. How do you fit that in? How do you motivate people to learn above and beyond to push their roles?
I’m sure you have the benefit of working with some great people at Distinctly, and I’m sure hiring goes into that, hiring the right people. But on a simple billable hours level, is this something that you bill time to? If not, you’re basically losing time that can be spent on agency work to train your team. So talk to me a little bit about that. I feel like it’s a big challenge for many people in many different industries and companies.
How do you justify investing time into non-billable work (like learning and integrating AI) at an agency?
Matt: Absolutely. It’s an investment in development at the end of the day, isn’t it? It’s making sure that we’re, yeah, providing the headspace in order to provide the training and for the team to go off and innovate and explore and do all that.
And I’m glad you mentioned about like the setup in the background, because that’s absolutely true. Nothing really happens individually in the team without the company having a mindset of. a focus on training and kind of integrating that with things like one on one meetings and line management and all that kind of thing.
So firstly, nothing’s going to happen if the back end’s not in order. But yeah, at Distinctly as a whole, we’re pretty hot on the utilization and making sure that everyone has a good balance between client workloads and internal activity, so training activity. And if we know that if we’re not managing that effectively, then client activity is always going to take priority.
So it is something that we want to manage because we know that learning is really important. For the AI initiative specifically, time was assigned to each team member. Every team member had time each week to, to explore, to create to try things out on AI. And we took a fairly open approach to it.
Everyone had time each week, or at least they had time assigned at the start of the month, where that time was spent wasn’t really that important. We didn’t demand that everyone spent a Friday morning on trialing AI. Funnily enough, it was usually Friday that it happened, but but I’m sure that’s going to be the same for everyone.
And the only ask that we really had from the team is away from this time assigned each week, we asked that anything that was found within that time, any learning that was found within that time, was put into a shared slide deck. Then we would go through that shared slide deck in person in a team meeting, and we would we’d talk about it where we talk about the learning failure was totally okay.
We had to ensure that we communicated that failure would be a part of this. Failure was part of learning, I think was the actual phrase that we used. So sometimes people came into these in person meetings and said, I tried this out.
I tried X, Y, Z, I tried this prompt. Then I tried this communication with it and actually, what came out of it was a horrible disfigured image that we wouldn’t ever use for anything, but that’s a learning and sharing that learning with the team means that the teams, they’re not going to go and try and Use those prompt to create images, et cetera, et cetera.
Yeah, we found that really important. I suppose when we talk about motivation, sharing things in a team meeting is a good motivation. Let’s say, I think if there’s the need for someone to share something, you don’t want to be the person who’s not sharing something. I like that.
Vince: Yeah.
A little social pressure. Exactly.
Matt: Exactly.
Vince: Yeah. Matt, I know you’re a busy guy. I don’t want to take up too much more of your time here. I think a good way to wrap this up is just to get your take on AI’s place and AI’s role in PR in general for the future. We talked yesterday about some news outlets using PR right now.
I’ve even heard of Google paying publications to write full AI articles like a test. I don’t know if it’s still going on. I haven’t heard much from it, but this was maybe six months ago or something. What’s the place? Agencies aside, it’s just digital PR. PR in general, where does AI go from here?
What’s your take on the future of AI in digital PR and the journalism industry?
Matt:
Where does AI go from here? Specifically for PR teams, I think if we’re looking at the wider ecosystem, we include an example of where journalists and news teams are using AI in house to optimize their time. And really everything that we do at PR is leading from journalism to a large extent. We will go where the journalists go.
We will be affected by what the journalist’s day looks like when the journalist wants to receive news. So if we’re to look at it broadly, I think there’s going to be more time for journalists to engage with PR for news stories. On the whole, I think there’s probably even faster new cycles, which will be crazy to think of because they’re fast enough already, but that’s old man Foster talking. I think journalists are likely going to have more columns inches to fill.
But I think if journalism develops at the same way that PR companies are all the way that we’ve all the ways that we’ve developed in terms of optimizing our time. I think news companies are also doing the same thing on their side.
We know that journalists receive hundreds of emails each day, and that for me is a very simple element where news teams can optimize their time in working through those emails and having the time to engage with PRs.
If I were to explain this more fully, in the white paper, we talk about NewsQuest, which is a UK local news network, and we reference insights from Jody Doty Cove, who is the head of editorial AI at Newsquest.
So the fact that they’ve got a position like that itself means that, of course, they’re moving forward, they’re experimenting with these, and Jody’s said that over the last year or so, they’ve talked about using a news creator tool, which they say is similar to employing AI as a hyper-efficient writer.
It can transform information from the journalist to create first drafts, which can then be verified and finalized for the journalist. So being fed data from the journalist to create the first draft. And if we think of that from a PR perspective, the question is more how can we be the ones to provide this NewsQuest News Creator tool with the data to create that first draft.
Yeah. And actually, nothing’s really changed. All that’s changed from our perspective is that the journalist has more time to read these emails that are there, sifting through them to feed this news creator tool then and have an article come out at the end of it. So yeah, essentially we’re, as PRs, we’re still connecting with humans as journalists on one side, and then the journalists just have more time To delve into their stories, to source more reliable quotes, or to source more, more interesting data to support that.
That is a full-circle moment, isn’t it? But yeah that’s, I think, things are heading that way. There’s time optimized from the journalist side of things, and I think that it’s only going to give PR teams more time to, to engage with that.
And we haven’t even opened the question on thought leadership and appearing in AI overviews, whether Helpful content updates, whether we need to push forward our thought leadership, whether we need to push forward our clients as thought leaders in the industry and all that side of things, I think digital PR is in quite a unique space at the moment where it’s connecting this AI development.
to what’s changing in the SERPs and in news publications as well. So, it’s just about understanding what’s happening and making sure that we’re able to connect the dots for the clients that we work with.
Vince: Yeah, and I’m glad you didn’t go the other route of saying AI is going to destroy journalism, the media, fake news, and everything else.
But let’s keep it positive. I think there are a lot of positives that can come from this. And as long as you’re staying positive, educated, and in the loop about what is happening, I feel like there are always positives to take from this sort of thing. So I highly recommend everybody check out the white paper from the Distinctly team integrating AI processes in digital PR.
I will link to it in the show notes. I’ll link to the headline grabber tool and anything else that we mentioned here. You can find Matt eyes on LinkedIn. He’s most active there. But you can also check out the Distinctly website where, you know, Alex Cassidy’s original articles that kind of prompted this discussion.
You can find there. A big thank you to Matt Foster, again, digital PR manager at Distinctly. Thanks so much, Matt, for coming on. We really appreciate it.
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