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We have known about media bias effect for decades: the belief that the media is biased against your side of a debate. New research finds that the same belief applies to misinformation. While the research was focused on political issues, the underlying cause applies equally to misinformation about brands, companies, and business issues. In this short midweek episode, Neville and Shel find that the PR industry has not yet acknowledged the phenomenon, which requires strategies to address it. Links from this episode: Think the Media’s Biased Against You? You Probably Think Misinformation Is, Too The Hostile Media Effect The Influence of Hostile Media Perceptions on Misinformation Beliefs and Sharing Hostile Media Effects on Twitter, Social Identity, and Media Bias Perceptions Fake News Has Real Effects on Consumer Demand The Impact of Fake News on Consumer Behavior and Market Outcomes Political Identity, Media Trust, and Susceptibility to Misinformation The next monthly, long-form episode of FIR will drop on Monday, June 29. We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email fircomments@gmail.com. Special thanks to Jay Moonah for the opening and closing music. You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog. Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients. Raw Transcript Neville Hobson:Hi everyone, and welcome to For Immediate Release. This is episode 519. I’m Neville Hobson. Shel Holtz:And I’m Shel Holtz. When you think about all the misinformation out there—fake news, bad-faith spin—do you think it’s mostly aimed at your side of an argument or the other side? Most of us, if we’re honest, feel like it’s aimed at us. And there’s now research saying that feeling is nearly universal. Even though the research was based on political discourse, it has a direct connection to organizational communication. We’ll explain right after this. All right, let’s start by backing up for a second. There’s a concept called the hostile media effect. It’s been around since the 1980s. The original study showed pro-Israeli and pro-Arab students the exact same news coverage of the exact same event. Both groups walked away convinced it was biased against their side. Everyone saw exactly the same footage, but they reached opposite conclusions. And the more committed you were, the more certain you were that the media was out to get you. That finding has held up for 40 years, and it’s a big reason trust in news has collapsed as politics has gotten more tribal. Now let’s add the new wrinkle. A team at the University of Amsterdam asked whether that same instinct applies to misinformation—to fake news. They surveyed 4,000 people across Germany, the Netherlands, and Poland around the 2024 European elections. Nearly half said their preferred party was particularly targeted by misinformation. Ask about the party they liked least, and that number got cut in half. They’re calling it the hostile misinformation effect, and it got stronger the more politically engaged people were. The more plugged in people felt, the more victimized they felt. Now, Neville, you might think that’s a political science finding. But the mechanism underneath isn’t about politics; it’s about identity and motivated reasoning. Every brand, every company, every department is an identity group. Your most loyal customers are partisans. Your most engaged employees are partisans. The research says the people most attached to your organization are exactly the ones primed to believe any criticism out there is unfairly targeting them. Now think about a crisis. Your defenders don’t need convincing that your critics are unfair. They already assume it. The minds still open are the uncommitted people in the middle. Among neutrals, knowing more made them see less bias. It’s only partisans who dig in. So if someone criticizes a brand that some people love, the brand’s biggest fans may see that as an attack rather than just an honest review—and respond in kind. There was no crisis, but now maybe there is. There’s an internal angle here, too. Picture a layoff memo or a return-to-office announcement. Leadership reads it as fair. But every faction inside the company—by department, by level, by tenure—is wired to read the same message as unfair to them. “We said it neutrally” is no defense because neutrality is in the eye of the beholder. This notion reveals a trap for communicators. When bad coverage hits, it’s tempting to wave it away as misinformation. But “fake news” self-destructed as a term the moment it got weaponized to mean “any story I don’t like.” Cry misinformation every time you’re criticized, and you train your audience to tune out the label. You also look evasive to the exact neutrals you need to reach. So this is where I want to bring you in, Neville. We’ve spent years on this show talking about declining trust and the misinformation environment. This research says the problem isn’t just that there’s more bad information out there; it’s that people are wired to feel personally besieged by it. And I’m not sure our profession has reckoned with what that means. Neville Hobson:Yeah, it doesn’t sound like it, Shel. I don’t think so. It’s actually quite fascinating looking at the Nieman Lab article you shared with me in our Slack channel and seeing the depth of the research on a topic that I had no idea was even a thing to look into. I found it interesting in a number of areas. For instance, the study you quoted from the 2024 European Parliament elections got me thinking. The tendency to see misinformation as directed at you seems more pronounced the farther right politically someone is. That caught my attention because isn’t that precisely what we’re seeing in the United States with the Trump MAGA movement? Here in the UK, we’ve got Reform and an even newer party that’s emerged further to the right. Those groups often function as an echo chamber for the kinds of messages Trump promotes. They’re constantly criticizing anything anyone else says as an attack and talking about issues in ways that rile people up and stimulate hostile reactions in return. We see a lot of that in this country right now. It’s interesting that this study has been done, and I think the way you’re connecting it to organizational communication is a good call. It certainly gives us a lot to think about. One question it prompted in my mind concerns the point about engagement and partisanship. If the more engaged and partisan someone is, the stronger this effect becomes, does that mean an organization’s most loyal stakeholders are actually its most vulnerable to this kind of perception? What do you think? Shel Holtz:Absolutely. I think that’s exactly the connection we can draw between this study and organizational communication. If somebody criticizes the company based on an experience they had—and let’s say that criticism goes viral—and it was sincere and well-intentioned, then the partisan defenders of that organization are going to feel attacked. They’re likely to respond in kind and escalate a situation that probably would have faded into the background if left alone. I think that’s one of the fallouts organizations can experience from this phenomenon. The more partisan you are, the more besieged you’re going to feel when you perceive something being said about the brand or organization as unfair—even if it was perfectly fair. Neville Hobson:So how do you address that within the organization? Shel Holtz:That’s an interesting question, and it’s hard to fight because you really can’t argue people out of it. One related concept is the third-person effect—the idea that other people are more susceptible to media influence than we are ourselves. In other words: I can see what the media is trying to do, but other people are going to be fooled by it. When you stack that together with the idea that your group is being unfairly targeted, you get a complete worldview: I’m clear-eyed, my group is the victim, and everyone else is gullible. There was a fascinating study where researchers took 661 Coca-Cola drinkers and showed them a real fake-news story—a 2016 hoax claiming that Dasani water was being recalled because parasites had been found in it. The finding was that the people most confident in their own ability to spot fake news were the most convinced that other people would be fooled by it. They were also the ones most loudly demanding that Coca-Cola take corrective action. Sometimes the stakeholders who are screaming “Do something about misinformation!” aren’t reacting to the actual threat. They’re reacting to a belief that other, less discerning people are being duped. That makes the challenge even more complicated for communicators. Neville Hobson:Yeah, it’s weird, isn’t it? The next question that comes to mind is this: If both sides feel targeted regardless of what’s actually out there, what should communicators do? Is there an approach that works when perception is this detached from reality? Shel Holtz:From an organizational standpoint—and I’m less interested in the political implications for purposes of this podcast—I think there are a couple of things. First, the more prebunking you can do, the better. When one of these situations comes up—a bad review, criticism from the media, negative reporting—you can immediately point people to information you’ve already published that addresses the issue. Having a bank of credible material you can reference may keep people from getting unnecessarily riled up. The other thing is to respond quickly, but not emotionally. If you can maintain a sense of calm—or even a sense of humor—you increase the likelihood that others will follow suit. If people see that the company isn’t feeling besieged and isn’t acting attacked, that may help tamp down some of the reaction. Neville Hobson:So this becomes a major issue for trust, doesn’t it? And I imagine the role of artificial intelligence in all of this only exacerbates the problem. Is that how you see it? Shel Holtz:Yeah, I do. The flood of AI-generated slop out there—content targeting your organization, your brand, or your leaders—is only going to increase exponentially. If somebody has an axe to grind and wants to flood search engines or AI summaries with negative content, AI makes that dramatically easier. Now, to be fair, the research we’re discussing focused on information published through media outlets. That may be an important distinction. People might be more skeptical of something posted on a blog or LinkedIn than something published by a mainstream news outlet. That’s where this research suggests people feel especially attacked. Neville Hobson:That was my thought as well. Going back to the study, we’re looking at this from a political perspective. We all consume information online, and most of us have preferred sources. Meanwhile, mainstream media is going through what seems like a growing crisis of trust. You see constant battles online between people citing one newspaper versus another. It’s distracting, and it wastes an enormous amount of time and energy. It also got me thinking about how I react to some of this. The suggestion that people on the political right are more susceptible to this phenomenon doesn’t really describe me. I’m more in the middle. I don’t react the way I see some people reacting—especially on that delightful conversation platform known as X. People vent their spleens there. Maybe it makes them feel better, but I don’t think it advances understanding in any meaningful way. Then again, perhaps that’s not the point. The point seems to be: I win, you lose. And that’s very much the Trump approach. It feels like that’s where much of this is headed. Shel Holtz:Yeah. One of the stranger findings from the research was that when researchers examined whether people felt more victimized after their party lost an election, the results weren’t what you’d expect. You’d think the losers would feel most targeted. Instead, the people whose party won were more likely to believe their side was being targeted by misinformation. Feeling besieged isn’t necessarily about being under threat. It’s about identity. And since you mentioned X, there’s another interesting strand of research. People may dismiss something because they saw it on X. But researchers found that the source of a message can trigger hostile media perceptions independently of the content itself. Your company’s name on a statement can be enough to act as a bias cue for people who already have feelings about you. The exact same words can land very differently depending on whose logo appears at the top. That’s worth thinking about because it means message discipline alone can’t solve a credibility problem. Neville Hobson:This is a bigger dilemma than it might seem at first. A real conundrum for communicators. The Nieman Lab article is lengthy, but it’s definitely worth reading. Shel Holtz:Yeah. And there will be links in the show notes to some of the original research on identity bias as well. The reason I chose this topic is that I’ve never heard it discussed in PR circles. I’ve never seen it covered in PR textbooks or books about public relations. This was completely new to me. That’s one reason I’m still struggling with an answer about how to deal with it. But it certainly starts with recognizing that it’s happening. Neville Hobson:I agree. It was new to me as well. The more I think about it, though, the more it seems to describe the environment we’re operating in today. Now we just have to figure out what to do about it. Shel Holtz:Yes, we do. And that will be a 30 for this episode of For Immediate Release. The post FIR #519: Is Misinformation Biased Against You? appeared first on FIR Podcast Network.

The history of public relations over the last 30 years is a litany of one failure after another — failures to recognize and embrace technologies that represented seismic shifts in how people and organizations communicate. The internet. The web. Social media. Smartphones. The video shift. And now, with AI, the industry seems poised to do it again. As many organizations explore how AI will reshape them, PR agencies still seem unable to figure out billing models to replace the now-useless hourly rate. In this short midweek episode, Neville looks at a post from Stephen Waddington that laments the industry’s intransigence, and Shel and Neville discuss what PR should be doing. Links from this episode: The future of jobs in PR: will we get the third technology shift wrong too? (by Stephen Waddington) It looks like PR has its head in the sand about AI (by Neville Hobson) Senior practitioner neglect of digital/social skills a huge threat to PR’s future (2015 post by Shel Holtz) Once Again, This Time with AI, the Communications Profession Will Be Late to Embrace a Valuable Technology (2023 post by Shel Holtz) The next monthly, long-form episode of FIR will drop on Monday, June 22. We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email fircomments@gmail.com. Special thanks to Jay Moonah for the opening and closing music. You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog. Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients. Raw Transcript Shel Holtz: Hi everybody and welcome to episode number five hundred and eighteen of For Immediate Release. I’m Shel Holtz. Neville Hobson: And I’m Neville Hobson. So here’s a question I want to put to you right at the start, and I’d like you to sit with it as Shel and I work through this topic today. Public relations as a profession has faced two seismic technology shifts in the last 30 years. In fact, more than two, but I’m just going to mention these two. The internet arrived in 1995. Social media arrived around 2007. And in both cases, PR largely got it wrong. Not wrong in the sense of ignoring the technology. Wrong in the sense of fundamentally misreading what it meant. In 1995, we thought the internet was a publishing problem. In 2007, we thought social media was just another broadcast channel. And the disciplines that grew out of both—search, content marketing, influencer marketing—were largely built by people who weren’t us, people outside the profession who saw what we missed. So the question is: are we about to do it a third time? We’ll address that question in just a minute. That’s the challenge Stephen Waddington lays down in a piece he’s just written for Influence, the member magazine of the CIPR, the Chartered Institute of Public Relations. Stephen is someone whose thinking I respect considerably. He’s been one of the sharper and more honest voices in UK PR for years. And this article comes off the back of a book he’s just co-edited, AI and Public Relations: A How-To Guide for Implementation and Management, published in May. And what he’s arguing in this piece is that this is no longer a theoretical debate, as job reductions are happening now. He gives specific examples. Three account executives doing media monitoring—that’s now one tool. A two-person intranet team—that’s now a fraction of the effort. The UK government has listed public relations professionals among the twenty occupations most exposed to large language models. We’re on the list. Early career employment in those sectors is also in relative decline. Now, Waddington is not a pure pessimist. He sees a plausible optimistic path. The career pyramid becomes a diamond. Firms building roles around insight and risk management rather than billable hours. A rough near-term reduction of perhaps fifteen to twenty percent in entry-level positions, followed by net growth as scope expands and new roles emerge, the way digital did after 2000. He thinks in-house teams especially have an opportunity here. When AI absorbs the routine, it frees space for the work that corporate communication teams have always needed but rarely had capacity for. But he gives serious, genuine weight to the pessimistic case too. And this is where I think the article gets interesting. He references Martin Ford, author of The Rise of the Robots in 2015, and Ford’s argument that previous technology waves hit one tier of the workforce and the tier above absorbed the displaced. This time Ford says there’s no tier above. The advisory work that absorbed previous shifts is itself the target. Waddington doesn’t fully accept that in his article, but he doesn’t dismiss it either. And then there’s the argument that I think should be keeping every agency head and comms director awake at night—the pipeline. He’s hearing a common response from firms right now: freeze your apprenticeship schemes, freeze your graduate intake, let AI cover the production work. And he calls that, bluntly, organizational self-harm. Because in five years, those organizations will have nobody who understands how the systems actually work, why they fail, and crucially when to override them. You cannot run an advisory profession without a pipeline. And you cannot build a pipeline if you spent five years dismantling the entry points. So that’s where I think we should start today’s conversation. Not with the technology, with the choices. Because Waddington’s closing argument, and it’s what I find compelling, is that human agency still exists here. The technology isn’t making decisions. We are. The question is whether we’re making them wisely, or whether for the third time in thirty years, we’re about to hand the future of our profession to people who aren’t us. Shel, what’s your instinct on this? Shel Holtz: Very much what yours and Stephen’s is. I have been saying for decades that the public relations industry is always, always, always late to the game when there is a new technology that is going to shape the way communicators do their jobs. We were late to the internet, for sure. We were late to the World Wide Web. My first book on communicating online—well, actually, my first book was on intranets, but the first one that got any attention was Public Relations on the Net—came out before the World Wide Web, before there was a graphical user interface. So there were plenty of opportunities for PR before the web, based on the capabilities of the internet. Then we missed the web, then we missed social media. In between we missed some other seismic shifts—mobile, being able to communicate with people based on the fact that they now had this computer in their pocket. We missed the pivot to visual communication, we missed the pivot to video communication. And now, yeah, we are poised to miss the pivot to AI. And that’s not to suggest that PR people aren’t using it. I think they are, but I think they’re using it at a very superficial level and are succumbing to a lot of the hype out there about things like job loss and “get rid of your entry-level people.” That’s all mundane drudge work that the partners and senior people don’t want to do—the account execs—so hand that all off to the AI and you don’t need to pay those people anymore. And you’re exactly right. I was listening to a podcast over the weekend where they were talking about the same issue, but they were talking about it in the context of law firms. And they were making the point that the associates that are brought in out of law school do the drudge work that the partners don’t want to do. They write contracts, right? They do things like that. And now that the AI can do that, who needs them? Well, the question becomes: where do the future partners come from when the ones who are already at the partner level retire? There’ll be nobody to take those jobs. We are not rethinking the industry, and we’re not rethinking it from two perspectives. One of those perspectives is the agency. The other perspective is the in-house side of communications. They’re two sides of the same coin. But I think we need to split them apart and look at them in terms of how we need to reinvent the profession. You and I have talked about reinventing how we bill, how we price, because the hourly model makes no sense anymore. But what does an entry-level person do if the AI can handle a lot of that drudge work? And it can. I mean, we’ve talked about on this show that I’ve set up a Hermes instance and it is out there. In fact, I haven’t checked my Telegram account yet, but there should be 10 links to recent news stories that are prime for me to news-check because I set up an agent to do that. I have an agent set up, a skill set up, that I can deploy anytime I want to. It is set up to analyze the websites of twenty-two of our competitors. And all I have to do is tell it what I want it to analyze. Do I want it to look at how they handle their project portfolios? Do I want it to look at how they handle their thought leadership? I can ask it any of those questions and it’ll come back and give me a very nice report. I could absolutely set it up to do media monitoring. I’m starting to question the need for my media monitoring service at work, although the agent that I have set up to do some of this certainly can’t get behind the paywall the way that the media monitoring service can, because they pay the licensing fee for all of those. So if the AI can assume all of this work, it’s not a question of saying we don’t need entry-level people. It’s a question of reimagining what entry-level people should be doing. In terms of AI: What should they be doing with AI, and what new things can we be having them do that we haven’t thought of before, or that we always wished they could do if they didn’t have all of this drudge work that they had to spend their time on? It’s time for a reinvention, and I don’t see anybody talking about that. I haven’t seen a whole lot of ideas about where all this should go. Neville Hobson: Yeah, I’m with you on that a hundred percent. Exactly my sentiment as well, that you don’t see people talking about this in a truly serious way. I see on LinkedIn—if that’s any barometer, I don’t know if it is or not—but I see people mentioning this now and again and “we ought to do something about that.” But there’s no webinars, no seminars, no get-togethers on the topic of reinventing the agency, let’s say. It’s a topic I’ve written about myself, and value-based pricing versus time-based pricing. And it’s interesting how Stephen Waddington addresses that topic in his article. It’s quite a pointed observation he makes that’s worth pushing on. If you’re still selling time rather than value, he says, AI will break your model. That’s a direct challenge to the billable-hour structure that much of agency PR still runs on. So the firms getting this right are building around insight, outcome, and risk management instead. It’s worth asking how many firms are actually making that structural shift versus just talking about it. Not enough. Doesn’t mean to say they’re ignoring it. Far from it. I think it’s largely because they don’t know what to do. How do they address this? So there’s an opportunity for someone with some insights and answers to help educate firms like that. There’s a consulting opportunity, if you like. Shel Holtz: I was thinking exactly the same thing. If somebody’s looking for a pivot in their career, that sounds like one to me. Neville Hobson: Yeah, yeah. So we are at that place. Again, go back just three years, 2023, when we wrote our pieces about that CIPR survey, and twenty-five percent of the respondents said they’d never ever use AI. It was pretty absolute, the answers. Here we are, three years later, and I bet you that number’s down to five percent, if not less. I can’t imagine anyone—and it causes a very broad question, “would you use AI, yes or no?” It’s a bit like “should we stay in the EU, yes or no?” I mean the Brexit referendum—well, people, what a dumb question. But so that’s where we’re at. But I believe a lot of the landscape is now so polluted with everyone’s opinion that it’s very confusing to zero in on what are the issues I need to be thinking about in an organization. Plus, I see so many people—I saw one just this morning—someone’s got a PDF book on how to move your business to selling value, basically, not time. And it’s not how many hours you did, it’s what did you deliver to the client. So it’s great, but it needs to be more authority than that, I think. And this is where the profession comes in—professional bodies like the CIPR, the PRSA in the US. The CIPR has done a good job in raising awareness about AI in the right way, in context related to public relations. They’ve had this AI panel for some time now with senior practitioners leading it. This book’s come out and it’s got a lot of support from practitioners in the UK and beyond. So maybe now is the time that this is going to get taken a bit more seriously than people do. I think though what Stephen worries about—and I think it’s not a misplaced worry—is the point that people are being laid off. Layoffs are happening all the time and most people believe it’s because AI is going to be more efficient and all that kind of stuff. And there must be some truth in some of that. But he also mentions something quite interesting in his article, because he says that most of the conversation about AI and jobs focuses on redundancy risks from above—leadership cutting roles. We’ve talked about that quite a bit. But Waddington notes a quieter pressure running in the opposite direction. Junior and mid-career practitioners are walking out of organizations they consider too far behind the curve. So firms that move too slowly aren’t just at risk of getting the technology wrong, they’re at risk of losing the people who could help them get it right. The talent drain is bi-directional. Now that’s an interesting element to bring into this discussion, I think—that it’s those folks who are walking away. He doesn’t say, and I hadn’t found anything before we started recording, as to where they’re all going. Are they leaving the profession entirely, or are they just looking for a place that—in a sense they feel it’s worth going to this company because they’ve got it switched on, that they’re clued into this? So maybe that’s the state we’re in. Doesn’t answer the questions, mind you, and they’re coming thick and fast now, I think. I see, again, LinkedIn is a kind of barometer of sentiment, if you will—not in the analytics way, but the feeling you see expressed in some posts from some people who are worth reading about it. And that includes many of the people that I follow and that you would follow as well. So you’re seeing this, but it’s all very random. That’s the thing. And it requires something more than that. And voices like Stephen’s, yours when you were talking about this—we’ve missed about three, four, five times, that sort of thing. What’s going to make people really pay attention to this? Shel Holtz: I hate to say it, but it’s the same thing that has always made the industry pay attention, and that’s when they suffer financial pain. The reason we have not embraced as an industry these technological changes is our billings were fine. We were doing just fine as an industry financially. So why should we make this risky change to something that we don’t quite understand and we’re not convinced is going to have all that much impact or will necessarily stick around all that long? That leaves an opening for other industries—advertising and marketing—to sneak in. It also leaves an opportunity for boutiques that specialize in this to start up and take money off the table that was there for the PR agencies that were already in business. And this seems to be a recurring pattern: if we’re not feeling the financial pain, we’re not gonna make any change. As soon as we start to feel that pain, as soon as we see our clients going to the boutiques and going to the marketing agencies, then we go, “we better change.” And then we’re behind the curve. So I think that’s the big issue and the big challenge—to be proactive rather than reactive when these technologies create these opportunities, or create the requirement, if we wait, that we must change because we’ve already seen these revenues go to somebody else. One thing to keep in mind: absolutely there have been layoffs within the industry and they have been attributed to AI. It is important to keep in mind though—and this was reinforced in that very same podcast I was listening to that I mentioned earlier—that if you look at economic data, there’s no evidence of mass layoffs as a result of AI. The unemployment rate is pretty much where it was before all of this. The number of new jobs that are being reported, at least in the US, has actually been pretty strong. The jobs report the last month was quite encouraging. So we keep hearing about the mass layoffs and they may be coming. They may not. Because frankly, what I see—and I don’t know if this is unique to the construction industry, I doubt it; I think it may be a bigger issue in the construction industry, but I think this is probably true of most jobs—is it’s not the job that gets replaced by AI, it’s tasks within the job. And then there are other tasks that the AI can’t do. The other thing is that there are things that we have wished that we could do, but haven’t had the time to do, from an internal comms standpoint and even, I suspect, a PR standpoint from inside the organization, the client side. I mean, I remember when I was in my first corporate job. This was with Arco. I was there from ’77 to ’83 with some brilliant communicators, but the company believed in it. So they funded the internal comms department. We had 25 employees in internal comms in five cities. And each of us had beats, just like you were a newspaper reporter with a beat. I had two beats. I had Arco Petroleum Products, which was the gas stations and the merchandising of cans of motor oil and things like that, and Arco Marine, which was the oil tankers that transported oil mainly from Alaska down to the refineries along the West Coast. And I spent time—I mean, that was my job, was to go hang out, to spend time, to shadow somebody, to do a ride-along, to ride on a tanker, to spend a day at one of the gas stations and really get a sense, and to be able to report on this a little more intimately than just calling somebody and doing an interview over the phone. And in public relations, I think it’s important to remember that “relations” part of the public relations label. How do you build relations? Well, if AI really does take away a lot of that drudge work that we spend the time doing while we’re sitting at our desk, then we have time to get up from our desks and go out and hang out with the publics that we are dealing with and build those relations. And why wouldn’t we want to do that? AI can’t do that. AI can’t get up, get their car and go to where the public is. Maybe it’s a community relations organization, maybe it’s a division of your business. Maybe it’s a customer base that is gathering—well, let’s say it’s Ford Motor Company and there’s a car club that’s meeting. Whatever it may be, we have the opportunity now to become much more entwined with those publics. And do a much better job of understanding them. Yeah, we still want to do the data, we still want to do the analytics, but there’s nothing like sitting with them and looking them in the eye and talking with them to build an understanding that’s going to help you communicate with them and help you build trust among them. That’s just one idea of what we can do with this freed-up time. And this is an important point—and I saw this in one of the reports that came out just last week, I think it was—the value that we get from saving an hour because AI can do it just leaks out of the bottom of the organization if we don’t know what we’re going to replace that hour with that has value. And we hear about all the savings of time that AI is going to give us. I haven’t heard a whole lot about how organizations are figuring out how to reallocate that time among those employees. Neville Hobson: Yeah, yeah, neither me. No, I agree. And you do hear a lot of talk about the concept of that. I mean there’s lots in this topic, Shel, really, and you’ve thrown some bright light on some of the things we should be doing. I like the idea of going out to meet your publics, as it were. It’s winding the clock back, actually, to how we used to do all this back in the day, before all this tech was there. Shel Holtz: Yeah, it really is. Neville Hobson: We had to go out and find the sources and interview them face to face and, you know, meet down the pub or whatever. So maybe we need to examine what worked in the past and bring it to the fore again. Shel Holtz: When I was a newspaper reporter, before I made the switch to corporate communications, I was with a local community daily newspaper, and I used to go hang out at the bar after work where all of the government workers hung out after work. Got to know them, got to listen in, got some pretty good stories out of that. But also I could pick up the phone and call some of these people because they knew me. I wasn’t just the reporter who called when I needed a quote or needed some information. I was the guy they just had a drink with. Neville Hobson: Yeah, exactly. Lessons to learn there, I think. So yeah, lots of good ideas here. I think Stephen Waddington did a good job in literally describing the landscape and expressing some of his concerns. That’s prompted this conversation. So let’s hope this adds to the topics that people need to be talking about. So listeners, hope this is helpful. Shel Holtz: And listeners, if your organization is actually making some changes and doing some pivots, we’d love to hear about it. And that’ll be a 30 for this episode of For Immediate Release.   The post FIR #518: Is the PR Industry Blowing It Again? appeared first on FIR Podcast Network.

Most agency owners know AI can write a first draft or clean up copy. Far fewer have figured out how to use it as the strategic sounding board they’ve always needed. In this episode, Chip and Gini explore how to use AI tools as a thought partner, not just a content machine. Gini’s example is a client who asked her to map what a PESO model maturity ladder would look like for an organization. She described the situation and constraints to Chat GPT, and keep pushing the conversation forward. Six weeks of iterative back-and-forth surfaced ideas she wouldn’t have reached on her own, including finding the gaps when the AI was willing to poke holes in her thinking. Chip points out that for owner-led agencies, that 8pm Friday idea you don’t want to dump on your team now has somewhere to go. The tool doesn’t care what time it is, and it has no stake in whether your idea succeeds or embarrasses you. Both hosts advise to direct the AI to ask you questions rather than just answer them. It takes some coaching to get a tool that genuinely engages rather than validates everything you propose, but once you’re there, you start getting real value. One warning they have is that these tools are not always consistent. The same AI that helped you build a strategy three weeks ago might question it today with equally compelling reasoning. Stay in the driver’s seat, and treat AI-generated recommendations as input, not conclusions. [read the transcript] The post ALP 305: How agency owners can use AI as an always-on thought partner appeared first on FIR Podcast Network.

Neville and Shel dig into a provocative Harvard Business Review article that argues most marketing teams are structurally unprepared for the speed and scale that agentic AI now enables. The bottleneck, the authors contend, isn’t the technology; it’s the operating model. Neville and Shel connect the piece to conversations FIR has been having for the past year: AI as orchestration rather than automation, professionals shifting from supervisors of tasks to directors of systems, and 2026 increasingly framed as “the year of the agent.” At the center of the Harvard piece is the idea of a “brand code” — a machine-readable knowledge system that lets specialized AI agents continuously create, adapt, test, and optimize marketing in real time. Communications urgently needs its own equivalent: a “narrative code” containing executive voice profiles, message hierarchies, sensitive-topic guardrails, and escalation rules. Whoever builds it first, he warns, will inherit the agentic stack, and if marketing gets there first, comms will be stuck with a system never designed for crisis, controversy, or stakeholder complexity. The episode also includes some concrete examples and early thoughts on Hermes, Wispr Flow, and where human judgment still has to win. Links from this episode: Redesigning Your Marketing Organization for the Agentic Age The Year of the Agent: What it means for the future of communications Google Summary: The Year of the Agent: What it means for the future of communications If you work in PR and you’re unsure how AI agents will help you, this should help. The next monthly, long-form episode of FIR will drop on Monday, May 25. We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email fircomments@gmail.com. Special thanks to Jay Moonah for the opening and closing music. You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog. Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients. Raw Transcript Shel: Hi, everybody, and welcome to episode number 513 of For Immediate Release. I’m Shel Holtz. Neville: I’m Neville Hobson. Over the past couple of years, we’ve heard countless conversations about how AI is changing marketing and communication. Most of those discussions tend to focus on tools — faster content creation, better personalization, workflow automation, synthetic media, analytics — all the things AI can supposedly do more quickly and at greater scale than humans. A new article in Harvard Business Review published last week takes the discussion somewhere much bigger. Its argument is not simply that AI will improve marketing productivity. Its argument is that AI may fundamentally redesign how marketing organizations themselves operate. The article is called “Redesigning Your Marketing Organization for the Agentic Age,” and the authors argue that most marketing teams are structurally unprepared for the speed and scale AI now enables. The reasoning is interesting; we’ll look into this in a minute. AI has already accelerated software engineering and product development dramatically. Products, updates, campaigns, and features are being developed and shipped much faster than before. But marketing organizations, they argue, are still largely built around sequential workflows, siloed teams, approval chains, meetings, handoffs, and coordination-heavy processes. So even when AI speeds up individual tasks, the organization itself still moves slowly. In other words, the bottleneck isn’t necessarily the technology, it’s the operating model. What struck me reading this article is that in many ways it feels like the continuation of conversations we’ve already been having on FIR over the past year. About a year ago, Shel demonstrated some of the early agentic AI capabilities we were beginning to see emerge — systems that could move beyond simple chatbot interactions and actually take actions across workflows, tools, and platforms. At the time, it felt experimental, slightly futuristic, and maybe just a glimpse of where things might be heading. Since then, we’ve repeatedly returned to related themes on the podcast: AI as orchestration rather than just automation, and managers becoming directors of systems rather than supervisors of tasks, to name but two. Recently, the wider communications industry has been framing 2026 as the year of the agent, a fundamental shift from generative AI, which creates content based on prompts, to agentic AI, which acts autonomously to achieve long-term goals. The rise of such autonomous agents requires a focus on agentic orchestration, with professionals acting as AI engineers who guide, manage, and audit these digital employees. As we discussed on this podcast last year, communication departments will adopt a hybrid structure where humans focus on high-level strategy and creativity while AI agents handle high-volume procedural communication tasks at machine speed. We’re already seeing a marked impact on marketing and public relations. The Harvard piece explains how companies such as HubSpot and AWS have begun putting this model into practice. They say organizations are achieving measurable gains, with marketing materials adapted up to 98 times faster, unit costs reduced by 80%, and click-through rates increased up to 17 times. Research from BCG has demonstrated these benefits at scale. Organizations embedding agentic AI into marketing workflows, the research has found, can achieve up to a threefold increase in ROI, campaign speed, and content volume. That’s why this Harvard article feels so interesting to me. It doesn’t contradict any earlier conversations; it complements them. It takes many of the ideas we’ve been discussing conceptually and places them inside a concrete organizational model. The authors propose something they call an agentic marketing organization — essentially a system where humans and AI agents work together continuously across multiple layers of activity. At the center of this idea is what they describe as a brand code: a machine-readable knowledge system containing brand strategy, customer insights, messaging frameworks, business rules, governance structures, and operational guidance that both people and AI systems can understand and act upon. Once that foundation exists, specialized AI agents can continuously create, adapt, test, distribute, optimize, and report on marketing activity in real time. It’s a vision of marketing that starts to look less like a department and more like an operating system. But what really caught my attention wasn’t the technology itself so much; it was the shift in the role of the marketer. Because beneath all the platform architecture and workflow diagrams is a much deeper question: if AI increasingly handles execution, what becomes the real value of marketers and communicators? The article argues that value shifts away from production and toward judgment — setting intent, evaluating outputs, interpreting signals, shaping governance, and guiding how the system evolves. And that raises some fascinating questions for communicators. But first, Shel, your demo of those early agentic capabilities was about a year ago now. As I mentioned earlier, it felt experimental and slightly futuristic then. So what’s changed since then? Shel: It feels like ancient history now. If I were to look at that, I’d probably shake my head and say, “my God, that’s pretty primitive.” The way it worked was, it took a screenshot of every site it visited and then acted on the screenshot. So it was a very slow and tedious process. The video that I shared, I edited out all of the waiting time for it to go through all of this, because it showed you everything. And those days are long gone. That was clearly a demo. I don’t remember which of the AI models offered that — I think it was Anthropic — but it was just tedious and not all that functional. It did what it was supposed to do in the end, which was to create a spreadsheet with the information I’d asked for. It was some open-source spreadsheet that it used. I ran a similar exercise just last week using Claude Cowork. And this was for a piece somebody in our sustainability department wrote. It was about two projects that had achieved world-first certifications for zero waste, which is kind of a big deal in the construction industry. It’s one of the biggest contributors to landfills and the like, the industry is. So I’m looking to place this article. And what I did was, I told Claude Cowork that I wanted four subagents working: one to look at construction and AEC publications — that’s architecture, engineering, and construction; AEC is the category for the industry. Another one was going to look at sustainability publications. And there was one other, but I also had it look for podcasts where the authors of this report might be invited for an interview. I said, what I want you to do is find the publications and podcasts based on their previous content that are most likely to be interested in something like this, and then create a spreadsheet with the name of the outlet. And of course, divide it into these categories — right? AEC, podcasts, sustainability-focused publications, and the like. Mainstream media was the other category. But I also wanted the URL, I wanted the name of the appropriate person to pitch the article to. And then, based on what that person has written — that particular reporter or editor — I wanted a pitch that was personalized to that person. And I came back in about half an hour, and there was a spreadsheet ready to go. And I had started acting on it. I don’t copy and paste the pitches; I go and take a look at that reporter’s writing and review the pitch and then make some tweaks to it. But my God, can you imagine how much time that would have taken for me to go out and do this on my own by way of research? That would have been hours and hours. And instead the agents went out and did it, and then Cowork assembled all that information into a spreadsheet. I was doing other stuff while it was doing that. I wasn’t sitting and watching, because there frankly wasn’t that much to watch. I mean, you could watch the agent tell you, “now I’m going to go look at this.” But, you know, that’s kind of boring. Let it do its thing. Neville: Yeah. So a question I have related to this, I suppose, is to put it into one practical area, which is: people might think of this in the context of the interaction you have with prompts and the old-fashioned way of doing things that is still prevalent. So how did you — the agents went off and did their thing, and then you came across what they produced and so forth, and it saved tons of time — how did you gain confidence, let’s say, that it was accurate, that there were no hallucinations, no errors? Or is that not the issue anymore with this kind of development? Shel: I believe that hallucinations would still be an issue. It’s still a model at some level doing this work. I mean, it’s Claude with Claude Cowork. I did install Hermes over the weekend. We’ll talk about that in a bit, but it’s an agent platform, an agent framework, and you create the agents to do things. For example, I created one over the weekend that I set up to be a weekly job, and it’s going to go out and look at construction industry news to find things based on our areas of expertise where I work, where we have subject matter experts and thought leaders, to find the top three articles that are ripe for newsjacking. If you remember David Meerman Scott’s newsjacking — things where we can get some stuff out there quickly. Neville: Yeah. Shel: And take advantage of the fact that this is something that people are looking at and gain some traction over it. So every Monday at eight, it’s going to run this job, and by 8:30, 8:45, it’s going to give me the results. And all of this is through Telegram, or WhatsApp, or whatever app you choose to use to interact with the bot. It still starts with a prompt. The difference is that you’re not prompting a question in order to get an answer; you are telling it what task to perform. And in the case of the one that I set up on Hermes, it’s now a weekly task. And the interesting thing about Hermes is that it learns as it goes. It continually self-improves based on the more it knows about you and the kinds of tasks that you’re asking it to perform. So I’m looking forward to seeing how that goes. But so far, I just have the one agent running there. But it’s still a prompt at the end of the day. And in fact, I used — I think it was Gemini — to help me craft the prompt to get the best results I could. I said, here’s the list of requirements, turn it into the best prompt that Hermes will understand and act on most effectively. And it did that. It did a great job. And I’m very satisfied with the results so far. I ran one test of it, so I liked it. Neville: Yeah. So Claude Cowork is kind of at the heart of this. I’m experimenting myself with Claude Cowork — with Claude generally, Cowork sort of. Nothing like you’re doing with this, I hasten to add. But one of the things that I’m very impressed with about Claude is the way in which you tell it the things about you, who you are and what you’re doing, all this stuff — your preferences in how it conducts what you’re asking it to do — in a way that, unlike ChatGPT for instance, where you have to, in a sense, include in a prompt stuff you’ve already told it for something previously, but you’ve got to do that again. It doesn’t kind of remember that in the same way. Claude is different, though. So your setup — I mean, I guess what I’m asking basically is, when you set this up, did it require that level of preparation that is probably desirable to do that? Or was there anything special that you had to do that was outside of what you would normally do with Claude Cowork? Shel: Well, for the byline piece that I was looking to pitch, that I set the subagents out to do their thing in Cowork, I did in the prompt explain what my goal was and what the organization was. I had it look at our company website to get a good sense of who we are and what our areas of specialization are. I gave it some additional information. But then something I do with all of these now — not every prompt, if I’m just in Claude or ChatGPT, but especially with the agents, with deep research projects and things like that — I’ll say, “ask me questions before you go out and do this.” And it usually asks some very salient questions. It’s very good at deducing what it doesn’t know. And the answers factor into the results you get, which is really interesting to me — that it can, if you ask it to, understand where there are gaps in the prompt that it could use this information in order to deliver really excellent and pertinent results. Neville: Got it. So thinking about our listeners listening to this, to how you’ve explained all of this — is it kind of credible and within the reach of anyone literally wanting to do this? Or do you need to have some kind of mental preparedness or knowledge technically to do this? Could anyone just dive in and start something? Right. Shel: Well, I don’t know about diving in. With Hermes, for example, I watched a couple of YouTube videos. I watched one that actually walked me step by step through the installation process and then had a whole section on use cases. I’ve watched more. There’s one on 99 use cases for Hermes that I watched, which was pretty good. So it helps you get in that mindset. But in terms of, can anybody do this? In the world of communications, anybody better be able to do this, because you’re not going to be sent out to look for these sites and assemble a spreadsheet anymore. You need to be able to orchestrate these agents. And that means knowing how to prompt it to get the results that you want. And that’s different, again, from prompting ChatGPT for an answer to a question, right? You are giving it a task, and it could be a recurring task that somebody on your team does. Now, in communications, I still don’t see this replacing a communicator, because every communicator is going to have the human-only or human-required elements of the job. I cannot see one of these conducting, say, an employee focus group. There’s so much that we do. I mean, you know, in public relations, the word “relations” always stands out to me, and maintaining those relations is not something a bot can do. But in terms of what that Harvard Business Review article was talking about, you can swap marketing for communications. I think it’s more true in comms. Comms workflows are more coordination-heavy than marketing. We have legal, we have HR, we have the C-suite. We have to make sure everything’s consistent with the brand and maybe get some brand representation approvals. They’re the owners of the channels that we have to deal with. If marketing needs a brand code — and this was a concept I really liked in that article — communications needs a narrative code. You know, a machine-readable positioning, machine-readable executive voice profiles, message hierarchies, sensitive-topic guardrails, rules for escalating things that emerge that need to be taken up a step in the hierarchy or maybe up to the C-suite or the CEO. I don’t know anybody who’s built a narrative code. Whoever builds this first in your organization, by the way, is going to end up owning the agentic stack. If marketing builds it first, we in communications are going to inherit a system that wasn’t designed for crisis communication, wasn’t designed for controversy or reputation damage or stakeholder complexity — it was built for marketing. And that’s the one we’re going to end up having to work with. You probably remember, Neville, in the early days of social media, Richard Edelman was out there sounding the drum that PR needed to own social media before marketing and advertising got their hands on it, because they would turn it into something inauthentic, right? It’s the same thing here. Neville: Yeah. Yeah. Shel: I think we in comms are going to have to build out the narrative code and let marketing take advantage of the agentic stack that we’ve built. But we need to be in the room when those decisions are being made. Neville: So another challenge for communicators, and I can see that. I think the overall structure of the Harvard piece, as I mentioned in the introduction, is on the organization as a whole. And I think there are examples where that’s in work — I quoted a couple, and then there’s the BCG research, which I found quite interesting. But that’s… restructuring is a way away yet on an organizational level, I would say, for most companies. But the individual actions, such as experimentation you’re doing, are definitely right in front of us, literally right now. And it prompted a thought in my mind, looking at this overall picture, about some assumptions in the Harvard piece that I think are worth looking at for a minute, where the article assumes that strategic judgment remains human, not AI focused, but execution becomes agentic. So I think, okay, then — though history suggests automation rarely stops neatly where people would like it to and where they would expect it to. So perhaps a question that’s relevant to address in this context is: if AI systems — agentic is part of that — increasingly assist with strategy too, which is what they’ll be doing, where exactly does human value migrate to? That’s a broad question, but for communicators specifically, how would we address that one? Shel: I think, first of all, if you’re going to look to the agentic system to assist with the development of the strategy, I would sit down and map out a game plan for that. I wouldn’t just say, “hey, you know the company I work for, come up with a strategy for us.” I would say, first of all, what is this strategy… Neville: Ha ha ha. Shel: …going to be designed to achieve? What do we know about the direction the company’s going and decisions that have been made? I would certainly use it to go out and say, research the marketplace and research our competitors and identify, to the extent that you can, what their strategies are. I would develop the strategy myself, but I would give it to the AI to stress-test. And by the way, some of this is agentic and some of it is just querying a chatbot. I mean, let’s just take crisis communication as an example. No CEO is going to go into a boardroom with an answer from an AI system telling a leader something they don’t want to hear. That is amplified by the agentic stack. If we go in as the crisis counselor and say, “look, I know you’re not going to like this. Here’s my judgment. And I’ve got this information that came from the weekly analysis of sentiment in the marketplace,” so I think it can bolster your argument. It can’t replace your argument. You’re going to walk into that boardroom as a human and make a case. Same thing, maybe, with focus groups. When passive signals in social media, for example, and message boards get gamed, sitting in a room with 10 employees becomes the truth that the dashboards that are out there — the agents that are out there looking at sentiment — get checked against. So when a dashboard says that morale is great and the focus group says it isn’t, I’m going to pay attention to the focus group. I’m going to pay attention to those 12 people in the room before I listen to an agent that says, “well, we’ve been analyzing all the sentiment in Slack and email, and everything is just dandy.” So I think it’s the same with strategy. I think I would never abdicate strategy… Neville: Mm. Shel: …but I could certainly develop it faster and be more confident in its viability by using agents and chatbots. Neville: Yeah, I agree. And it makes me think of, I guess I would say, what’s coming, which is already here in ways that lead to even greater — well, integration, I suppose, is the right way. I’m thinking what you said at the beginning of this segment we’re talking about now, which is, you don’t hand the whole thing over to the AI and say, “hey, go and develop a strategy.” You would do… Shel: And you know there are people who are, right? Neville: Yeah, they will. They will. But it seems to me that this is really, in a sense, the fulfillment of an expectation — a promise — from artificial intelligence tools like this, that you would have a conversation with it in the same way you would with a human being who might be an external consultant or a colleague who’s a subject matter expert or whoever it might be, that you would explore with that individual: we’re developing a strategy for next year, let’s look at how we’re going to do this. You set the framework for how you might start that conversation with your AI assistant. And as you said, this is not specifically agentic; it’s the whole spectrum of what the tools are. And you set it on course to go and research this. And that’s probably what an agentic tool will do. And that to me is the excitement of where this is going — that you can get to that stage, which then I think would address some of the skepticism and indeed alarm bells by some in organizations when they see unfettered technology going all over the place or being asked to do stuff. This, though, makes it credible and gives it some legs of credibility. Which leads me, I guess, to possibly the final question here. We’re seeing this, as you’ve explained, this is light years ahead of the demo you gave a year ago, which gave a signal, a strong sense of what’s possible, where this could go. We’ve seen that fulfilled. It is eminently possible. And you don’t need to be a rocket scientist, as you might have expected you would have to be a year ago. This is doable. And the more people experiment with it in simple ways, like you’ve outlined as a real-world example, they will want to do that in that case. So the question then, therefore, is: okay, fine, a year on from last year, you’ve explained something you’re doing that delivers value quite readily every Monday morning, let’s say. So what’s next, do you see, in terms of developing technology and the developing value people will get from it that would accelerate probably its uptake? How do you see it? Shel: I think that the next thing we’re going to see is an evaluation of every role and where an agent will fit. This is something we went through a couple of years ago. Ethan Mollick was talking about it in his book, Co-Intelligence, before we were even talking about agents — talking about inviting AI to the table and figuring out where you could work it into your workflows. But it was still the chatbot. It was still the, “I’m going to ask you a question and you’re going to deliver some kind of answer.” I think we need to do that again and look at agents. What tasks are we performing, and which ones can we hand off to agents? And I think there are probably roles where this is going to be even easier to do, where you’re going to see more opportunities than in communications. I mean, you know, engineering, for example, I think is wide open for this sort of thing. So I think that’s what’s next — as we do hand off certain (and I’m going to call them) mundane tasks, because this is not the high-level strategy and the human-touch stuff that is so important in so many jobs. But as we hand these off, and it now takes an hour instead of a week, what does that do to the rest of our workflows? What does that do to our organizational structure? One of the things that I was reading over the weekend was the expectation that middle managers are going to be a thing of the past, because what do they do? They handle the flow of information up and down between the people who report to them and the people that they report to. They handle a lot of mundane tasks that might now be handed off to an agent. Agents, according to — I don’t remember who this was who was saying this. It was somebody noteworthy. It might’ve been Dario Amodei at Anthropic, but I honestly don’t remember for sure — but middle managers can be replaced by agents by and large. So what does that do to organizational structure? Certainly flattens it. But now, in terms of those executives who have a lot of people reporting to them, what part of that reporting structure can be handed off to an agent? So I think this is sort of a cascading situation where everything we do leads to a reconsideration of something, that leads to, well, what else can we do with the agents, which leads to further reconfiguration? I think that’s what we’re looking at. And I don’t think it’s going to happen overnight, because, as you alluded to, the technology may be moving fast, but organizations tend not to, particularly when it comes to issues of structure and governance. Neville: I think this is so exciting, to be frank — the idea of the changes we can see coming that will be painful for many. But is it more structural change? It’s a constant in our lives, is it not, with all of this? Something we should embrace emotionally and logically, that we can control this. And I don’t mean control the tech — we can’t do that. But we can control the risk and the benefits of something like this by not reacting to something that’s coming, by, in a sense, embracing it and experimenting with this and learning it. And as you said, if we don’t do this, the marketing guys will. And so we can’t have that. I think… Shel: And then we’re stuck with theirs. Neville: I think it’s something to really pay attention to. So this has been a useful, interesting discussion, Shel, getting your thoughts on this in particular. So yeah, I think we’ll come back to this conversation unquestionably at some point in the future. Shel: No doubt, as we see developments. In fact, as I say, I just started working with Hermes over the weekend, and it was an eye-opener, and I expect, as I work with it more, I’ll have more thoughts about it and my thinking will evolve. I should point out that I did install this on a personal virtual server, not on a company computer. I’m not taking that kind of risk. And it’s my personal account. One other thing I thought I’d mention — you talked about the idea of having a conversation with the AI, and I think that’s becoming more of a focus. And I’ll give you two quick examples. One I already mentioned is with Hermes: you don’t go to a terminal and engage with it or go to its website. You do this through WhatsApp or Slack or, in my case, I’m using Telegram — just like I’d be having a conversation with a person in that same app. But on, I think it was Thursday, I did a half-day webinar that was offered by the Marketing AI Institute, Paul Roetzer’s organization, and it was on AI for writing. And it was very interesting. Chris Penn was among the speakers; he did a great job, as always. But one of the folks there talked about, you know, have the conversation with AI for real — do it with your voice, not with your keyboard. And she talked about a tool, which I haven’t used it yet — I have installed it across my personal computer, my laptop, and my phone — called Wispr Flow. It’s an AI tool. Have you…? It’s pretty cool. I mean, in any tool you’re using, you just click it and talk. And it doesn’t go directly into the chat box; it interprets it… Neville: Yeah, I’ve been using it. Yeah. Yeah. Shel: …and then puts the best prompt based on what you just said into the box. And that’s what you use to prompt the model. And I’m looking forward to giving that a try. And it’s called Wispr Flow, by the way, because if you’re in the office in an open-space format and you don’t want to disturb the people next to you, it understands what you’re saying when you whisper to it. Neville: Yeah, it is interesting. I’ve got a hurdle to jump with it, though, which is getting accustomed to speaking what I want things to be done and how, rather than typing them. You know… yeah, and I haven’t got across that hurdle yet. That’s limiting my use of it. So I’m reverting to the, well, I’m more comfortable typing, I can type fast and all that kind of stuff. But, reality, this is faster than that. And it is… Shel: Yeah, same. Neville: I recognize the benefits of it. I can see this. Not everyone will be used to this. This is not dissimilar to the argument we could have about voice notes. I know people who love voice notes; I don’t. And I know more people who don’t like it. It could be a generational thing, I think to myself. But it’s part of the communication landscape. So you need to get accustomed to these developments. Shel: Yeah. And I hear about voice notes being preferred by some reporters who are being pitched, because it’s evidence that it wasn’t AI slop that’s pitching them. Neville: Yeah, yeah, yeah. Yep, yep, yep. Shel: And that’ll be a 30 for this episode of For Immediate Release. The post FIR #513: Why Communications Must Build the Narrative Code for the Agentic Age appeared first on FIR Podcast Network.

In this episode, Chip is joined by Karen Swim and Michelle Kane of the That Solo Life Podcast for part one of a special crossover episode exploring the practical effects of AI on agencies, solos, and the communications industry. Karen and Michelle share their view that AI is no longer optional. Practitioners who resist it risk falling behind, while those who embrace it can dramatically expand their capabilities. The conversation goes beyond basic content creation, exploring how AI can elevate strategy, reinvigorate professional skills, and free up time for deeper, more creative thinking. Chip, Karen, and Michelle also discuss the importance of treating AI like a new employee — providing context, voice, and guidance to get the best results — and address common concerns around ethics, privacy, and copyright. They encourage communicators who haven’t revisited these tools recently to dive back in, as the technology has advanced rapidly and shows no signs of slowing down. [read the transcript] The post CWC 113: How AI impacts PR agencies and solos (featuring Karen Swim and Michelle Kane) appeared first on FIR Podcast Network.

While there’s no evidence that business leaders are outsourcing the most important decisions to AI, there are reports that many executives are relying on AI to make many — in fact, most — of their decisions. The implications for communications could be huge. Links from this episode: AI Is Changing More Than Work, It’s Rewiring Executive Decision-Making Inside the C-suite: How AI is quietly reshaping executive decisions AI and the future of human decision making C-Suite Executives Dominate AI Decision-Making as Strategy Becomes Priority Decision-Making by Consensus Doesn’t Work in the AI Era How AI Is Transforming the Way Executives Lead Leadership at a Turning Point: How AI Is Shaping Executive Decision-Making Can AI Make Executive Decisions? The next monthly, long-form episode of FIR will drop on Monday, May 25. We host a Communicators Zoom Chat most Thursdays at 1 p.m. ET. To obtain the credentials needed to participate, contact Shel or Neville directly, request them in our Facebook group, or email fircomments@gmail.com. Special thanks to Jay Moonah for the opening and closing music. You can find the stories from which Shel’s FIR content is selected at Shel’s Link Blog. You can catch up with both co-hosts on Neville’s blog and Shel’s blog. Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients. Raw Transcript Neville: Hi everybody, and welcome to episode 512 of For Immediate Release. I’m Neville Hobson. Shel: And I’m Shel Holtz. The inspiration for this week’s report came from a post Brian Solis wrote recently. In it, he argued that AI isn’t just changing work — it’s rewiring how executives make decisions. Once Brian put that in my head, the trend started standing out in other things I was seeing. I’ll summarize the numbers and what they mean for communicators right after this. The numbers Brian pulled together are honestly alarming. A Confluent study of UK private sector leaders found that 62% of executives now use AI to make the majority of their decisions. That’s not some — it’s the majority. 70% say they second-guess themselves when AI disagrees with them, and 46% say they rely on AI more than their own colleagues. On the U.S. side, SAP’s research found that 44% of C-suite executives would reverse a decision they had already planned to make based on AI input. 74% place more confidence in AI advice than in the advice they get from family and friends. Meanwhile, McKinsey reports that 92% of companies plan to increase their AI investment over the next three years, but only 1% — 1 percent — describe themselves as mature in deployment. The money to pay for AI and a sort of blind trust in its abilities are racing ahead of the internal competence to use it. Now, I want to be clear before I go on. I’m not anti-AI, Neville — you know this. Anyone who listens to the show knows I’ve been beating the drum for AI as a tool for communicators and for business in general for a long time. AI as a thinking partner, a research assistant, a stress-tester for ideas — that’s enormously valuable. But there’s a meaningful difference between using AI to inform a decision and using AI to make the decision. And Brian puts this well: AI is becoming the new executive influencer. The problem is that it hasn’t earned that role, at least not yet. So let’s talk about what this means for those of us in communication, because the implications are everywhere. Start with employee trust. The implicit deal between an organization and its workforce is that the people at the top got there because they have judgment and experience and pattern recognition that the rest of us don’t have — or at least they’ve been able to employ it really well and get noticed by the people who promote you into those leadership decisions. That’s the story leadership tells, and it’s the story employees buy into. Now imagine the all-hands where the CEO announces a major restructuring, and somewhere in the Q&A, or worse, on Blind or Reddit a week later, it comes out that the decision was essentially handed to a chatbot. What happens to confidence in leadership? What happens to engagement? What happens to the social contract that says, follow me because I know where we’re going? You can’t credibly ask people to bring their full selves to work, as they say, while you’re outsourcing your own judgment to a language model. Now extend that to external stakeholders — investors, customers, regulators, the board. They’re paying, and in a lot of cases they’re paying a lot, for executive judgment. If a strategic call goes sideways — and you know that happens — the explanation that the AI suggested it isn’t going to land well. It’s going to sound like an abdication, because it is an abdication. And from a crisis communication standpoint, “we trusted the algorithm” is one of the worst defenses I can imagine. I don’t expect that anybody’s going to say that, but it doesn’t mean it’s not going to come out. Just ask anyone who’s worked an aviation incident, a financial services failure, or a healthcare AI misfire. Imagine the reaction when either the leader tells people, or they learn through a third party, that the afflicted stakeholder hears, “Well, that’s the decision the AI told me to make.” And there’s a third implication that I think communicators need to surface inside our organizations: the erosion of dissent. I find this particularly interesting and disturbing. Confluent found that 65% of leaders say decision-making has become less collaborative since adopting AI. The Harvard Business Review just ran a piece arguing that consensus is dead in the AI era. That may be — but debate isn’t consensus. Debate is the friction that exposes bad assumptions. It’s what didn’t happen at that auto manufacturer — I think it was Volkswagen with their emissions standards. They didn’t have the psychological safety to feel safe in dissenting against the decisions being made. In this case, we’re not even looking forward at the leadership level in some cases. If AI is pushing aside the colleague who would have pushed back, whatever process your organization had for dissent just stops functioning. And when dissent dies, so does the early warning system communicators rely on to spot reputational risks before they get out of control. So what do we do? A few things. We push for governance — and if you already have a governance model, push to revisit it. Your governance needs clear declarations of which decisions AI informs versus which ones it actually makes. We coach our executives to talk publicly about how they actually use AI, with appropriate humility, before the question gets asked for them. We build the internal narrative that human accountability is non-negotiable, no matter how good the model gets. And we keep reminding leadership that machine confidence isn’t the same as strategic clarity. Brian’s right: AI is a test of leadership. It’s also, increasingly, a test of communication. Neville? Neville: Well, just to set my position clear on this, too — I’ve been a drum-beater for AI as a research assistant, as a useful tool, since GPT first came out. The initial kind of hysterical enthusiasm was tempered over time, but I use the tool every single day in what I do for work, or for pleasure for that matter. So it’s something I believe strongly in. But I’ve got this, how could you say, in the back of my mind always — this thought that I don’t accept blindly anything the AI assistant tells me. If I’m researching something, for instance, I’m going to make a recommendation about something, let’s say, or I’m writing a report or even something relatively simple like an article for the blog. If I felt I wanted to say this and it’s telling me that, that’s a simple decision: I’m either going to follow it or not. Typically when that happens, I’ll ask it questions to further that angle. But this is something else, what Brian writes about. And The Register — I’ve read their piece — tempered with a bit of hysteria, it seems. I mean, this is a very alarmist piece, or argument, you could say. If it’s saying, as it is — the survey that The Register reports on — 62% of leaders of private sector companies, and according to The Register that’s owners, founders, CEOs, managing directors, the C-level leaders of various types of companies. They didn’t say sizes. But they use AI to make the majority of the decisions, which leads to some of the alarm bells ringing that you outlined. What if it gets out that the AI made a decision when something goes south? You could flip that. What happens if it gets out that an amazing decision that led to the company being massively successful was actually made by an AI? I think it’s inevitable you’d have that sort of focus on it alongside more sane arguments, perhaps. You could argue, well, that CEO is pretty smart that he used an AI to help him do that — as opposed to the other side, which is, gee, we’ve got to fire this guy, he used an AI and it went wrong. So you’ve got to put some balance there. Also, I think you mentioned this earlier, and I agree with you, that there are two angles to every question we might ask about this. One is internal, within an organization, and the other is external. So it is an interesting point. And one thought I had in my mind, the pragmatic question: if a leader changes a decision he or she has made because the AI assistant suggests something different, who actually owns that decision in the end? In fact, whether he changes his mind or not, if the AI said, “I recommend you should do this, and here are the 10 reasons to support that idea,” that are different from what the leader was going to do, and he or she made the changed decision based on that — who actually owns that decision? Or, as I asked myself, is that really the most important question to be answered? But it’s still a natural one to arise. And yes, we could run through a long list of the implications in this scenario for the employees of the organization, other stakeholders, and the external audiences. But I have to say Brian’s arguments are well made. He sets the scene — the executives are relying heavily on AI. From there it goes more into the alarm function. Judgment being reshaped — the judgment exercised by a leader is obviously so flaky that it can be reshaped by the AI assistant. In other words, that individual is willing to let that happen. I wonder whether this is all part of, perhaps, the speed with which people are expecting decisions to be made. Indeed, something I was doing this weekend — we’re on a holiday weekend here, by the way, so I had time to do this — that was nothing to do with work. It was a personal thing I was involved with that required analyzing a document that had a lot of financial information in it. I asked my AI assistant, in this case Claude, as part of my experiment with Claude, to summarize it and pinpoint the key aspects. It did that in about 20 seconds. And that was enough for me to know what questions I would need to ask it next, to develop it the way I want, rather than starting from scratch trying to do that. So there’s the benefit. But I think treating AI like a trusted advisor, to me, makes a lot of sense. And I’m trying to balance that thought with the alarmist approach — you know, this is a bad thing, all these terrible things are going to happen, and it will all come out. So how does that gel with treating AI like a trusted advisor? Although your point, I agree, it hasn’t earned the trust in the context of this conversation. So does it mean leaders are willing to override their own decisions or instincts based on AI input? Well, according to The Register, 62% have said they are, I suppose. If that’s true, I think we’re in trouble already, before this gets any further. So the real challenge — I think you’ll agree with this, Shel — is not the tech at all. It’s the leadership aspect, the human behavioral aspect of this, as is so often the case. When people talk about the relationship between the human and the AI and they just talk about the tech, it’s not — it’s a human issue. Cut through all the alarm bells and pluck out something which to me is extremely important, that really doesn’t get much airtime in Brian’s report at least: isn’t this really about the whole point of judgment? That someone in a leadership position in an organization is in that position partly because he or she is very good at exercising judgment in the work they do or the decisions they make. Are we saying that judgment is so fragile that an AI could just overturn all of that in an instant and lead all this? I guess my point is that I’m noting this. I listened to what you said. I haven’t read all the surveys you mentioned, or the other reports — the Harvard Business Review, for instance — I will. But I find this literally the worst-case scenario, and that’s being pitched as, you know, this is upon us, based on The Register, which, by the way, has a — let’s call it interesting — reputation over the years for some of their reporting. But this is very factual; their own report is actually quite well written. So what do we make from this then? Should we be worried? I don’t think we should, if we see this as simply something to note and look at as a communicator — let’s say the role you’ve got in ensuring that the CEO isn’t going to have his or her judgment completely overwhelmed by an AI. I just find the idea of that frankly ridiculous, in the sense of, well, not implying or even saying that this is the norm. It’s a result of surveys. There’s other research also supporting some of this, I think. But we should put it in perspective: this is, I guess, an inevitable discussion point that’s emerging at this stage in the development of AI and organizations. We’ve reported recently on this podcast how leaders are taking ownership of the AI deployments in their organizations. That doesn’t mean to say every company is doing this, because they aren’t. But we’re seeing that, and then we’re seeing other reporting we’ve commented on — that employees and other stakeholders related to an organization are unhappy with what’s happening with AI rollouts in their organization. So you’ve got all these mixed messages coming left, right and center, and now this. It doesn’t mean we should — oh my goodness — stop doing this, or have a meeting with the CEO and say, “What are you doing?” No, I don’t think so. But we need to note this nevertheless. I don’t believe this is something we should all get terribly alarmed about, to be honest, as long as we apply our own common sense to observing what’s going on and making sure we understand the CEO we’re supporting as communicators — let’s say the leadership teams — that this isn’t happening. Shel: Well, I don’t think this is the most important issue we’re facing with AI. I do think it’s a time to worry. Now, I will say I don’t imagine that the CEOs leading the world’s biggest companies — the Jamie Dimons, the Josh Domaros, the Tim Cooks of the world — are using AI to make important decisions. And you have to wonder, because I don’t think they asked, in the survey they did, what types of decisions these CEOs are making. Are they the game-changing decisions, the most important decisions they have to make, or are they lower-level decisions? We talk about AI taking all that drudge work off the table. Are they allowing the AI to make decisions associated with that kind of work? But I think, as people — and CEOs are people — as they get accustomed to letting AI make decisions, it might get easier and easier to turn bigger and bigger decisions over to AI as time goes by. With any luck, AI is going to get better and better and may earn that trust. But this would cause that decision-making instinct that leaders have, based on their experience and their judgment and the other things that got them to that level, to atrophy. I mean, atrophy is happening elsewhere as a result of AI among some groups of people — the ability to write your own thoughts down, to craft your own email, to conduct your own research. As far as CEOs making good decisions with support from AI, I think support from AI is going to become table stakes. I think CEOs who don’t know how to use it are going to become dinosaurs in fairly short order — not necessarily the ones who have the job now, but I don’t think you’re going to see people getting promoted into that position, or hired into it, if they don’t know how to use AI for decision support and the other things we see AI being used for very effectively at leadership levels. And leaders are using AI, according to most of the research I see. I wonder, though, if they start turning more and more decisions over to AI, what is the board or the owner going to see as the value of the CEO? If most of this work — or much of this work, the majority according to that Confluent study — is being done by AI, does that mean the enormous salaries being paid to the people at the top of the organization are going to decline? Or does it mean that the role changes altogether, or maybe even ceases to exist in favor of some other model? And by the way, I’d love to see the same question posed to people at other levels of the organization, because this probably is not something confined to the C-suite, this turning decisions over to AI. I wonder how much it’s happening in middle management. I wonder how much it’s happening among frontline workers. If it’s at the same level, then it’s a company-wide issue that needs to be addressed, because there are going to be some problems that emerge if we don’t — I mean, along the Volkswagen lines with their emissions scandal. Dieselgate, exactly. Yeah. Neville: That was Dieselgate, as it was dubbed. I mean, it’s a good point you make. I agree. And the point you made earlier, too, is actually a critical question: what kind of decisions are we talking about here? Is it on the scale of, let’s proceed with the merger with this company rather than that one? Or is it something like, should I fit in a stopover in this city on my way to that city to meet with these people and so forth and achieve these things? Is it that? Or is it even something more prosaic? You know, what do I get my wife for her birthday next week? I’ll have my secretary do it — but the AI could tell me. I mean, that’s ridiculous, actually. But it’s significant to know what kinds of decisions we’re talking about, because I’ve not seen it referenced. It’s implying — and people are jumping, obviously, on this — that these are the kind of organization-affecting major decisions that are suddenly at risk because an AI is doing it. I find that ridiculous, to be honest. So we need to know what kind of decisions. Shel: Yeah. I mean, in my industry, there’s a go/no-go decision on pursuing a project. I cannot imagine, in my wildest imagination, in my organization, anybody turning that decision over to an AI. But what if somewhere in the industry they do, and end up pursuing a project that ends up being more trouble than it was worth? Somebody in the organization at that leadership level, who was involved in the previous discussions, would have known for various reasons, but the AI didn’t have the experience and the insight that that individual had. That could be a financial problem for the organization. Neville: So the role of the communicator in all of this — and this is not to say that the communicator who works closely with the leadership teams, including the CEO and others in the C-suite, is involved in every single thing they’re doing. No, that’s not realistic, because they’re not. But the communicator’s role in preserving human judgment is the right question to ask. What is it in this context? Where do communicators fit in helping leaders balance AI insights with human insight and judgment and experience? Where do they fit in doing all of that? So the two angles I notice: internal comms — communicators act as sense-makers, ensuring context, ethics and human impact remain part of decision-making. Externally, they help articulate how AI is used responsibly in the organization, which is increasingly central to trust and reputation. That addresses the point you made about when it leaks and it gets out that AI did something. I think increasingly we’re going to see that point — articulating how AI is used responsibly in an organization — because the impact can be huge if rumor builds, which it would do: “the AI is making all the decisions in this company, and why do we need the CEO and all that?” So that’s a good role for a communicator to take on, and to be seen to be the person who is the “yes, but” person and the key advisor to leadership in these things, which strengthens the communicator’s role, in my view. So there are things we can do to address this. If this is as big a problem as these articles make out, I don’t believe it’s something we should lose any sleep over right now in the context of everything else that’s going on in the organization. But nevertheless, we’ve got respected sources — Harvard Business Review, we’ve got Deloitte talking about it, and others that we pay attention to because they’re credible publications talking about this. Shel: Well, yeah. Neville: Brian seeded an interesting discussion point, it seems to me. Shel: Yeah. And let’s look at a very plausible scenario. Let’s say somebody sues the organization over a decision that the CEO made, or that leadership made, that affected them badly, and they feel they deserve compensation for that. In the U.S., anybody can sue anybody for anything. And we have seen some recent lawsuits. Look at the lawsuit that we’re seeing play out right now between OpenAI and Elon Musk. Neville: Yeah. Shel: And look at the records, the emails that have been surfaced in discovery. Look at the trials that have been held over lawsuits brought by the parents of children who killed themselves because they got encouragement or assistance from ChatGPT, and who sued OpenAI over that. What they got in discovery was access to the kids’ entire ChatGPT history. So you have a shareholder or a customer who sues the company, and in discovery, all of these things come to light — and that’s how it gets out. So I think even decision support has to be balanced with other input that you can demonstrate in a courtroom influenced the decision that was made, so it doesn’t look like the decision was completely outsourced to the AI. I think that’s an entirely plausible scenario in a lawsuit. So yeah, it’s something we need to consider. And as you say, and as I said, there are things communicators can do about this. One is making sure people are aware of the potential for this situation. And then, as I said, influencing the governance model so that it incorporates decision-making — if it doesn’t already have decision-making and decision support in the governance document, it needs to be added. And then making sure the leaders are talking about how they’re using it, so it never comes up that they’re using it to make a decision of importance in the organization — that it’s focused on using it in very effective ways. Neville: Yeah. I mean, I think the picture you painted — lawsuits and stuff like that — are very possible, particularly in America, where, as you said, anyone can sue anyone for anything, usually for amazing sums of money, in the billions. So maybe what needs to happen in organizations that would address this, among other things, is keeping records. So that, for instance, in an organization that has deployed or rolled out AI tools such as chatbots — let’s say maybe their own version of something based on ChatGPT, whatever it might be — it needs to be known that those record anything you interact with on an AI. Whatever level you are in the organization, there’s a record kept along with anything else: emails, internal reports, you name it, they’re monitored and tracked in most organizations. And the fact that you could add to that picture even some of these automated note-takers, like Otter and others, that are commonly used in intrusive ways in Zoom meetings — and you hear stories of private Zoom meetings — Shel: AI transcripts of Zoom meetings in which the decisions were made. Neville: — where the outcomes are disclosed or leak out publicly because someone used one of these tools that summarized things, including the recommendations or suggestions if they were made by anyone. If that gets into a law case by the plaintiffs, that’ll be shown out of context — you can be sure of it. So, right. Shel: Yeah. And that’s why a lot of organizations are saying to their employees, you can’t record these kinds of meetings. Neville: Right. But someone will, and it’ll happen. So you need to head that off the path, as it were, and have your own structure in place and your communication surrounding it. So, for instance, you have to have very clear narratives around decision ownership, for example, that would help you in crisis situations. That’s the internal focus. Externally, you’ve got to communicate the kind of structure you have for human accountability — not “the algorithm said we should do this.” We can laugh about it, as I am at the moment, but imagine the reality of something like that happening. So I think these are all things that are plausible, I do believe, particularly in the U.S., I have to say — but hey, could be anywhere. It isn’t complicated to work out a plan of how you would prepare for things like this. But I’d rather look at it not as preparing for worst cases, although you need to. It’s just a switch — flip it over a bit and look at the benefits of all of this. And again, not solely the communicator: the individual leader has to be willing to go along with this, has to be willing to share some of the thinking he or she is doing and the discussions with the assistant, whether it’s an AI or anyone else, to realize that you can’t do this without full transparency, at least to your advisors, including the communicator. Shel: Yeah, absolutely. And we will be back with a follow-up episode when the inevitable headline surfaces of a company that gets in trouble because it’s revealed that the CEO abdicated a decision to AI. Until then — actually until next week — that’ll be a 30 for For Immediate Release. The post FIR #512: The AI Shift in Executive Decision-Making appeared first on FIR Podcast Network.