Podcast
For Immediate Release
Hosted by Neville Hobson and Shel Holtz · EN
Neville Hobson and Shel Holtz analyze the month’s news in digital and social media for communications professionals.
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FIR #516: Your New Shadow Website
2d ago00:22:13Tap to summarizeThe Economist has gone public with an experiment: it has created a shadow website featuring an AI-friendly version of its front-of-paywall content. The idea is to improve the odds of this content surfacing in AI answers and responses to AI queries. It’s based on a new standard, llms.txt, which has been described as the robot.txt of AI. What does this mean for communicators? Neville and Shel break it down in this short midweek episode. Links from this episode: The Economist tests AI-ready web pages The Economist prepares for a two‑track internet: one for humans and one for AI agents The Economist is testing content read by AI agents How The Economist is using AI to extend its global reach The next version of the web will be built for machines, not humans 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 For Immediate Release. This is episode number 516. I’m Shel Holtz. Neville Hobson: And I’m Neville Hobson. Something quiet is happening to the web, and The Economist is one of the first major publishers to talk openly about how it’s responding. A piece published by Digiday last week describes how The Economist is building what its VP of generative AI, Josh Munker, calls two versions of the web. One version is the one we’re all familiar with: richly designed pages, feature photography, navigation, everything optimized for a human reader browsing with intent. The other version is quite different: stripped back, structured around questions and answers, designed not for you, but for an AI agent acting on your behalf. Now, if that framing sounds familiar, it should. In episode 515 last week, we spent some time on what Google announced at its developer conference in May: that searching the web will increasingly be done by AI agents rather than by humans, and that people will focus on acting on the information those agents surface rather than clicking links themselves. I made the point then that the question for communicators was shifting from, “How do we get found?” to, “How do we become part of the information environment that AI systems draw from?” What The Economist is doing is a direct practical answer to exactly that question. And here’s what makes this particularly interesting. The Economist itself published a piece last December describing this shift in precise terms: a move from a pull internet, where people initiate actions, to a push model, where agents act unprompted, setting up meetings, flagging research, handling tasks, often without a human ever typing a query. They wrote about it then as an emerging phenomenon. Now, six months later, their own team is operationally responding to it. They’re not just observers of this trend; they’re participants in it. The logic behind their approach is straightforward. A growing share of people, particularly in B2B contexts, no longer start their discovery process with a search engine or a home page. They start with ChatGPT or Gemini or Claude. They ask a question, get a synthesized answer, and may never visit the original source at all. For a publisher like The Economist, that creates an obvious problem. If your content isn’t structured in a way that an AI agent can parse and surface clearly, you effectively become invisible. Not because your content is poor, but because the intermediary can’t read it properly. So The Economist is experimenting. Right now, the focus is on content that already sits outside the paywall: marketing copy, B2B sales material, the kinds of pages where you want a potential subscriber or corporate client to find you. They’re building parallel versions: the polished human-facing page alongside a clean, agent-readable equivalent. The aim is to show up accurately and usefully in AI-generated answers. Now, why does this matter to communicators beyond the publishing world? Because what The Economist is describing isn’t a publishing problem. It’s a communication problem. And it connects to something that one researcher quoted in The Economist’s December piece put plainly: Marketers and communicators may need to pitch not to people, but to agent attention. The audience increasingly will be algorithms, and the humans will act on what these algorithms surface. Think about your own organization’s public-facing content: press releases, executive bios, policy statements, corporate FAQs, product and service descriptions. All of that content is increasingly being read and summarized by AI agents before it ever reaches a human. If that content isn’t structured to be understood accurately by an agent, you lose control of how your organization is represented in AI-generated answers. And unlike a Google snippet, you may not even know it’s happening. Alessandro DeSantis, a media consultant quoted in the Digiday piece, puts it bluntly. He calls agent optimization a defensive baseline, not a competitive advantage, but the minimum requirement to remain visible at all. There’s a deeper question sitting underneath all of this, which we’ll get into: Who do you trust in the AI-intermediated world? What does it mean for the communicator’s job when the first reader of your content isn’t a person at all? Shel, you and I discussed the Google side of this in FIR 515. Here’s a publisher responding in real time. What’s your take? Shel Holtz: I have lots of takes on this. This is, I think, a big issue. The first thing I want to point out is that, as I read the commentary of people who are talking about this, there’s an expectation that in the not-too-distant future, the AI version is all that we’re going to need to publish because we’re going to be publishing for AI as people rely on AI to get their information. I find this a troubling idea. I think people are ignoring the fact that right now, 25 to 60 percent, depending on the nature of the site, of visits to a website are direct. They are not coming from a search engine. It’s somebody who already knows the URL. As I mentioned in a post I published to LinkedIn last week, nobody going to Amazon starts at Google and says “online retail site” and waits for the URL to come up. They just type Amazon.com. There are a lot of people who know the URLs. There are URLs published in magazine articles, in advertising, in TV commercials, for example. And then there is the dark web: I send you a link by email or in our Slack channel, and you click it. There’s no search involved at all, so there is no opportunity to see that AI overview. So I think we have to keep in mind that there are still a lot of people who are coming to our websites, not through Google or some other search mechanism, or starting with Claude or ChatGPT or Gemini or what have you. They’re coming directly to your website, either because they know the URL or it has been shared with them by somebody else. So I think we do need to keep that in mind. The other reason I think we need to maintain our own websites is because we own them, and we don’t own that intermediary. You publish that Markdown version of a web page and you provide the proper router to it. Was it called LLM text, I think? They’re calling this the robots.txt of the AI era. And it’s going to share with the person who’s making the query what it shares. It may not be exactly what is on your page. So now you’re down to using a third party. Neville Hobson: Something like that. Shel Holtz: So, yeah, it’s good to have at least as a statement of record what your original content was. I have some other thoughts about this, but I’ll let you react to that first. Neville Hobson: Yeah, no, I get it totally. Yet the trend seems to be quite clear. This is the way it’s moving. And I would say that, from what I’ve been reading, not just this, but The Economist is actually a probably good signal for what other media properties may or may not be doing or might want to do, depending ...
Transcribe →FIR #515: Agents Everywhere
1w ago01:47:40Tap to summarizeEmployees at the Pentagon have spun up over 100,000 AI agents. In the private sector, we’re seeing reports of 10,000 or more agents being deployed by employees at a variety of companies. The problem is that most organizations lack governance to address agents, and the problems this explosion of agents operating on employees’ behalf can cause are innumerable. In the long-form FIR episode for May 2026, Neville and Shel delve into the rise of agents, the harms they could cause, what companies should do to ensure these agents deliver benefits rather than problems, and how communicators can take a leading role in addressing the issue. Also in this episode: AI copyright lawsuits are coming for communicators Google’s search overhaul could signal a post-citation era Placing your thought newsmakers, thought leaders, and subject matter experts on podcasts is becoming a standard media relations practice “I worked all weekend” is no longer an argument for the fees you charge Short-form video clippers are creating go-to content from long-form videos — including yours Dan York outlines the big enhancements in WordPress 7.0 Links from this episode Slopaganda, the New Rules of Narrative Warfare AI Copyright Lawsuits Pose Growing Risk for Communicators Practical Considerations for Managing IP Risk in AI-Generated Content Best Practices for Mitigating Copyright Risks in AI-Generated Content AI in Litigation Series: An Update on AI Copyright Cases in 2026 Powered by A.I., Google Changes Its Search Box for the First Time in 25 Years Google Search as You Know It Is Over Why Podcast Placements Are the New Press Coverage Including Podcasts in Your PR Strategy Podcast Guesting vs. Traditional PR: What Works in 2026 U.S. Newsroom Employment Has Fallen 26% Since 2008 U.S. Podcast Consumption Reaches Record High: The Infinite Dial 2025 You Can’t Beat AI. Steve Rubel on AI, Media Analytics, and the Future of PR AI and the End of Billable Hours The Clipping Economy: How Short-Form Video “Clippers” Are Overrunning the Internet How Short-Form Clips Took Over the Internet The Clipping Economy The Case for and Against Clipping Inside the “Clipping Farms” Driving Fintech’s Marketing Boom Companies Have a New AI Problem: Too Many Agents Businesses Will Have Over 150,000 AI Agents by 2028, Says Gartner AI Agents Introduce a New Class of IT Management Challenges Why Most Enterprise AI Agents Will Fail — And What Leaders Are Missing How Smart Governance Can Contain Agentic Sprawl Six Capabilities Enterprises Need to Scale Agentic AI in 2026 Pentagon Workers Vibe-Code 100,000 AI “Agents” to Use on Unclassified Networks Links from Dan Yorik’s Tech Report Turn Your Blog Posts Into Podcast Episodes Google Search as you know it is over Google Changes Its Search Box for the First Time in 25 Years WordPress 7.0 Field Guide AVFTCN 040 – Returning From A Hiatus, and Plans for 2026 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 Neville Hobson: Hi everyone and welcome to the For Immediate Release podcast long-form episode 515 for May 2026. I’m Neville Hobson. Shel Holtz: And I’m Shel Holtz, and we have six really interesting reports to share with you today. And not all of them are about AI. I’m not saying most of them aren’t, but a couple are on other topics of interest to communicators. Also have a really excellent report from Dan York looking at the latest upgrade to WordPress, a massive upgrade, one of the most significant upgrades WordPress has seen in some time, and Dan’s report is fascinating as he talks about this. But we are going to start by filling you in on a new podcast on the FIR Podcast Network. We haven’t had a new show on the network in a while. You know, we started this as just FIR and we needed a place to house multiple FIR shows. Those who have been listening a long time may remember FIR book reviews and FIR speakers and speeches. And we had a number of these. And then we had some people say, hey, can my podcast live on your network? And we said, as long as it has something to do with communications, sure. So all of them have pretty much faded except a couple that Chip Griffin continues to crank out, but now we have a new one. And the reason we have a new one is because I’m doing it as a new podcast by me and my longtime friend and colleague, Steve Crescenzo. And it is called On the Same Page. It is an internal communications focused podcast. We’re recording it twice a month, about 20, 25 minutes per episode. And each episode focuses on an element of the strategic internal communications framework that I developed. It was several years ago. It was actually before I took a job in the private sector again. I’ll have been at the company I work for now nine years in October. So yeah, I developed this a long time ago. Then I wrote 28 blog posts about it. Somebody said, turn it into a book. So I did. And I have found a publisher for that book. So the podcast and the book are companion pieces and the first episode of On the Same Page is out now. You can find it on the FIR ...
Transcribe →FIR #514: Was Twitter A One-And-Done Phenomenon?
2w ago00:27:59Tap to summarizeThere’s a concept circulating in Platformer, the Reuters Institute, and Nieman Lab: the text-based social networks that defined the last 15 years of public communication may be in irreversible decline. Apptopia reports that Bluesky’s daily users are down 96% from January 2024; Threads has lost users in seven of the past eight months (down 61% from its October 2024 peak); and X has been “culturally altered.” At its peak, was Twitter less a replicable product category than a unique moment in media history? The mass audience has moved to short-form video, algorithmic feeds reward attention over the social graph, and platforms increasingly refuse to be referral engines. Text still thrives in newsletters, Reddit, Discord, WhatsApp, LinkedIn, and AI chat interfaces — what’s collapsing isn’t text, but giant algorithmic public feeds. Neville and Shel look at what this means for communicators: the promise of scale is giving way to relevance, trust, and consistency — a shift that requires a different approach to brand presence on social. Get details in this not-so-short midweek FIR episode. Links from this episode: Are the Twitter clones in trouble? Pew: Americans’ Social Media Use 2025 Pew: Social Media and News Fact Sheet Reuters: Mapping news creators and influencers in social and video networks 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 For Immediate Release episode 514. I’m Neville Hobson. Shel: And I’m Shel Holtz. Communicators devote a fair amount of time to social media management. It’s no different where I work. We’re a smaller team in the construction industry, so we don’t have any dedicated social media resources. But whether it’s a company like mine, where it’s part of the job that somebody does, or a global brand like Wendy’s or Starbucks with a full-blown team, everyone’s trying to make an impact on social network users. The strategy behind those efforts may need an overhaul, though, to address the decline of text-based social networks. Platformer’s Casey Newton wrote about this recently, focusing on Threads, Bluesky, and X — but I think it’s fair to throw Facebook into the mix. Depending on whose numbers you believe, Threads has lost momentum, Bluesky never became the Twitter replacement that political journalists or media folks had hoped it would be, and X is, well, shall we say, culturally altered. Meta and Bluesky dispute some of this third-party data, so I don’t want to overstate the precision of the numbers, but we shouldn’t shrug off the larger point. This isn’t about whether Threads beats X or whether Bluesky can recover, but rather about whether that old Twitter model can be rebuilt at all. And increasingly, the answer looks like probably not. Twitter at its peak was a real-time public layer for news, commentary, expert reaction, and professional visibility. Journalists, politicians, academics, CEOs, and PR people were all there reacting to each other in public. That gave communicators something we had never really had before: a live dashboard of what influential people were saying, what stories were breaking, and how publics were interpreting events in real time. The problem is that this depended on a specific set of conditions — a text-first interface, a public follow graph, a tolerance for public argument, and a shared assumption that this was where you went to see what was going on. Even with a small subscriber base compared to Facebook and a lot of other networks, Twitter was where news broke, and it was frequently cited in the mainstream media’s reporting. Well, those conditions have changed. The mass audience has moved heavily toward video. TikTok, Instagram Reels, and YouTube Shorts are now the primary discovery platforms for younger users in particular. News and commentary arrive as video, personality, remix, and clip. In fact, I was talking about this recently with someone I work with who said she doesn’t watch Saturday Night Live — she watches 10 or 15 of the clips that Saturday Night Live shares on YouTube so she can catch the funniest bits. At the same time, the logic of the feed has changed. The old social feed was built around who you followed. The new algorithmic feed is built around what holds attention. A post on early Twitter spread because of the social graph. A video on TikTok spreads because the system thinks it’ll keep people watching. Now that changes the incentives. It rewards performance, emotion, personality, and visual fluency. It’s also why the link-in-the-post model is fading. Social platforms don’t want to be referral engines. They want the content consumed inside the platform. You can’t conflate social engagement and site traffic anymore. For brands, this requires a pretty significant rethink. Today, social is less about sending people somewhere else and more about creating native moments of value right there, inside the feed. The implication for communicators is that we can’t just ask, “What should we post?” We have to ask, “What role does each of these platforms play in our communication ecosystem?” Some platforms are for discovery, some for reputation, some are mostly listening posts — environmental scanning, sentiment tracking, intelligence gathering. Some platforms may not be worth the effort at all anymore. We also need more human voices. The logo account is not adequate anymore. Trust attaches to people — experts, leaders, practitioners, analysts. That doesn’t mean every executive needs to be dancing on TikTok. In fact, please, no. But organizations do have to get better at helping credible people communicate in platform-native ways. The decline of the old public square forces us to build more durable relationships. What matters? Newsletters, podcasts, owned communities. LinkedIn still matters for professional audiences. So I’d resist the lazy conclusion that text is dying. Text is everywhere — in newsletters (which, by the way, is where I latched onto this story, in Casey Newton’s Platformer), in captions, in scripts, in search results. What’s dying is something more specific: the idea that a text-first social network can serve as the default global town square. Twitter may have been less a replicable product category than a unique moment in media history. For communicators, the job is no longer to master the town square. The job is to understand the map after that square has gone to seed. Neville, is this what you’re saying? Neville: It’s a lot. There’s a lot going on here to kind of zero in on a handful of potential responses, I suppose. But one thing does seem to be quite clear from all that you’ve outlined, which I believe is the case: Twitter probably was historically unique. And I think the issue, or an issue, is that everyone doesn’t think like that. They think it’s repeatable, it’s replicable. And it’s not. I think you could also see AI maybe accelerating the decline. Content abundance — so much of it. Authenticity is getting really difficult to judge. And everywhere is noisy. And that’s not what many people want. So I guess, to crystallize it in a sense — you know, we’ve got all these elements you mentioned. The paradox of Bluesky: it hasn’t grown. Threads has got scale, but it doesn’t really have a big identity. It’s kind of part of Meta. What does it all mean for communicators? We’ll come back to that, I’m sure, in a bit. But I wonder — the thought that keeps recurring in my mind from everything I’ve read about this is that the decline may not be about text at all. That’s not to say it’s because they’ve all migrated to YouTube and video platforms. I don’t believe that’s the case either. I think, as you pointed out, and that’s obvious to all of us, the text itself isn’t disappearing. People talk about the decline of text-based social networks. But the audience hasn’t vanished. They’re just dispersed. They’re elsewhere. They’re not in a central place. There is no public square — no global publ...
Transcribe →FIR #513: Why Communications Must Build the Narrative Code for the Agentic Age
3w ago00:34:10Tap to summarizeNeville 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 subage...
Transcribe →FIR #512: The AI Shift in Executive Decision-Making
May 400:31:28Tap to summarizeWhile 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, thi...
Transcribe →FIR #511: Doing AI Governance Right and Still Getting It Wrong
Apr 2701:33:25Tap to summarizeThe policies are clear and well communicated. The guardrails are firmly established. Every last employee has been trained. And someone in your organization still releases a public document riddled with AI-generated errors. What went wrong has nothing to do with technology and everything to do with internal culture and accountability. In this long-form April episode, Neville and Shel examine a company that seemingly took all the right steps yet still had to apologize publicly for a court filing riddled with hallucinated citations. Also in this episode: Gartner predicts that, by 2028, 75% of employees will rely on an internal chatbot to get the news that matters to them. How will internal communicators need to rethink their role to ensure everyone knows and understands what they should in order to achieve strategic alignment? One of the promises AI executives have made is a leveling of the playing field, giving lower-level employees the opportunity to excel and rise through the ranks. According to one new study, exactly the opposite has been happening. PR hacks have been accelerating the pace at which they churn out press releases and pitches. That has raised the bar for what it takes to earn a journalist’s trust (and journalists do still rely on press releases, according to a survey of reporters). Apple’s announcement of its CEO transition offers communicators a clinic on how to announce a new top executive. “Slopaganda” from Iran has proven remarkably effective, which means it is undoubtedly coming for your company or clients soon. In his Tech Report, Dan York outlines big changes coming with WordPress’s next update. Links from this episode: Elite law firm Sullivan & Cromwell admits to AI ‘hallucinations’ Sullivan & Cromwell law firm apologizes for AI ‘hallucinations’ in court filing Letter re: In re Prince Global Holdings Limited, et al., No. 26-10769 Sullivan & Cromwell Just Put Every Firm on Notice. And S&C Advises OpenAI on Safe AI Use. An AI Screw-Up By… Sullivan & Cromwell? LinkedIn search results for Sullivan & Cromwell AI AI, Trust, and the Reinvention of Corporate Communications: Inside Gartner’s 2026 Playbook Does your intranet still matter in an AI-first workplace? Chatbots in Internal Communications: Game-Changing Wins How AI Chatbots Are Redefining Internal Communications? The future of internal communication: How AI is changing the workplace High earners race ahead on AI as workplace divide widens Sarah O’Connor: One early view about AI was that it would share… How AI is forcing journalists and PR to work smarter, not louder What journalists want from AI-assisted PR pitches Journalists Trust Human-Written Pitches Over AI Journalists Reject AI-Generated Press Releases As Untrustworthy What communicators can learn from Apple’s CEO transition announcement Tim Cook to become Apple Executive Chairman; John Ternus to become Apple CEO Iran’s Meme War Against Trump Ushers In a Future of ‘Slopaganda’ Iran’s ‘slopaganda’ team uses AI Legos to flood social media Slopaganda wars: how and why the US and Iran are flooding the zone with viral AI-generated noise Slopaganda Comes of Age Alberta separatist leader unconcerned about influence of YouTube ‘slopaganda’ videos Links from Dan York’s Tech Report WordPress 7.0 Source of Truth – Gutenberg Times WordPress 7.0: Real-Time Collaboration Arrives in Core WordPress 7.0 Release Party Updated Schedule 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 511 of For Immediate Release. This is our long-form episode for April 2026. I’m Shel Holtz in Concord, California. Neville: And I’m Neville Hobson, Somerset in England. We have six great stories to discuss and share with you this month and to delight and entertain you, we hope. Topics range from the consequences of not following company guidance on AI use, chat bots, employee use, and the workplace divide, using AI to work smarter, what we learned from Apple’s CEO transition announcement, and the future of slopaganda. Lovely word, that one, show. Plus, Dan York’s tech report. But first, let’s begin with a recap of the episodes we’ve published over the past month and some listening comments. In the long form episode 506 for March, published on the 23rd of March, our lead story was on Anthropic’s view that AI will destroy the billable hour, a topic we’ve talked about before on FIR. We also explored digital monitoring of employee work, Gartner’s prediction that PR budgets will double next year, the escalating misinformation crisis, and Cloudflare’s prediction that bot traffic will exceed human traffic by 2027. That’s next year, by the way. On LinkedIn, you’ll find no shortage of posts stridently deriding the notion that anyone should ever use AI to write them. In FIR 507 on the 30th of March, we rejected roundly that idea and looked at the actual trends in using AI for writing. And that prompted some comments from listeners, right? Shel: Yes, it did. Starting with Susan Gosselin, who’s actually with a client of mine back in my consulting days. She writes, there are many types of writing that I think AI is great for interpersonal communications, summaries, et cetera. But for marketing writing, that’s another thing. There are issues of copyright to consider and what you’re feeding into the channel....
Transcribe →FIR #510: Should Companies Embrace Shadow AI?
Apr 2100:25:54Tap to summarizeEmployees have long found ways to use software tools to get the job done, even when those tools are not approved. It’s called Shadow IT, but ever since generative Artificial Intelligence hit the scene in 2022, employees have adopted a new version: Shadow AI. The company approves Microsoft Co-Pilot, but employees opt to use their smartphones or personal laptops, along with their personal accounts with ChatGPT, Gemini, Claude, Midjourney, or whatever best suits their needs. For most companies, this is a problem that needs to be addressed through repeated policy announcements and vigorous crackdowns. One company, though, took a different approach. In this short, midweek FIR episode, Neville and Shel outline what the company did and how communicators might advocate for a version of this approach to aiding in AI adoption and speeding up productivity gains. Links from this episode: The Hidden Demand for AI Inside Your Company Shadow AI Threat Grows Inside Enterprises as BlackFog Research Finds 60% of Employees Would Take Risks to Meet Deadlines FIR #419: Is Shadow AI an Evil Lurking in the Heart of Your Company? The Rise of Shadow AI is a Double-Edged Sword for Corporate Innovation The next monthly, long-form episode of FIR will drop on Monday, April 27. 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 510 of For Immediate Release. I’m Shel Holtz. Neville Hobson: And I’m Neville Hobson. There’s a quiet tension playing out inside many organizations right now. On one side you have leadership teams, IT, legal, and compliance, all trying to put structure, governance, and control around how artificial intelligence is used at work. On the other side you have employees who’ve already moved on. They’re not waiting for official tools. They’re not sitting through pilot programs. They’re not asking permission. They’re opening ChatGPT on their phones. They’re using Claude in a browser tab. They’re experimenting quietly, often invisibly, finding ways to make their work faster, easier, and sometimes better. And in many organizations, this shadow AI behavior is still being treated as a problem — something to restrict, monitor, or shut down. It’s a topic Shel and I discussed on this very podcast in episode 419 nearly two years ago, and it hasn’t gone away. Neville Hobson: In fact, recent data suggests it’s accelerating. A study last November by Blackfog and Sapio Research found that nearly half of employees surveyed in the UK and US are using unsanctioned AI tools. Even more striking, 60% said they would take security risks with those tools if it meant meeting a deadline. So this isn’t fringe behavior — it’s become normal. An article in the Harvard Business Review this month argues that instead of treating unauthorized AI use as a compliance issue, organizations should see it as a signal — a sign that people are already finding value in these tools, even if the organization hasn’t caught up. We’ll explore that idea in just a moment. Neville Hobson: The article calls this the hidden demand for AI inside your company. And when you look at it through that lens, the picture changes quite dramatically. Because instead of asking, “How do we stop this?” you start asking, “What are we missing?” The piece goes further than theory. It looks at what one organization actually did when it recognized this dynamic: BBVA, a Spanish multinational financial services company with more than 125,000 employees. Rather than clamping down on shadow AI use, they moved quickly to provide a secure enterprise environment. But more importantly, they didn’t try to control everything from the center. They took a different approach. They identified and empowered what they call “champions” and “wizards” — the people already experimenting, already curious, already building things. They created a network, a community of practice, a way for ideas, use cases, and practical solutions to spread peer to peer across the organization. Neville Hobson: And the results, at least as reported, are striking: thousands of employees actively using AI tools, thousands of internally created applications, and measurable time savings of hours per person every week. But perhaps the most interesting part isn’t the numbers — it’s the philosophy behind it. The idea that successful AI adoption doesn’t start with a perfectly designed top-down strategy. It starts by recognizing that innovation is already happening, just not where leadership expects it. So the question becomes: do you try to control that energy, or do you find a way to harness it? And that opens up a much broader conversation, one that goes well beyond technology. It touches on leadership, trust, and culture — on how change actually happens inside organizations. And, importantly for communicators, on how you surface, legitimize, and guide behavior that may already be happening under the radar. Neville Hobson: Because if employees are already using these tools — and most evidence suggests they are — then silence or restriction alone isn’t really a strategy; it’s a gap. So in this conversation, we want to explore that gap. What shadow AI really tells us about organizations today, whether the BBVA approach is something others can realistically replicate, and where the risks still sit, because they have not disappeared. And we should be clear: BBVA may be an outlier. It’s a highly data-mature organization with strong leadership alignment. Many organizations don’t have that foundation. So the question isn’t just whether this works — it’s whether it can work anywhere else. And what that means for the future of work, and for the role communicators play in shaping that future. Shel? Shel Holtz: Well, a few thoughts, starting with the fact that BBVA has the financial resources to provide a secure environment for those tools that employees are using. There are many organizations whose IT budgets are razor thin and don’t have those resources, so they would need to figure something else out. But I think there’s a caution here worth raising. The numbers from Blackfog are real, even if the framing from the Harvard Business Review is optimistic: 34% of employees using free versions of tools when paid, approved versions exist; 58% of unsanctioned users on free tiers with no enterprise protections. The reframing from threat to signal doesn’t eliminate the exfiltration risk — it reframes how we need to respond to it. Shel Holtz: Communicators should be careful not to let the BBVA-style narrative become an excuse to ignore governance. The right frame is: harness the demand, don’t suppress it, and build the governance at the same time. Employees using unsanctioned tools and putting secure data and company information into them — that’s a governance risk, and I don’t think we can ignore it. I mean, I think what BBVA did is great, and I think they baked it into some governance while looking at a new approach they could afford to take. But for many organizations, governance is still a requirement. Neville Hobson: Well, I agree. It’s important and it’s not to ignore by any means. I think, Shel, you fleshed out a little bit the survey that I mentioned, which is actually useful to have that level of detail. But the big question for me is: if this is the picture in many organizations, according to that survey — compared to data previously — this is getting worse, or rather, it’s happening more frequently. People are just going ahead and using what works for them as opposed to what’s the official thing. What is that a symptom of? Maybe a lack of trust? It’s probably a mix of things. And to me, the communicator’s role here seems to be to try and help people on the one hand understand what the tools can do for them, and on the other hand to help the organization understand that we need to address this issue. People aren’t using the approved ones. They’re doing stuff on their own, and that isn’t good. Neville Hobson: You mentioned security risks. The Harvard article goes into some detail about that, as indeed do the people ...
Transcribe →FIR #509: Does Corporate Content Need Copyright Protection?
Apr 1400:20:49Tap to summarizeWhen bad actors use AI tools to clone a musician’s voice and upload synthetic versions of their songs, they can then file copyright claims against the original artist’s content — and win, at least initially. That’s because the systems platforms used to validate copyright claims are automated and configured to treat whoever files first as the rightful holder. The result: musicians like Murphy Campbell, a folk artist from North Carolina, lose both revenue and control of their own creative identity. The same mechanism works just as well against any organization that publishes audio or video content online. In this midweek episode, Shel Holtz and Neville Hobson break down how the scam works, why it matters to communicators, and what you should be doing right now — before an incident forces your hand. Links from this episode: AI Cloned Her Voice, Then Claimed Her Songs ‘This Is Not Me’: Inside the AI Scams Driving Musicians Crazy A Folk Musician Became a Target for AI Fakes and a Copyright Troll A traditional musician became a victim of AI imitations and a copyright aggressor ‘AI slop’: Emily Portman and musicians on the mystery of fraudsters releasing songs in their name The next monthly, long-form episode of FIR will drop on Monday, April 27. 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 509. I’m Neville Hobson. Shel Holtz: And I’m Shel Holtz. And today we’re going to talk about something else that communicators need to worry about. I think we need to develop a worry list for communicators. This one starts with a tale about a folk singer from the mountains of Western North Carolina. She’s named Murphy Campbell. She plays banjo and dulcimer and records old Appalachian ballads, some of them written by her own distant relatives. And she posts videos of herself performing in the woods. She has about 7,800 monthly listeners on Spotify. And she is, as Shelly Palmer put it in a recent column, exactly the kind of artist the copyright system was designed to protect. In January, some of her fans started messaging her about songs on her Spotify profile that she had never uploaded. Someone would have taken her YouTube performances, run them through AI voice cloning tools, and posted synthetic versions of her songs under her name on streaming platforms. These fake tracks, to put not too fine a point on it, were really bad. Her dulcimer sounded like — and these were her words — a warbled metallic mess. Her voice had been deepened and auto-tuned into what she called a bro country singer. But here’s where it gets interesting for those of us in communications, because that’s not the end of the story. It didn’t stop at impersonation. Whoever uploaded the fakes through a legitimate music distributor called Vydia (V-Y-D-I-A) then filed copyright claims against Campbell’s original YouTube videos — the very videos the AI had been trained on. Because YouTube doesn’t use humans to review initial copyright claims, Campbell stopped earning revenue on her own content. That revenue started going to the person who had filed the copyright claims. She described herself as being in a weird limbo where “I’m telling robots to take down music that robots made.” Shelly Palmer called this a reverse copyright scam, and he confirmed, speaking to other content creators off the record, that this is more common than he might have believed. Now, I know what you’re thinking — music streaming platforms, artists, what does this have to do with me? And the answer is everything. Because the mechanism that elbowed Murphy Campbell out of earning royalties for her own music will work just as well against any organization that publishes content on platforms with automated enforcement systems. That is virtually every organization that has a YouTube channel, a podcast feed, or any kind of public video or audio presence. So here’s the structural problem as Palmer frames it. The copyright system we have was built on a foundational assumption that the first entity to register a claim is the rightful owner. That assumption held when human creativity was the bottleneck. It breaks completely when AI can generate a synthetic version of any content in seconds using any voice. Think about what your organization puts out there publicly — executive speeches, earnings calls, thought leadership videos, branded audio, training content, podcasts, content marketing pieces. Every one of these is a potential training data set for someone who wants to clone your voice, your leaders’ voices, and then upload a synthetic version through a low-cost distributor. We’re talking about something that costs $25 to $90 a year. Then they file a claim against your legitimate content before a human ever reviews it. Neville Hobson: (pause) Shel Holtz: That means the system is going to see them as the first one to file that claim and assume they are the legitimate copyright holder. Now, Rolling Stone confirmed that this isn’t an isolated case. Paul Bender, Veronica Swift, Grace Mitchell — these are just a few of the artists who have faced the same attack. One musician even ran an experiment he called Operation Clown Dump, uploading fake content under his colleagues’ names across platforms. His success rate was 100%. So what do communicators need to do? First, audit your public content footprint. Do it now, before an incident forces you to. Know what you’ve published, where it lives, and what revenue or visibility is attached to it. Second — and here’s something that’s new for a lot of communicators — register your copyrights. Formal registration is the prerequisite for meaningful legal recourse in the United States. Third, build a rapid response protocol for platform disputes. The organizations that survived these attacks quickest were the ones who knew who to call and knew what to say. And fourth, have this conversation with your legal team today, not after something goes wrong. Murphy Campbell eventually got Vydia to withdraw its claims, but only after her story went viral. Most organizations won’t have that option. Your story won’t go viral. The bad actor doesn’t need to win permanently — they just need the automated system to act before you do. And that is the lesson, and it’s one we’d better learn from musicians before we have to learn it the hard way. Neville Hobson: Extraordinary, isn’t it, Shel? I guess you could call it a new phenomenon, only in the sense of the speed with which this can be done. I must admit, I’m astonished that the system is such that the first person to file the copyright claim is assigned ownership. Maybe that’s similar here in the UK — every jurisdiction is different, of course — but that’s rather unsettling. It obviously goes back to a time when people weren’t exploiting the syste...
Transcribe →FIR #508: Inside AI’s Human Raw Material Supply Chain
Apr 800:20:39Tap to summarizeWhen workers lose their jobs, many turn to gig work to earn income while waiting for new opportunities. Increasingly, companies that hire gig workers are shifting from delivering food or sharing rides to creating content to train AI systems. This raises various communication and ethical issues. Neville and Shel explain what’s happening and discuss the implications in this short midweek episode. Links from this episode: The jobs AI can’t do – and the young adults doing them Thousands of people are selling their identities to train AI – but at what cost? The gig workers who are training humanoid robots at home Gig economy becomes new AI training ground The next monthly, long-form episode of FIR will drop on Monday, April 27. 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 508 of For Immediate Release. I’m Shel Holtz. Neville Hobson And I’m Neville Hobson. Over the past few weeks, I’ve come across a set of stories that all point to something quite striking — not just how AI is evolving, but how it’s being built. Increasingly, the raw material behind AI isn’t just data scraped from the web. It’s us: our voices, our movements, our everyday lives, and increasingly, our identities. There’s a new layer of the gig economy emerging. We’ll explore this in just a minute. People are being paid, typically in small amounts, to record themselves walking down the street, having conversations, folding laundry, even just going about their day. That data is then used to train AI systems because those systems need examples of how people actually speak, move, and interact in the real world. In one case, delivery drivers in the US are being redirected to film tasks for robotics training. Platforms are turning existing gig workers like delivery drivers into distributed data collectors for AI. In another example, people are selling access to their phone conversations through apps that pay contributors to upload voice and text data. And in yet another, workers are strapping phones to their heads to record household chores so humanoid robots can learn how to move. The work is global, fragmented, and often invisible, with workers spanning Nigeria, India, South Africa, the US, and far beyond. Humans are no longer just users of AI — they are raw material suppliers. In China, there are even state-run centers where workers wear virtual reality headsets and exoskeletons to teach robots how to carry out everyday physical tasks. What we’re seeing is the rise of what you might call data labor, where identity itself becomes part of the work. There’s a clear driver behind it. AI companies are running out of high-quality training data. The open web isn’t enough anymore, and synthetic data has its limits. So the industry is turning to something else: real human lived experience. Because if you want a robot to understand how to load a dishwasher, navigate a room, or interact with objects, you need to see humans doing it at scale. But there’s an interesting contrast here. One of the stories highlights a 23-year-old in the US, a guy called Cale Mouser, who earns well into six figures repairing diesel engines. It’s something he’s developed great skill in doing. His work depends on judgment, experience, and problem solving in the real world — things that don’t easily translate into data. So while some people are being paid small amounts to generate data for AI systems, others like Cale Mouser are building highly valuable careers precisely because their skills can’t be reduced to it. And that contrast feels important. Because on one level, this new kind of work does create opportunity. For some people, especially in lower-income regions in the Global South, this is real income — paid in dollars, flexible and accessible. But there’s another side to it. Because what people are actually selling isn’t just time, it’s identity: their voice, their behavior, their presence in the world. And often once that data is handed over, it’s gone — permanently licensed, reused, repurposed, potentially in ways the individual never sees or understands. So you have this asymmetry: individuals earning small immediate payments while companies build long-term, highly valuable AI systems. Perhaps it’s a new version of the Mechanical Turk for the AI era. And that raises a deeper question. What does it mean when the inputs to AI are no longer abstract data, but pieces of human identity? When the training set is not just content, but behavior, voice, and presence? And when those pieces can be reused, replicated, and scaled, often without the individual’s ongoing knowledge or control? Many platforms grant royalty-free perpetual licenses, where workers get paid once and lose control forever. There’s potential for deepfakes, identity theft, and misuse without consent. And perhaps more uncomfortably, what does it mean when people are contributing to systems that could automate their future jobs? For communicators, this feels important because this isn’t just a technology story. It’s a story about trust, consent, transparency, and how organizations explain what they’re doing with AI. If AI ethics lives anywhere, it’s here — in how these systems are built and how that’s communicated. So the question to explore — one of the questions to explore, perhaps — is this one: Are we comfortable with an economy where identity itself is becoming labor? And if not, what responsibility do organizations and communicators have in shaping it? Shel Holtz It’s a big story with a lot to consider. On one level, it seems like the high-tech version of the sweatshops where high-end fashions were made — Nike shoes, for example — with people paying premium prices to get those products while the people making them are earning a pittance in factories with long hours and terrible working conditions. And then you add onto it the identity issue. So it’s something that I think — something at least I hope — we’re going to be talking about for a while. In terms of the AI element, what this suggests is that the gig economy didn’t go anywhere when AI came along; it just became the training ground for AI. And it’s interesting that the workers who are being squeezed out of knowledge jobs are selling their voices and their movements to build the systems that squeezed them out. Because where do a lot of these people who are being laid off because of AI go? Well, they go drive for Uber, they go drive for DoorDash. And you do that long enough and you get really accustomed to the idea that they send you a task, you go do that task, and you get paid for it. So if that task shifts from picking up a meal at a restaurant and delivering it to somebody’s house to going to your own house and washing your dishes because that’s what they want to capture on video — it’s the same thing. You’re getting a task on the app. You’re doing the task and you’re getting paid for it. So I think for a lot of people, this is going to be a fairly easy shift, and they’re not going to think a lot about what’s happening to the information and the content that’s being created with their movements and their voices, which is now being shared and used to make a lot of money for the people who are paying a pittance to these folks. So I see three issues here that connect directly to organizational communication. The first is consent and transparency — and I’m talking about inside organizations — because companies are already deploying AI tools trained on data that their own workers have supplied, and sometimes they’ve supplied this data unknowingly. The ethical and reputational questions that employees are going to ask are questions like: Was my voice used to train a bot that you activated in order to replace my friend who sat next to me and I had lunch with? And regulators are going to end up asking these questions too. So communicators really need to be out front with clear internal messaging about what data employees generate and how the company is using it. Let’s talk about that before I hit the other things th...
Transcribe →FIR #507: Should Nobody Really Ever Write with AI?
Mar 3000:25:37Tap to summarizeTake a stroll through LinkedIn. You’ll find no shortage of posts stridently deriding the notion that anyone should ever use AI to write for them. While that case isn’t hard to make for professional writers, there are countless professionals in other fields who struggle with writing, never trained to be writers, yet now have to write everything from emails to reports as part of their jobs. Should they really sweat for hours over wording, time they could be devoting to the core areas of subject expertise, when AI can produce content that is cogent, clear, and direct? In this short mid-week episode, Neville and Shel look at the trends in using AI for writing, despite the plethora of opinions from the pundits. Links from this episode: Meet the Tech Reporters Using AI to Help Write and Edit Their Stories Meet the Journalist Using AI to Write Stories How Journalists Feel About AI Muck Rack’s 2026 State of Journalism Report Finds 82% of Journalists Use AI AI Doesn’t Reduce Work—It Intensifies It Is Writing with AI at Work Undermining Your Credibility? How We’re Using AI Review of ‘Using Artificial Intelligence in Academic Writing’ Best Practices for the Effective Use of AI in Business Writing AI Tools for Business Writing 5 Ways to Instantly Level Up Your Communication Using AI Tools Charlene Li and Katia Walsh demonstrate the right way to build a book with AI help – Josh Bernoff The Truth About Writing a Book on AI The next monthly, long-form episode of FIR will drop on Monday, April 27. 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 everyone and welcome to For Immediate Release episode 507. I’m Neville Hobson. Shel: And I’m Shel Holtz. And if you spend any time at all on LinkedIn, you’ll see the degree to which anti-AI sentiment is ramping up. A lot of it’s aimed at using AI for writing and how absolutely wrong that is. Yet just last week, on the same day, Wired Magazine and The Wall Street Journal both published articles on reporters using AI to help write and edit their stories. So today, let’s talk about using AI to write. Specifically, is it okay for employees to use AI to help them write for work? And my answer is not only is it okay for many employees, it might be one of the most genuinely useful things AI can do. Here’s the framing I would push back on. When we talk about AI writing assistants, we tend to picture a journalist or a marketer or a communications professional, someone whose craft is writing, it’s what they’re paid for, handing their keyboard over to a robot. And for those of us who are professional writers, that raises legitimate professional and ethical questions. But that’s not the population we’re talking about when we’re communicating AI adoption in most organizations. Think about who actually has to write at work. Engineers document processes. Product managers write status updates. Safety officers draft incident reports. Shel: Finance analysts compose budget justifications. Scientists write up findings for non-technical stakeholders. These are not people who chose their careers because they love writing. Writing is a tax they pay to do the work they actually care about. And many of them pay that tax really, really badly. The idea that a structural engineer should produce elegant prose unaided is the same logic as saying a communications director should coordinate the concrete mix for a construction project. We don’t expect that. So why do we expect every knowledge worker to be a competent writer? Muckrack’s 2026 State of Journalism report found that 82% of journalists, professional writers, people whose job this is, are now using at least one AI tool. That’s up from 77% the year before. If the people whose professional identity is tied to their writing are using AI tools, it shouldn’t surprise us that everyone else is too, or that they should. Now the research does tell us something important about how to use these tools. A University of Florida study of 1,100 professionals found that AI tools can make workplace writing more professional. But regular heavy use can undermine trust between managers and employees, particularly for relationship-oriented messages like praise, motivation, or personal feedback. The study found that employees are more skeptical when they perceive a supervisor is leaning heavily on AI for those kinds of communications. Now that’s a meaningful finding and it’s exactly the kind of nuance internal communicators need to help their organizations understand. It’s not an argument against AI writing assistance. It’s an argument for knowing when it’s appropriate. Purdue Business School Professor Casey Roberson, who literally wrote one of the first business writing textbooks to address AI, puts it this way: AI is a great tool for brainstorming when you’re stuck, for outlining and structuring documents, for revising drafts to improve clarity and tone, but it should not be used for confidential information, and using it to write first drafts can stifle creativity and critical thinking. The Wharton communication program makes a similar distinction. Their guidance frames AI tools as powerful and skilled hands for the right task, valuable for brainstorming, editing, improving conciseness, and anticipating challenging questions, but a liability when used as a substitute for your own thinking, your own knowledge of your audience, and your own credibility. So what’s the practical guidance for internal communicators trying to help their colleagues use AI responsibly in their writing? First, make the distinction between communication types explicit. Routine informational writing — process documentation, project updates, meeting recaps, technical reports — that’s where AI assistance is most defensible and most valuable. That’s exactly where the trust risk is lowest and the productivity gain is highest. Conversely, messages that carry relationship weight, like a manager recognizing someone’s contribution or a leader addressing a team through a difficult moment, that deserves a human voice. Help your employees understand that difference. Second, reframe the conversation around who’s actually writing. A systematic review published in the International Journal of Business Communication found that AI can significantly help with idea generation, structure, literature synthesis, editing, and refinement. Essentially all the phases of writing that non-writers find most daunting. AI isn’t replacing a writer’s voice. In many cases, it’s giving non-writers a voice they otherwise wouldn’t even have. Third, be honest about the nuance inside the journalism conversation. The Columbia Journalism Review published a fascinating piece where journalists across major newsrooms shared their practices. Nicholas Thompson, the CEO of The Atlantic, described using AI the way he’d use a fast, well-read research assistant who’s also a terrible writer — helpful for checking consistency, flagging chronological issues, examining logical claims, but not for the writing itself. Amelia Daly, a senior reporter at VentureBeat, put it this way: AI helps her productivity,...
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