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ALP 302: Rethink entry-level hiring to succeed in the AI era
Apr 2700:18:36Tap to summarizeThe entry-level talent pipeline is being entirely restructured. If agency owners don’t figure out what role a young professional actually plays in an AI-assisted agency, they won’t just struggle to hire today. They’ll have no one to promote in five years. In this episode, Chip and Gini dig into what’s happening with entry-level hiring right now, and why the answer can’t be to stop hiring junior staff altogether. The conversation covers why the old model of routine work is gone, what needs to replace it, and why agencies that don’t solve this problem soon are setting themselves up for failure. The episode opens with an observation from Gini: every presentation she gives to college classes lately surfaces the same anxiety from students. Nobody’s hiring at the entry level because AI can handle the work those roles used to cover — news releases, media lists, social drafts, basic research. How can they find jobs today, and get the on-the-job training they need to move forward in their careers? Chip frames the problem as a junction of circumstances: the rise of AI, economic uncertainty, and a higher education system that hasn’t evolved with the workforce reality. Colleges discouraging AI use while their graduates are about to enter workplaces built around it is, as he puts it, the same mistake as banning calculators in math class. The students coming in aren’t unprepared because they’re less capable, they’re underprepared because the institutions that trained them weren’t keeping up with the times. Chip and Gini agree that entry-level hires aren’t obsolete, but the role must change. Instead of being the lowest rung of the ladder, new professionals need to come in already functioning like managers — just managing AI tools and processes instead of people. That requires more on-the-job training, better-documented processes and SOPs, and a genuine commitment to learning and development that most agencies still don’t have. There’s more than one upside, though. Better documentation and SOPs don’t just help entry-level hires do their jobs — they make your agency more efficient, reduce owner dependency, and, for those who want to sell someday, significantly improve the value of the business. Their closing argument is not to avoid entry-level hiring because the old version of the role is antiquated. Rethink what the role is, invest in the systems that support it, and get comfortable assigning junior people with responsibilities that would have felt premature five years ago. The alternative is a mid-level talent shortage that will be very hard to fix. [read the transcript] The post ALP 302: Rethink entry-level hiring to succeed in the AI era appeared first on FIR Podcast Network.
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 →Circle of Fellows #127: The 7 Cs of The New Communication Compass, Part I
Apr 2601:00:10Tap to summarizeThe next two “Circle of Fellows” episodes will offer something different from our panels of the last several years. We welcome Dianne Chase, a veteran communicator and former IABC chair, to the discussion. While Dianne is not a Fellow, she did recruit six Fellows to write all but one of the chapters for her new book, The 7Cs of the New Communication Compass. (Dianne wrote the seventh chapter.) The book, which has five stars on Amazon, “offers both a guiding framework and a practical roadmap for mastering strategic communication in complex environments,” according to its description. “If you are a leader, manager, educator, public official, influencer, or anyone striving to make an impact, this book is an essential and thought-provoking read. It distills communication excellence to foster collaborative results and organizational effectiveness.” The book’s Cs include Collaboration, Connection, Compassion, Cohesion, Community, Congruency, and Calibration. For the first of these conversations, Dianne will join Shel Holtz, Ginger Homan, Jane Mitchell, and Brad Whitworth to discuss Connection (Brad’s chapter), Compassion (Dianne’s chapter), Congruency (Jane’s chapter), and Calibration (Ginger’s chapter). Join us for this very different “Circle” at noon EDT on Thursday, April 23. Participants in the live stream can ask questions and share comments, observations, and experiences, and become part of the discussion. If you’re not able to join us, you can listen to the audio podcast later or watch the YouTube replay. About the panel: Dianne Chase helps organizations and leaders harness the power of strategic communication to navigate crises, build trust, and drive positive change. With over two decades of experience in journalism and corporate communications, Dianne has developed a unique approach for training and consulting clients that combines crisis management expertise with the art and science of business storytelling. Dianne is an award-winning media, journalism, and strategic communication professional with profound expertise in communication disciplines, most notably crisis communication, issues and reputation management, media training, and executive communication. She is one of two people in the world accredited in the powerful GENIUS Business Storytelling methodology, created by international communications thought leader, Gabrielle Dolan. She is former chair of the International Association of Business Communicators, and author/editor of The 7 Cs of The New Communication Compass. Ginger Homan, ABC, SCMP, IABC Fellow, counsels senior leaders seeking to bring out the best in their people and brands. Her award-winning communication model for driving transformation has been used to change behaviors, align cultures, and build thriving communities worldwide. Her work with senior communication professionals has enabled them to align their department goals with business goals, achieve measurable results, and expand their influence. Founder of Zia Communication, she is a seasoned speaker, coach, and workshop facilitator. Her clients include Walmart, the Walmart Foundation, the Walton Family Foundation, T.D. Williamson, CITGO Petroleum, Phillips Seminary, and MOSAIC. IABC, PRSA, and SMPS have honored Ginger’s work on the local, regional, and international levels. A past chair of IABC, her volunteer work has been honored with three IABC International Chair’s Awards for leadership, and she is a recipient of the Leadership Tulsa Paragon Award for work in her local community. Jane Mitchell’s career began at the BBC in London on live TV programs. She moved on to producing award-winning films and videos for public- and private-sector organizations and to developing groundbreaking employee engagement programs. Since 2006, when she formed her own consultancy, she has guided organizations (some of which have experienced cultural trauma) in embedding values and ethics by understanding culture and leadership, and their link to high-performing, sustainable organizations. She has worked with Top 100 companies worldwide and is a regular conference speaker. Jane has been a member of IABC since 2008 and has served on local, regional, and International IABC Boards. In 2021, she was Chair of the (virtual) World Conference and became an IABC fellow in 2022. She is based in the UK and now spends the majority of her professional time as a Non-Exec on company boards and Employee-Owned Trusts. Brad Whitworth, ABC, SCMP, IABC Fellow, is a pre-eminent thought leader, lecturer, and author in organizational communication. He has led global internal and executive communication programs at HP, Cisco, Hitachi, PeopleSoft, AAA, and MicroFocus. He holds an MBA from Santa Clara University and undergraduate degrees in journalism and speech from the University of Missouri. Brad lives in California, a wine country, and he grows Pinot Noir on his property. A former broadcaster, Brad has made more than 300 presentations to executives, communicators, and university classes worldwide. Brad is a past board chairman of the International Association of Business Communicators and a Fellow of the association. He is one of the authors of The IABC Handbook of Organizational Communication and the new IABC Guide for Practical Business Communication: A Global Standard Primer. He chaired the Global Communication Certification Counsel in 2021. The post Circle of Fellows #127: The 7 Cs of The New Communication Compass, Part I appeared first on FIR Podcast Network.
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 →ALP 301: Five words every agency owner needs to understand
Apr 1300:21:04Tap to summarizeMost agency owners spend a lot of time thinking about growth, clients, and revenue. Far fewer think carefully about the words that define how they actually operate their businesses. In this episode, Chip and Gini dig into five of those words: leadership, management, accountability, responsibility, and authority. Leadership and management aren’t the same thing. Leadership is about vision and getting people to follow you. Management is about making the work happen. Knowing which one you’re stronger at is the first step toward building a team that covers your gaps. Accountability is the wrong place to start when a team member isn’t delivering. You can’t hold someone accountable for something you never clearly assigned, and you can’t hold them accountable if you didn’t give them the authority to get it done. Gini offers a useful comparison: when a client hires you for your expertise and then second-guesses every decision, it’s demoralizing. That’s exactly how your team feels when you delegate the work but not the authority to do it. The episode closes with a simple reminder. If you want more freedom as an owner, you have to be willing to actually let go. And if your team isn’t capable of handling more responsibility, you should be asking yourself why you hired them. [read the transcript] The post ALP 301: Five words every agency owner needs to understand appeared first on FIR Podcast Network.
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 →ALP 300: 300 episodes in: what’s changed, what hasn’t, and what we got wrong
Apr 600:24:14Tap to summarizeEight years and 300 episodes later, Chip and Gini take stock of what the Agency Leadership Podcast has actually been about and where their thinking has shifted since they sat down for lunch outside Wrigley Field and decided to start a show. Chip shares an AI-generated analysis of the 10 most common themes across 300 episodes. Gini distills them into four she considers non-negotiable: communication fixes most problems, know your numbers, focus on particular wins, and the owner sets the temperature. Chip adds that communication doesn’t just solve problems, it prevents them. Ironic, given that probably everyone listening is in the communications business. On what’s changed, Gini has moved from annual retainer-focused planning to quarterly reviews that constantly show results and surface what’s working. She also notes that her advice for navigating a tough business environment now mirrors what worked during the pandemic: find the project work, start with an assessment, and build trust before building a retainer. The biggest evolution for Chip is his position on AI. While he was skeptical a few years ago about the timeline, now he thinks agencies are under-emphasizing it. He and Gini disagree on AI’s limits. Gini believes critical thinking, emotional intelligence, and crisis work still require human judgment. Chip is less certain those guardrails will hold. What they do agree on: AI is turning everyone into a manager, and that puts a premium on skills that were already in short supply. The episode closes with a lightning round covering worst advice agencies still believe, best scary decisions, and prospect red flags including unreasonable expectations and unwillingness to discuss budget. [read the transcript] The post ALP 300: 300 episodes in: what’s changed, what hasn’t, and what we got wrong appeared first on FIR Podcast Network.
Transcribe →ALP 299: Hire people who understand how to solve problems
Mar 3000:20:40Tap to summarizeMost hiring processes obsess over the wrong things. Do they know our project management software? Are they proficient in this specific tool? Meanwhile, the one capability that actually determines whether someone will make your life easier or harder—their ability to solve problems independently—gets a cursory “are you a good problem solver?” question that everyone answers with “yes.” In this episode, Chip and Gini break down why problem-solving ability should be the primary hiring criterion, especially as AI makes technical skills easier to acquire and offload. The conversation explores why this matters more now than ever: as AI handles tactical execution, the ability to define problems clearly, break them into components, and figure out solutions becomes the differentiator between humans who add value and humans who get replaced. Chip and Gini discuss how problem-solving cuts across every role, even ones you don’t typically think of as problem-solving positions. Designers facing impossible deadlines, account people navigating last-minute client demands, anyone dealing with the reality that things rarely go according to plan. They all need to be able to figure out how to move forward rather than escalating every obstacle upward. The episode tackles the mechanics of actually interviewing for this capability. You can’t just ask “are you a good problem solver?”—you need scenario-based questions that reveal how candidates think through challenges. But not hypothetical scenarios you make up; real situations that have happened in your agency. Ask them to walk through how they’ve handled compressed timelines, missing information, conflicting priorities, or last-minute changes in past roles. Gini shares how her daughter’s school explicitly focuses on humanities and emotional intelligence rather than technical skills, anticipating that AI will reshape what jobs exist. She connects this to Anthropic’s hiring practice of seeking people with humanities degrees who can absorb information, think critically, and demonstrate emotional intelligence rather than just technical proficiency. The episode concludes with an important reminder: if you hire problem solvers but then micromanage how they solve problems, you’ve wasted the hire. You need to let them solve things their way, even if it’s different from how you’d do it, or you’ll end up with everything back on your plate anyway. [read the transcript] The post ALP 299: Hire people who understand how to solve problems appeared first on FIR Podcast Network.
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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