Wag The Dog: strategic communications insights

As artificial intelligence takes over more of our operational process, rewards will come for those who focus on the one thing that machines are really bad at: articulating a story that humans and algorithms both trust. Storytelling is back, according to Simon Murphy, founder of Indigo Murphy. Globally, white-collar work has become the next cost base driving wild market swings, with Wall Street acting like “a mob with bats” , indiscriminately searching for the next industry to be hit by AI automation. This is a familiar theme being felt across the communications sector right now, especially in holding company land where consolidation is both a cost and capability play. The Omnicom–IPG merger , for example, has focused on an estimated US$750 million in annual cost savings tied to severance and “structural expense savings” that will be reinvested in data and AI. On the surface, it’s about productivity: AI taking on junior production, research and reporting so networks run leaner. Take a look underneath though, and something more interesting is happening. As generative models flood the world with cheap content (aka “AI slop”), brand leaders are rediscovering that what still differentiates isn’t volume, but the human ability to frame a story that clients, regulators, employees and machines recognise as credible. Key to this according to Professor Scott Galloway are three human skills make you “irreplaceable in an AI world” and should sit within the DNA of any good PR consultant: namely curation, curiosity and connectivity. In a recent episode of his Pivot podcast, Galloway even singles out strategic communications as one of the few jobs he’d bet on being not just safe, but even more important in the AI age. This is encouraging for current and aspiring storytellers, and it is a signal that is being validated elsewhere. Business Insider recently noted that the hottest job in tech right now isn’t a coder, it’s a storyteller. Netflix advertised a director of product and technology communications role paying a staggering US$775,000, median Fortune 500 CCO pay rose by US$50,000 in 2025 to between US$400,000 and US$450,000, and Linkedin posts mentioning “storyteller” doubled over 12 months. The double-edged truth here is that as agencies cull their juniors in a brutal quest to maintain profit, the market is paying a premium for storytellers who can set and defend the narrative. Three AI-related forces explain this return to vogue. First, generative AI has created a flood of verbose, generic content (the current state of “thought leadership” on LinkedIn is a moot point in my opinion). Not everyone should presume they can write, which is why former journalists often make the Chief Storyteller transcendence so capably. Second, AI has changed where trust is formed. Muck Rack’s Generative Pulse study found that 94% of sources cited in AI answers are non-paid third-party sites: journalism, industry outlets, government databases and niche publishers. Half a brand’s AI citations typically come from just 20 outlets, and those outlets vary sharply by brand, even within a category. Visibility is now a rapid precision target game, as citation velocity peaks in the first seven days after publication then just as quickly falls away. Third, AI has changed when stories matter. Monthly chatbot visits now sit over 7 billion globally, approaching 10% of traditional search traffic. This means that AI writes the first draft of your crisis narrative and your first sales call, using whatever operational stories, filings or activist content it can find. Being ahead of the story is now more paramount, and challenging, than ever. In this always-on-gorge-everything world, chief storytellers can do three things that AI cannot: they can build a coherent explanation of who the organisation is and ensure it survives contact with sceptics; they can translate operations into “reputation infrastructure” (safety, governance, customer outcomes and proof points) that humans and engines can interrogate and trust; and they can strategically orchestrate story distribution across journalists, Linkedin, Reddit, press wires and owned content so that generative AI accurately treats the organisation as a trusted source, not a blind spot. Ultimately, in an age optimised for competence, connection is the real premium, and those of us who can communicate, build trust and manage complexity across multiple constituencies will be hardest to automate. In other words, professional storytellers aren’t on the fringes of the AI story; they’re one of the few groups the future is actively tilting towards. However, with advertising now taking a foothold within generative AI, traditional earned PR and marketing folk are soon going to be rubbing elbows within the same generative environments. It’s time to make nice with our marketing colleagues, or at the very least learn from and emulate them. We cannot afford to be allergic to funnels, attribution or media economics. In a world of AI slop, storytelling may be the only thing that makes you stand above the crowd. Today’s chief storyteller must understand how stories travel and how the media business around those stories now works, paying heed to five skills in particular. Earned visibility through Generative Engine Optimisation (GEO) Influence brand visibility inside generative AI through earned channels. This demands a precise, high-cadence earned programme aimed at the specific journalists, wires and platforms that AI trusts for your category. Narrative architecture and explanation design AI is optimised for explanation, framing and recommendation, not just discovery. Design “explanation layers”: clear, consistent narratives about what you do, who you serve and why you’re credible that hold up across thousands of prompts. Operational fluency and reputation infrastructure Get close to the business. Winning storytellers understand supply chains, product, compliance and safety deeply enough to turn them into stories about traceability, resilience and outcomes, ensuring those stories are documented and structured so AI has something solid to work with. Cross-disciplinary marketing literacy As generative AI compresses discovery, consideration and purchase into a single interface, communicators need to also be able to speak marketing. Marcoms in its truest AI-led sense has arrived. Know how retail media, performance, loyalty and brand safety behave when the “storefront” is a chatbot and align with marketing so that paid, owned and earned stories line up inside AI environments. Critical thinking and sniffing out the BS AI is prolific, not wise. The tech companies leading the charge on communications investment do so because they value storytellers as “BS detectors” who can spot cliché, bias and over-claim and design more tactile, grounded storytelling. This requires classic why, what, how storytelling that is sharpened with data: structured thinking, skepticism and the willingness to kill a neat story that isn’t actually true. AI won’t take the job of a great communicator any time soon. It will, however, make good storytelling the scarce resource that talent, capital and algorithms are all competing to capture. Good luck to all the current and future storytellers out there. This story first appeared in Mumbrella’s opinion section on 3 March, 2026

Just before Christmas, Arun Sudhaman wrote " Spectres at the Feast ," unpacking Sir Martin Sorrell's BBC Today programme commentary that "there's no such thing as PR anymore." Sudhaman's diagnosis cut deeper than Sorrell's provocation: the real problem isn't whether PR is dead, but whether the industry can reclaim authorship of its own mandate while better-resourced marketing players claim "scaled, digital storytelling" as their territory. If you work in communications, this should have landed with more of a thud than the usual industry chatter. The strategic high ground of earned storytelling, surely the very thing PR was built to own, is being contested while we're still explaining what we do. Rather than fuel the "dead or alive" argument, I've decided to treat this moment as a prompt. After 25+ years watching this industry evolve from "press release and prayer" (there is truth in this) to something far more sophisticated and multifaceted (which you and I both know it is), I keep returning to a simple future looking question: how do we build earned credibility that survives in a world where machines increasingly do the summarising? Seeking inspiration over Christmas, I re-read Jordan B. Peterson's 12 Rules for Life (2018) , which argues for choosing order over chaos by starting with what you can control. Six of his rules struck me as unexpectedly helpful signposts for communications in response to this question. 1) Stand up straight with your shoulders back PR has a habit of underselling itself, then wondering why it gets treated as a cost centre. If we want a seat at the table, we need to show up like we belong there. That means describing our work in terms that matter to the business: risk reduced, regulatory heat lowered, reputation enhanced, customer confidence sustained, purchase decisions accelerated. The final outcome is especially salient. As the AI search era gathers pace, earned credibility is a commercial driver. Recent research from Onclusive found that brands with highly positive earned media sentiment are three times more likely to win in head-to-head commercial comparisons. When your organisation is being described by AI answer engines using other people's words, the quality of those third-party words matters more than ever. Show your stakeholders what your organisation's ChatGPT profile looks like versus your competitor's. That gap becomes your business case. 2) Set your house in perfect order before you criticise the world This rule is painfully practical. Before complaining about Sorrell's barbs, let's fix the basics. Most organisations still have trust gaps hiding in plain sight: dated FAQs, vague positioning, thin "about" pages, leadership profiles that say nothing, verbose thought leadership that says even less. Getting your house in order - namely your own content - isn't just good brand housekeeping. It's the very foundation that feeds the machines. Generative engines reward clarity, consistency, and credible sources. If you want to show up well in AI-mediated discovery, make your backyard legible: A well-structured website explaining what you do, who you serve, and what proof you have FAQs answering real stakeholder questions, not the ones you wish they asked Clear, quotable narratives for leaders, with verifiable supporting facts Useful, authoritative content that earns its place rather than fills space Research from my UK based partner Hard Numbers shows that large language models source information from a blend of editorial media, owned content, and other high-authority online sources. This makes Gen AI a force multiplier for existing content efforts. It's not glamorous, but it's compound interest. 3) Tell the truth, or at least don't lie Trust is significantly undervalued in today's climate, which makes it worth the investment. In an AI-shaped information environment, credibility is currency and contradictions are tax. Applied habits of yesteryear - massaging reality, spinning weak stories, hiding behind euphemisms - don't just look bad anymore. They're expensive own goals. The strongest communications teams aren't the ones who "win the narrative." They're the ones who help organisations behave in ways that can be defended, explained, and repeated without regret to both human and machine stakeholders, all the while building trust. Simple test: would we be comfortable seeing a questionable claim quoted back to us on a chatbot, out of context, in six months? If not, tighten it or drop it. 4) Be precise in your speech Vagueness can be the more comfortable path, but precision is about being understood. It's the difference between "we are committed to innovation" and "here's what we changed, why we changed it, and how we measure whether it worked." In generative search, precision is also how you become citeable. If AI systems increasingly act as the first filter between stakeholders and your brand, then "machine-readable credibility" becomes part of the job. Fewer fluffy adjectives, more concrete proof points, more conversational straight talk that can survive repetition across sources. The goal isn't volume. The goal is reliable information that scales. 5) Make friends with people who want the best for you Earned has always been a team sport. In the old world, this meant fostering relationships with journalists, editors, and producers. That still matters, but the stakeholder circle has widened. Today your credibility is shaped by analysts, academics, creators, industry advocates, government, NGOs, employees, customers, traditional media, and niche communities. The modern earned play is less "spray and pray" and more "build a citation-rich ecosystem." You want credible third parties saying consistent, positive things about you for reasons that stand up to scrutiny. Internally, the same rule applies. If PR wants to lead in the AI search era, it can't sit downstream of decisions. Build allies across product, legal, customer, HR, risk, and the C-suite, not to ask permission, but to shape reality before it hits the headlines or the model. 6) Do not bother children when they are skateboarding If PR is to evolve, we must protect experimentation. Marketing figured this out with the 70:20:10 rule. As Rory Sutherland notes , you need the 10% of honeybees following random routes to find new pollen when the old supply dries up. Communications has been too risk-averse to adopt this discipline. We need to fix that. Most communications teams I know run flat out just to keep up with the cycle of work coming their way, which means change happens only after something breaks. That's a rough way to live. Fortune favours the bold. Ringfence time for structured tests in AI search optimisation, not gimmicks or prompt hacks, but real experiments that teach you what gets remembered and repeated: Which thought leadership formats earn citations, not just clicks Which proof points travel through third-party sources Which questions stakeholders actually ask AI tools about your category Which owned assets improve clarity and reduce confusion Small falls are the price of progress. Better to have them in controlled pilots than in crises. Reclaiming the Mandate Can the PR sector reclaim authorship of its mandate, demonstrating that its counsel and capabilities are indispensable? That's the right question for 2026, but it requires us to stop asking for permission and start demonstrating competence. The "press release and a prayer" version of PR is mercifully long gone. The discipline that's emerged - earning trust, building understanding, architecting reputation in an age of algorithmic mediation - is more valuable and measurable than ever. But as the AI search era gathers pace, the strategic high ground of earned storytelling is not ours by default. We have to take it. This article first appeared on Earned First on 20 January 2026.

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Earned attention has always been the backbone of reputation. Whilst traditional media engagement is a conduit for reaching important human stakeholders, with the unstoppable rise of Generative AI there is a new audience that must be factored into the earned equation. Training and influencing the machines will be an endurance race that is already well underway. As communications leaders consider how to encourage their teams to rise to the challenge, the question that comes up most often is: if we pivot now, how soon will our efforts be rewarded? The honest answer is that it depends. Days, weeks or months, based on a selection of cases shared below. But here is what every communications lead needs to hear upfront: if you are waiting for certainty before you start, you are already falling behind. Successfully showing up in GenAI search requires a significant "shift and lift" of your current communications strategy, and the sooner the better. This means optimising your earned and owned assets (often referred to as Generative Engine Optimisation, or GEO) and conducting regular benchmarking to continually measure and fine-tune your efforts. GEO can be thought of as the evolution of SEO for environments where large language models increasingly mediate discovery. The algorithms and sources driving Generative AI search remain enigmatic and constantly evolving, forming a new track around which we must run. It is still early days, but the race has begun. The fast wins: days to weeks Noah Greenberg, CEO at Stacker, has talked extensively about how PR and content teams can positively impact chatbot results overnight. In one example, he shows how a study commissioned by tech recruitment firm Checkr on the best U.S. job markets was quickly picked up by Tier 1 outlets including Newsweek and CBS,¹ and within about a month, Checkr was being mentioned consistently in relevant AI conversations.

I've been banging the drum about the Great Communications Reset for a while now, and if you've been following along, you'll know my core argument: we're living through a once-in-a-generation opportunity for communications professionals to reclaim strategic territory that matters. But here's what I haven't stressed enough – and what new research has now quantified in stark terms: It's not just about getting earned media coverage anymore. It's about the quality and sentiment of that coverage. Fresh research from Hard Numbers and Onclusive titled "Recommendations in the Age of AI" has put hard numbers to something many of us suspected but couldn't prove: brands with high-quality, positively framed earned media don't just show up more often in large language model outputs – they win decisively when it matters most. And by "win", I mean actual commercial outcomes. The study examined over 100 global brands to understand how earned media influences category recommendations within ChatGPT, Gemini, Perplexity and other LLM platforms. The findings are unambiguous: Brands in the top 10% for media influence get recommended by LLMs around 80% of the time, compared to under 50% for brands in the bottom 10%. That's a 30-point gap in visibility. In commercial terms, that's the difference between being discovered and being invisible. But here's where it gets really interesting – and where most communications teams are still missing the point. Brands in the top 10% for positive media sentiment are nearly twice as likely to receive low concern scores from AI platforms. Think about that for a moment. When someone asks ChatGPT "What are the concerns about [your brand]?", the machine's response is directly influenced by the tone and sentiment of your earned media footprint. And in head-to-head "Which brand is better?" prompts, high-sentiment brands are around three times more likely to win against competitors. Three times. The pattern is unmistakable. It's not enough to be in the story anymore. The actual tone of that story – whether it's positive, neutral, or negative – is now a performance metric inside the machine. Why Sentiment Matters More Than Volume For years, communications teams have been measured on reach, impressions, and coverage volume. The logic was simple: more coverage equals more visibility equals better outcomes. But generative AI platforms don't work that way. LLMs aren't counting your clips. They're synthesising narratives. They're looking for patterns across trusted sources to form coherent, credible responses. And in that synthesis process, the quality and tone of individual pieces of coverage matter far more than the sheer volume. A single deeply positive feature in a trusted publication – one that positions your brand as innovative, trustworthy, and delivering genuine value – can influence AI outputs more effectively than a dozen generic mentions. This is why the Hard Numbers and Onclusive research is so significant. It's not telling us to chase more coverage. It's telling us to chase better coverage. Coverage that: Comes from authoritative, trusted sources that LLMs prioritise Contains clear, structured information that machines can parse Positions your brand with positive sentiment and credible third-party validation Addresses the specific attributes that matter in your category (trust, innovation, value, quality) The Agentic Commerce Reality Check Here's why this matters right now, not in some distant future. With OpenAI and others rapidly advancing agentic capabilities, LLMs are evolving from passive information retrieval tools into active brand recommenders and decision-makers. We're entering an era where AI doesn't just inform purchasing decisions – it makes them. ChatGPT can already browse the web, compare products, and make recommendations. The next iteration will be able to complete transactions autonomously on behalf of users. When someone says "ChatGPT, find me the best project management software for a team of 15 and set up a trial," the machine won't serve up 10 blue links. It will make a decision. And that decision will be heavily influenced by your earned media footprint – specifically, the sentiment and quality of that footprint. What This Means for In-House Teams If you're leading communications for a brand right now, here's what you need to be doing: 1. Audit your current earned media sentiment Don't just count clips. Analyse the tone and positioning of your coverage across key publications. Are you consistently positioned positively? Are the attributes being emphasised the ones that matter for your category? This isn't vanity work. This is understanding what the machines are learning about you. 2. Prioritise quality over quantity in media relations One deeply positive feature in a tier-one publication or respected trade outlet is worth more than a dozen generic mentions. Invest your time in cultivating relationships with journalists who can deliver substantive, authoritative coverage. Focus your pitching on stories that genuinely demonstrate value, innovation, and trustworthiness – the attributes that LLMs prioritise when forming recommendations. 3. Structure your owned content for machine readability Your newsroom, blog, and website content are also training the machines. Make sure they're doing the job properly. Use clear, structured formats (FAQs, how-tos, product comparisons). Implement schema markup. Update content regularly. Ensure your "About Us" and core product pages use consistent language that mirrors how you want to be discovered. 4. Monitor your AI footprint regularly You should be querying ChatGPT, Gemini, and Perplexity regularly with category-relevant prompts to understand: How often you're being recommended What's being said about you Which sources are being cited How you stack up against competitors This isn't optional anymore. This is reputation management in 2025. 5. Measure what matters Move beyond AVE and reach. Start tracking: Share of positive sentiment vs competitors Citation frequency in AI outputs Win rate in head-to-head AI comparisons Sources that most influence your AI reputation These are the metrics that actually correlate with commercial outcomes in the AI-driven discovery era. The Bottom Line Regular, high-quality earned media has become a key driver of whether a brand is surfaced, recommended, and ultimately purchased through generative AI platforms. The brands that understand this – that invest in building authoritative, sentiment-rich earned narratives – will dominate tomorrow's reputation landscape. The ones treating communications as a tick-box exercise, chasing volume over quality, will become increasingly invisible where it matters most. This is the Great Communications Reset in action. The opportunity is significant, but it requires a fundamental shift in how we think about earned media success. It's not about the clip anymore. It's about what that clip teaches the machine. And the machines are learning fast. You can access the full "Recommendations in the Age of AI" research report from Hard Numbers and Onclusive [here - link ].