The starting point is an Ahrefs study finding that only 37.9% of the pages an AI Overview cites still sit in Google's top ten, down from 76% a year ago. Harjot reads it as a clear signal that answer engines are becoming how people find things. Will reads it as mostly noise, arguing the models are just cleaning up the sloppy way most people search. They agree on one point: ranking first and being recommended by the AI are no longer the same list.

The second half turns to a vendor study of a hundred SaaS brands, which reports that the top-ranked brand can be absent from the AI's answer while smaller companies with real third-party validation get picked. Will and Harjot split on why, but agree on what a marketer should do first: run your key buying questions through the AI, see whether you appear at all, then give one person the job of fixing it. More content is not the lever.

Highlights of this Episode Include:

• Ranking and AI Citation Have Split: Only 37.9% of AI Overview citations still sit in Google's top ten, down from 76%.
• Signal Versus Noise: Harjot calls the shift the future arriving; Will calls it people finally searching better.
• Query Fan-Out Explained: The AI breaks your question into sub-questions and cites pages that never ranked for it.
• The Number-One Brand Can Be Absent: A vendor study reports top-ranked SaaS brands going missing from the AI's buying answer.
• The Dollar Machine Traps Incumbents: Big teams cannot switch off a proven revenue engine to chase something unmeasured.
• Luxury Brands Face a Harder Problem: Answer engines weigh product information over the look and feel a glossy brand sells.
• Your Monday Move: Run your top buying questions through the AI, then assign one person to own AEO.

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New York's law is now in force, and any advertiser reaching its consumers must disclose an AI-generated performer inside the ad. The EU follows in August, while Britain has nothing. Will reads it as a canary for copycat state rules and federal ones to come, with liability landing on whoever publishes the ad. Harjot calls it a cookie banner moment that stamps AI as untrustworthy and binds only the people already behaving.

The second half turns to brands running AI customers who never existed, while platforms label everything by default. The hosts pull apart three things usually treated as one, the disclosure label, the provenance credential, and the lie itself. A fake testimonial is false whether a model or a real actor delivers it, and a label only proves a tool was used. The practical move is to record which tools touched each asset and check the claim is real.

Highlights of this Episode Include:

• The Producer Carries the Fine: New York's law puts liability on whoever pays for and publishes the ad, not the agency or the tool.
• A Canary for What's Coming: Will expects copycat state rules then federal ones, and treats this as a legal problem, not marketing.
• A Cookie Banner Moment: Harjot argues the law brands AI as untrustworthy and binds only the people already trying to behave.
• Regulation Favours the Incumbents: Big brands have compliance teams; a nail salon on Instagram gets caught by a thousand-dollar fine.
• Three Things People Conflate: The hosts separate the disclosure label, the provenance credential, and the actual lie of a fake customer.
• What a Label Actually Proves: It shows a tool was used, never whether the claim behind the ad is true.
• The Monday Move: Get suppliers to state in writing which AI tools touched each asset, and verify the claim is real.

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LinkedIn's three-year study with Bain reports that 94% of B2B buying groups consult an LLM before speaking to sales, and argues AI retrieves whoever is already trusted rather than discovering anyone new. Neither builder finds that surprising. Will notes LinkedIn sells reputation-based advertising and has reason to describe the world this way. Harjot reads the behaviour as comfort, arguing buyers trust AI more than they trust colleagues.

The second half is where they part. DISQO claims its AI Search Lift can measure whether advertising moves your brand inside AI search. Will calls it branded search relabelled and wants the panel size before anyone signs. Harjot rates it, arguing it may reveal how buyers actually decide, and wants the methodology published. The takeaway is to find out what AI already says about you, and baseline before trusting any lift number.

Highlights of this Episode Include:

• What the Buyability Study Claims: LinkedIn says AI surfaces vendors who already carry customer proof, peer recommendation, and expert endorsement.
• Consider Who Funded the Research: Will notes LinkedIn sells reputation-based advertising, so it has reason to say reputation now decides everything.
• Buying Is a Comfort Behaviour: Harjot argues buyers trust AI more than colleagues, using it to feel safe in a decision rather than to learn.
• The Retrieval Layer Decides Who Gets Pulled: Challengers should optimise what a model can reach; incumbents should stay clearly described through rebrands.
• The Hosts Split on Measurement: Will calls DISQO's AI Search Lift branded search relabelled and demands the panel size before anyone signs.
• Answer the Questions Buyers Actually Ask: Will's Monday move is to mirror the Q&A format on your own site, since retrieval reads it even if training never does.
• Never Skip the Baseline: Harjot's rule is to trend results over time and correlate them with your other metrics before trusting any lift.

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In the fourth episode of Assistant to the CMO, Lexie Meskouris speaks with Will Nash and Harjot Singh about whether AI moving into the buying itself is a real shift to build for now, or a loud launch that most customers are not ready to use.

OpenAI put a checkout inside ChatGPT and the ad money arrived fast, but Will and Harjot split on what it means. Will sees a real signal, though he says the change that matters is discovery - how you show up when someone asks ChatGPT, which he calls AEO - not the buy button. Harjot calls the checkout mostly noise: the revenue is real, but almost nobody will hand over a card inside a chat, so it only fits cheap impulse buys.

The second half turns to the walk-back, as OpenAI quietly pulls checkout toward retailer apps and a survey shows 60% put off by AI in brand messaging. Will reads it as normal early-curve wobble, not a crisis, and says the fix is honest disclosure. Harjot keeps it simple: hold on to the site you own, because AI strips your brand down to bare facts. The takeaway is to audit what AI already says about you before you change anything

Highlights of this Episode Include:

• Discovery Is the Real Shift: Will says the change touching every marketer is how AI describes you when asked, not the checkout inside ChatGPT.
• The Buy Button Is Mostly Noise: Harjot says the revenue is real, but almost nobody is confident enough to finish a purchase inside a chat yet.
• Build for the Agent, or the Human: The core split - Will would get your product feed agent-ready now, Harjot would build for the human and wait.
• Concentrate, Don't Go Wide: Both agree AI leans on a few big sources like Reddit and G2, so concentrate spend there, not on micro-influencers.
• The Walk-Back Isn't a Crisis: With about 20% of US adults using AI daily, Will reads OpenAI's checkout retreat as a normal early-curve wobble.
• Disclose the AI Fast: Will says the 60% flinch is about feeling deceived, so tell customers early when a persona is AI rather than hide it.
• The Monday Move Is a Self-Audit: Ask ChatGPT and Claude what they say about you versus rivals, find the source, and keep the site you own.

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In the third episode of Assistant to the CMO, Lexie Meskouris speaks with Will Nash and Harjot Singh about two stories that turn out to be the same argument: AI agents moving into ad buying, and Cannes declaring that AI handles production while humans keep the strategy.

The episode opens on agentic ad buying, with Meta wiring ad accounts into ChatGPT and Claude and Google running its Ask Advisor agent across Ads and Analytics. Harjot reads it as catch-up that quietly lowers the barrier for everyone, even a one-person shop, while the real skill shifts from knowing the dashboard to knowing advertising. Will pushes back: the value sits in the standalone agent layer for sophisticated in-house teams, and for most marketers, using these tools directly just creates work and risk. The second half turns to Cannes and its tidy line between execution and strategy. Will thinks the line is false because the two were never cleanly separable. Harjot thinks it is broadly true but self-serving, a way for agencies to defend margins while production costs collapse. The takeaway is a fork: decide whether agentic ad buying is even relevant to you before you touch it, and if you test it, keep it small and name who owns the result.

Highlights of this Episode Include:

• The Dashboard Moat Just Evaporated: Knowing your way around Ads Manager matters less now, and advertising judgment matters more.
• Who Is This Actually For: Harjot says it opens to everyone, Will says only sophisticated in-house build teams should bother yet.
• The Chat Window Is a Red Herring: Both agree the real shift is the agent layer, not talking to your ad account.
• You Still Cannot Skip Strategy: An agent can run the campaign, but CPM, channels, and targeting still need a human.
• Cannes Drew a Convenient Line: Harjot argues "humans keep strategy" protects agency margins while production costs quietly fall.
• The Line Itself Is Shaky: Will argues execution and strategy were never cleanly separable, so the slogan misleads people.
• Run It Small, Name the Owner: Test one agentic tool as a separate experiment, and assign someone accountable when it breaks.

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In the second episode of Assistant to the CMO, Lexie Meskouris speaks with Will Nash and Harjot Singh about whether AI now choosing what people buy opens a door for challenger brands or locks the biggest brands further ahead.

A Bain and Walpole study found that 82% of high spend luxury shoppers now start with an AI, and both hosts agree the front door has moved. The real shift is trust. Buyers now lean on their own ChatGPT, which already knows their history and preferences, over a brand's own website. They agree the trust has left the brand's site, and they part ways on what that means next.

One read is that AI keeps recommending the same trusted names, so the biggest brands get locked further in. The other is that AI is still easy to influence today, so a smaller brand with clean, clear product data can muscle past a 100 year old name. Either way the takeaway is the same. Make your product information clean and legible in the places the AI already looks.

Highlights of this Episode Include:

• The Front Door Moved: 82% of high spend luxury shoppers now start with an AI, and both hosts call it a real signal.
• Buyers Trust Their AI: People now trust their own ChatGPT, which holds all their context, over your on site finder tool.
• Trust Lands Where You Don't Own It: AI does not value content on your own site, so the place buyers trust is no longer yours.
• Level the Field or Lock It: The core split, where AI either lets a clean challenger break in or keeps the same big names locked in.
• Lazy But Not Blind: The one point both hosts agree on, that AI grabs easy spec data but can still hold imprecise info without dropping you.
• Influencer Spend the AI Can't Read: Models read text, not Instagram comments, so a decade of influencer investment sits stranded.
• Same Homework Either Way: Whichever way it goes, the first move is the same, make your product data clean where the AI already looks.

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The episode starts with what ChatGPT ads actually look like. They are not banners off to the side. They are sponsored cards that appear underneath an answer, inside the same conversation users already trust. Harjot sees a major opportunity: people tell ChatGPT things they would never type into Google, creating a new kind of intent signal for advertisers. Will is more cautious. The signal may be rich, but the controls are still thin, the measurement is limited, and the ad can feel uncomfortably close to a recommendation.

The second half turns to the anti-AI backlash. Aerie, Equinox, McDonald’s, and Anthropic all become examples of brands trying to work out what “human-made” actually means. Harjot argues that the enemy is not AI, but slop. Will argues that “no AI” can work if it is rooted in a real brand history, as Aerie’s is, but becomes dangerous when it turns into a promise the company may not be able to keep.

Highlights of this Episode Include:

• ChatGPT Ads Are Not Banners: Sponsored placements appear inside the trusted experience, underneath the answer, which makes them feel materially different from traditional display ads.
• Intent Plus Trust Is the Bull Case: Harjot argues that ChatGPT captures unusually rich context because users explain what they want in full, not just through keywords.
• The Controls Are Still Thin: Will pushes back on the current product: limited targeting, no retargeting, weak measurement, and no clear way to know whether early spend creates durable advantage.
• Before You Buy the Ad, Check You’re in the Answer: Will suggests turning ChatGPT memory off and asking it to recommend products or services in your category before spending money on sponsored placement.
• The Anti-AI Backlash Is Really an Anti-Slop Backlash: The episode argues that bad AI work is not bad because AI was involved. It is bad because there was no taste or judgment in the process.
• “No AI” Is a Risky Brand Promise: Aerie’s claim has history behind it, but broader “made by humans” positioning can become a trap if the brand later needs AI to stay competitive.
• The Work Is the Point: Whether a brand uses AI or rejects it, the label matters less than whether the final work has taste, clarity, and substance.

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New episodes of Assistant to the CMO land every Thursday.