Christopher Dorsey writes about business implications of AI and advertising, including enterprise sales, workplace AI governance, retail media, and how AI changes payment for creative work.
They are most useful for concise analysis of how AI shifts enterprise sales, retail media, and creator pay.
Best for
Research-led thought leadership for retail media, adtech, or B2B media brands.
Not for
Campaigns needing broad reach, audience data, or stated sponsorship terms.
Key takeaways
AI vendors still need human sellers for messy enterprise deals; transactional sales are exposed.
Governance dashboards shift who can kill a deal, moving influence to the console owner.
Metering can make per-use pay practical again for creative work.
Check first: Confirm sponsorship format, rates, media kit, brand inquiry route, and audience breakdown.
Main ideas
AI vendors still need humans for messy enterprise deals · Governance dashboards shift who can kill a deal · Retail media is one way retailers get paid, not the only one
Audience
4,066 LinkedIn followers · 4 posts published 2 June to 28 September 2026 Posts in reviewed sample
Christopher Dorsey writes about how AI and advertising change business decisions.
In four LinkedIn posts, they examine why complex sales still need people, how workplace AI governance can affect adoption, how Costco’s membership model differs from retail media, and how metered AI use could change creator pay.
These examples show a writer who connects business developments to their practical consequences for sellers, brands, workers, and creators.
Dorsey’s distinctive strength is making business-model shifts concrete.
Rather than discussing AI or advertising only as broad trends, they trace how those shifts alter a specific exchange: who can approve an enterprise purchase, what a brand contributes to a retailer, or how creators might be paid for usage.
The posts also make room for exceptions: AI may absorb transactional sales, while complex purchases still call for human sellers; and retail media may matter to many retailers, while Costco’s membership fees offer a different source of income.
Follow them for concise explanations of these practical tensions.
Christopher Dorsey writes about how new technology changes business models, not just technology itself.
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Across their posts, they track where money and control sit: which purchases still need a human seller, who can block an enterprise deal once AI use becomes visible, how a retailer gets paid if not through media, and whether usage metering lets platforms pay creative contributors per use again. Their examples are specific, and they often spell out what each change means for the brand or vendor on the other side of the table.
AI vendors still need humans for messy enterprise deals
Dorsey challenges the assumption that AI companies would be first to automate their own sales teams.
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The issue, they argue, is the shape of the deal, not the technology: when a purchase involves several stakeholders, an unplanned budget and a procurement cycle, a human has to be in the room. Dorsey reads hiring patterns at the AI labs as a signal about which sales work will last: their products are absorbing transactional, self-serve sales.
At OpenAI and Anthropic, go-to-market accounted for the largest share of open roles—roughly one in five—ahead of research and engineering, even though these companies are best positioned to replace sellers with software.
Dorsey sees the arrival of enterprise agent governance as a shift in buyer power.
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For two years, the play was adoption first, procurement later—a strategy that worked because IT could not see the agents.
A console that inventories unmanaged agents turns a quiet productivity win into a flagged risk.
The gatekeeper is now whoever owns that console, not the original budget holder.
Microsoft's Agent 365 became generally available to find unmanaged agents, including Anthropic's Claude Code, across Microsoft, AWS and Google Cloud, at $15 a seat. Dorsey says a pipeline that depends on staying invisible to IT is a countdown, not a strategy.
Retail media is one way retailers get paid, not the only one
Dorsey compares retail media's growth with a model in which the retailer collects margin before a supplier buys any advertising.
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Their point for brands: a joint business plan without a media line still costs money, paid through price, pack size and velocity rather than impressions. Retail media is a choice about where the budget goes, not a universal requirement.
Costco reported a $93.9 billion quarter.
Across fourteen analyst questions, nobody asked about retail media, and management never raised it—even though Costco runs a network called Velocity on the same vendors Walmart Connect uses.
Walmart's ad business grew almost 50 percent, and Kroger's ad arm grew profit 24 percent in a quarter when it cut sales guidance.
Costco, meanwhile, booked $5.9 billion in membership fees.
For suppliers, Dorsey says, Costco's offer is price, pack size and velocity, with an end-cap and product samples standing in for media.
Dorsey presents Costco as an exception to retailers increasingly pulling margin from suppliers through advertising. The contrast makes the case for assessing each retailer's model on its own.
Metering can make per-use pay practical again for creative work
Dorsey connects a billing mechanism to creator economics.
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The advertising industry largely abandoned residual per-use payments because tracking where and how often an ad ran cost more than the payment itself.
Platforms that bill by character already count usage for free, making the same per-use model cheap to operate.
For contributors, an advertiser's high asset volume becomes income rather than unpaid work.
ElevenLabs has paid voice creators $22 million, double what it reported paying out the previous November. When Meta asks for up to 50 assets per ad set, Dorsey argues, volume becomes the creator's paycheck.
See how Christopher Dorsey connects AI adoption to the shape of a business purchase.
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It’s a useful starting point for anyone asking whether AI changes sales roles or mainly changes which deals require human help.
Christopher Dorsey contrasts the large share of open go-to-market roles at OpenAI and Anthropic with predictions that AI will replace salespeople. The post argues that complex purchases involving several stakeholders, unplanned budgets, and procurement still need human sellers, while transactional, self-serve sales are more exposed to automation.
For brands planning a campaign
For a B2B media or AI company, this supports a thought-leadership angle on which sales tasks AI may absorb and where human expertise still matters. The post offers a thesis, not evidence about every sales organization.
This offers a concrete account of how workplace AI governance could change an enterprise sales process.
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It shows why an employee-level productivity win may not be enough to secure organization-wide adoption.
Using Microsoft’s Agent 365 as an example, the post describes a shift from employees adopting AI agents outside IT’s view to a governance dashboard that can identify and manage agents across cloud providers. Dorsey frames the consequence as a change in who can block a deal: the person overseeing the console may matter more than the original budget holder.
For brands planning a campaign
An enterprise AI or B2B technology company could use this as a starting point for content about governance, procurement, and the people who influence adoption. Verify current product capabilities and pricing before repeating the post’s specifics.
This explains retail media from both the retailer’s and the brand’s perspective.
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The Costco example shows that a media budget is only one part of the commercial relationship.
Dorsey juxtaposes Costco’s reported $5.9 billion in membership fees with advertising growth at Walmart and Kroger, then makes the comparison tangible for brand readers: Costco’s value exchange is described through price, pack size, velocity, end-cap placement, and product samples rather than a media line in a joint business plan. The post says Costco’s Velocity retail-media network launched in February but gives no year; confirm the date before using it.
For brands planning a campaign
A retailer, retail-media network, or brand could use this framing to discuss the tradeoff between buying media and earning access through price, packaging, placement, or sampling. Confirm current network details and financial figures before using them in campaign materials.
This shows how Dorsey connects a technical feature—metering—to a change in the economics of creative work.
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It helps newcomers assess whether a platform’s business model could also shape how creators are paid.
The post links a claim about ElevenLabs paying voice creators $22 million to a broader argument about payment systems.
Dorsey says traditional per-use advertising payments were dropped partly because tracking usage across markets cost too much, while AI platforms already count characters for billing.
That makes usage-based creator compensation more practical in this setting and could make high-volume ad production a source of creator income rather than only extra work.
For brands planning a campaign
An AI audio platform, agency, or brand could explore a campaign about measurable usage and creator compensation.
Verify the post’s payout figure and comparison before reusing them.
Ask whether the compensation model applies to the specific AI-generated or voice work in question.
Dorsey contrasts expectations that AI vendors would automate their own sales teams with the fact that OpenAI and Anthropic are hiring heavily for go-to-market roles.
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They argue that enterprise deals involve multiple stakeholders, unplanned budgets, and procurement cycles, keeping a human in the room, while AI products absorb transactional, self-serve sales.
Reads hiring patterns and deal structures to infer which sales work remains human-led.
For brands planning a campaign
Use this angle for thought leadership aimed at B2B sales, revenue operations, and GTM audiences: focus the campaign on which sales motions survive AI adoption rather than repeating generic job-replacement claims.
Enterprise AI governance and the shift in deal ownership
Dorsey describes Microsoft Agent 365 becoming generally available for $15 per seat to find and govern unmanaged AI agents across Microsoft, AWS, and Google Cloud.
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They argue this breaks the enterprise AI sales motion that depended on teams adopting agents before IT could see them: once a CIO opens the governance console, an ungoverned agent becomes a flagged risk, and whoever owns that console may be able to kill the deal.
Treats a product launch as a shift in buyer power and enterprise sales risk.
For brands planning a campaign
Frame campaigns for AI governance, IT visibility, and enterprise software buyers around the new gatekeeper role. Show why pipelines that depend on staying invisible to IT are temporary, and help vendors adapt their positioning for governance and procurement stakeholders.
Retail media economics and retailer business models
Dorsey uses Costco's quarterly results to argue that retail media is not a major earnings story for the company: analysts did not ask about it, and management did not raise it.
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They note that Costco has a retail media network called Velocity, while Walmart's ad business and Kroger's ad arm are growing profitably.
Costco instead collects $5.9 billion in membership fees.
For brands, they say, Costco's joint business plan has no media line; suppliers pay through price, pack size, and velocity, while end-cap placement and samples stand in for media.
Compares quarterly results, analyst question patterns, and retailer revenue sources.
Presents Costco as the exception: it earns membership fees instead of pulling margin from suppliers through retail media.
For brands planning a campaign
Useful for retail media networks, agencies, and consumer brands evaluating where ad budgets actually go. Compare retailer models to help suppliers decide when retail media is a real line item and when a retailer already monetizes through membership or trade terms.
Dorsey notes that ElevenLabs has paid voice creators $22 million, double what it reported paying out the previous November.
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They explain that the ad industry dropped per-use pay largely because tracking usage was expensive, while AI platforms meter every character and therefore count usage for free. When platforms like Meta ask for up to 50 assets per ad set, that volume can become the creator's paycheck rather than an unpaid burden.
Compares historical advertising residual pay with usage metering in AI platforms.
For brands planning a campaign
Relevant to campaigns about creator licensing, AI voice and content partnerships, and performance-based talent deals. Use the argument to assess whether metered AI platforms create a more durable payment model for creative contributors and how asset volume affects talent economics.
The four reviewed LinkedIn posts from Christopher Dorsey's account disclose no sponsorships, affiliate arrangements, partnerships, employment, client work, or owned businesses.
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The companies mentioned are subjects of analysis or examples in posts about AI, enterprise sales, retail media, or creator pay; none of the posts carries a sponsorship or paid-partnership disclosure.
Costco Wholesale
Mention
Costco's $93.9 billion quarter and its Velocity retail media network are the subject of the post.
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Christopher Dorsey argues that Costco collects supplier margin through $5.9 billion in membership fees rather than ads, and tells brand-side readers that a Costco joint business plan has no media line. They cite Walmart's ad growth and Kroger's ad profit as comparisons, not as relationships.
The post analyzes the general availability of Microsoft Agent 365, a $15-per-seat product for discovering and governing unmanaged AI agents across Microsoft, AWS, and Google Cloud.
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Christopher Dorsey argues that the console changes enterprise AI sales cycles.
OpenAI features in an argument about sales hiring.
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Christopher Dorsey notes that go-to-market accounts for about one in five open roles at OpenAI, ahead of research and engineering, and reads that as a signal that complex enterprise deals still need people.
Anthropic appears in the sales-hiring post alongside OpenAI, and in the Microsoft Agent 365 post as an example of an agent product the governance tooling is designed to discover.
ElevenLabs' $22 million in payouts to voice creators anchors a post arguing that AI platforms can meter usage cheaply, making per-use creator pay more practical than it was in advertising.
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Meta's request for up to 50 assets per ad set illustrates the volume side of the argument. Ask for disclosure of any relationship with either company.
Christopher Dorsey's work falls into two clusters.
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For AI and enterprise selling, start with the posts on why OpenAI and Anthropic still hire go-to-market roles and on Microsoft's Agent 365 governance console; both ask who can block a deal once AI use becomes visible.
For how money moves through retail and creative work, read the Costco retail-media analysis and the ElevenLabs creator-payment post; both trace a business model rather than a product feature.
Across both clusters, they track where payment and control sit, and what that means for the brand, vendor or creator on the other side.
Readers can explore related questions in the creators below.
Enterprise AI salesAI governanceRetail media economicsCreator compensationBusiness model analysisLinkedIn postsB2B technology and retail leaders
Don “eCommerce” Brett
Brett also works at the intersection of retail, ecommerce and CPG strategy, using earnings and market data to argue where brand investment should go.
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His posts on digital growth versus store growth and Amazon's grocery expansion make the same kind of retailer-level argument as Dorsey's Costco retail-media post.
Brett focuses on category and channel allocation—where a CPG executive should move budget and how to read retailer data—while Dorsey often looks at the business model behind the number, such as membership fees versus ad revenue.
Hariharan writes about AI, CPG, ecommerce and retail media, focusing on how new technology changes operating models.
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His posts on Amazon's AI-powered ad prompts and enterprise AI risk overlap with Dorsey's interest in governance and AI's effect on commercial performance.
Hariharan writes from an operator-and-risk perspective, often citing quantified enterprise failure rates and framing them through insurance, while Dorsey stays closer to deal mechanics and market structure.
Singh writes about the creator and commerce agency world from the brand side, including how brands should evaluate TikTok Shop agencies.
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That overlaps with Dorsey's focus on how creative work gets paid and who owns the commercial relationship.
Singh's posts are more personal and operator-focused—one is about a layoff and one about parental presence—while Dorsey tends to analyze platform or retailer moves from the outside.
Christopher Dorsey's LinkedIn account is small and sharply topical.
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The only measured audience figure is 4,066 LinkedIn followers, observed 11 October 2026.
Their posts do not report platform demographics, so geography, age, gender, employer, occupation and seniority are unknown.
Four posts from June to September 2026 address the commercial side of AI and advertising: how OpenAI and Anthropic are hiring go-to-market staff rather than automating them; how Microsoft's Agent 365 governance console exposes unmanaged enterprise agents; why Costco's retail media business stays invisible in earnings calls; and how metered AI voice payouts change creator compensation.
That mix points to an audience of B2B media, retail media, adtech and enterprise go-to-market readers.
For a B2B media or retail-media campaign aimed at specialist professionals, this is a good fit for co-created thought leadership, but a poor fit for broad reach or a large measured audience on one platform.
Before committing budget, ask for an audience breakdown; treat the follower count as a scale indicator, not a composition profile.
LinkedIn followers
4,066
LinkedIn profile for Christopher Dorsey · 2026-10-11
Christopher Dorsey's four posts offer no stated partnership program, sponsor disclosure, rate or deliverable, media kit, or contact route for brand inquiries.
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They present industry analysis and commentary, each ending with a pointer to a longer piece elsewhere ("link in the comments")—a distribution pattern, not a stated sponsorship offer. Ask Dorsey or a representative to confirm collaboration terms.
Fits a campaign focused on specialist analysis of how money and control move through B2B media, retail media, and enterprise AI sales.
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A retail-media network, adtech vendor, or B2B media company that wants supplier-side brand marketers to understand where ad budgets actually sit would get a credible voice.
The posts show a consistent method: pick a company event, then work out who pays whom.
Dorsey reads hiring data at OpenAI and Anthropic to argue that complex purchases still need human sellers while transactional, self-serve sales are the exposed part.
They read Microsoft's Agent 365 release as a shift in who can kill a deal, moving influence from the budget holder to whoever owns the governance console.
The Costco post does the same work for retail media, contrasting $5.9 billion in membership fees with advertising growth at Walmart and Kroger and pointing out that a Costco joint business plan has no media line, so suppliers pay in price, pack size, and velocity.
For a research-led or thought-leadership engagement, the fit is that transferable skill: turning a quarterly report or product launch into a decision framework a brand team can argue about internally.
The account is small, with 4,066 LinkedIn followers recorded on 11 October 2026, and the sample is four posts, making this a fit for co-created analysis with a defined professional audience, not for reach.
Before committing, ask directly about sponsorship format, rates, media kit, and brand inquiry route; none are published.
When to choose a specialist
Poor fit for a campaign whose success depends on measured reach, audience composition, or fixed commercial deliverables.
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The only audience figure in the posts is 4,066 LinkedIn followers; no demographic or engagement data is published, so a campaign planner cannot state who sees the work, how often, or in which markets.
A consumer product launch, a broad awareness push, or a paid creator partnership that needs disclosed sponsorship terms and a subscriber base to price against has little to plan with here.
The posts carry no sponsor disclosure, stated rate, deliverable, or inquiry address; each ends with a pointer to a longer piece elsewhere, which is a distribution habit rather than an offer.
A second mismatch is format.
The posts are short, argumentative reads of company news, one idea each.
A campaign that needs long-form instructional content, a tested guide, or a resource a reader completes and reuses would not be served by these posts: they stop at the thesis and hand the detail off to a linked piece that is not shown here.
A campaign demanding demonstrable firsthand access, such as a behind-the-scenes account of a retail media negotiation, would also outrun what these posts show.
Treat the follower count as a scale indicator only.
Before committing, ask directly about sponsorship terms, deliverables, and audience data.
A worked campaign example
Campaign need: a retail-media network wants supplier-side brand marketers to understand why some retailers sell media and others extract the same margin through membership, price, and pack size. The deliverable is a four-part research-led explainer series with a companion decision worksheet for brand teams preparing a joint business plan.
Angle: build the series on the comparison they make in the Costco post.
Episode one lays out the two business models side by side: retail media networks that book advertising revenue, using Walmart's ad growth and Kroger's ad-driven profit as reference points, versus a retailer that collects $5.9 billion in membership fees and asks suppliers for price, pack size, and velocity instead.
Episode two answers the analyst-room question, using the observation that fourteen analysts asked about a $93.9 billion quarter and none raised retail media, to introduce the idea of which commercial levers a retailer actually reports and rewards.
Episode three turns that into a supplier worksheet: for each retailer, list the levers you are being asked to move, test whether a media line exists to buy, and, if it does not, work out what an end-cap position, a sample programme, or a volume commitment costs against that advertising line.
Episode four applies the worksheet to a brand-team scenario and shows the decision it produces.
Why this angle: it plays to the method the posts demonstrate—reading reported numbers and earnings-call behaviour to infer who pays whom.
It also gives the network a reason to be in the room, because the comparison makes its own advertising line the explicit alternative rather than an unstated pitch.
The retail-media contrast is the strongest available: the Costco post supplies the membership-fee figure, the absence of retail media questions from analysts and management, the Velocity network reference, and the brand-side framing of price, pack size, and velocity.
The Walmart and Kroger comparisons supply the counterweight, and the OpenAI and Anthropic hiring post supplies a secondary thread on which commercial work stays human-led, useful if the series wants an episode on selling to procurement rather than to a marketing budget holder.
The posts provide the argument, but not current network details or financial figures.
Velocity's launch is given a month but no year, and the earnings and ad-growth numbers would need checking against primary filings before they appear in client-facing material.
The payout comparison from the ElevenLabs post is a separate thread and should not be folded into a retail-media series without verifying the figure.
No rate, deliverable list, or inquiry route is published, so ask directly about scope, rights, and payment terms.
Better when a campaign focuses on eCommerce growth inside large US retailers and needs a retailer-by-retailer commercial playbook rather than a single media-economics argument.
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The posts draw on datasets traced to company filings and earnings releases: 52 public US retailers and roughly 3,300 data points show median comparable sales of +2.9% against median digital growth of +12.5%, with gaps broken out by retailer (Walmart +2.6% comp versus +24% digital; Kroger +1.0% versus +19%; Costco +6.8% versus +21%).
NielsenIQ figures show Amazon's fresh business, with a perishables shopper spending $5,121 a year against $3,771 for the average Amazon shopper.
Each post closes with a numbered “What I Would Do” list for a CPG executive and names a route into the business (Pattern, The CPG View podcast, the Retail eCommerce Club, the Retail Media View newsletter).
For a campaign seeking supplier-side decisions grounded in a stated dataset and a clear commercial path, this is a closer fit than a single-thesis read of one company's quarter.
The posts center on a services business named in them, so the content also leads into that execution offer, its newsletter and its community.
Media or adtech buyers must separate the argument from the pitch.
The frame is commerce strategy, not the media or AI selling dynamics of campaigns on those topics: retail media appears as a growth channel to invest behind, not as the subject.
The numbers come from third parties — company filings and NielsenIQ — so check them against the primary sources before client-facing use.
Better when a campaign wants enterprise AI risk and governance alongside retail media, or values a founder-operator framing.
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The two posts cover the same terrain from a different seat.
One examines AI failure modes with named examples — hallucinated rulings, an AI ordering system shut down after adding items nobody ordered, an algorithmic screening tool at the centre of a class-action claim — and argues that most companies carry no coverage for AI-specific liability.
The other reads Amazon's $19.8 billion quarterly advertising revenue and $79 billion annualized figure, then uses Amazon's own disclosed 48% conversion lift and 21% larger basket for shoppers who engage AI-powered Sponsored Prompts to argue that product-data quality now determines ad performance.
For a campaign that wants one voice to address both the retail-media buying shift and the AI-governance problem, this pairing is directly on point.
The AI-risk post focuses on risk transfer and insurance, a different buyer and budget from a media or retail-media brief.
Folding it into such an engagement needs a reason.
The retail-media post relies on Amazon's own disclosed performance numbers, which are vendor-reported rather than independently measured; the claim that content quality drives conversion is the poster's interpretation of those numbers.
With two large subjects covered in two posts, there is less depth on any single commercial model than in a focused retailer comparison.
Better when a campaign focuses on creator commerce and TikTok Shop agency selection from the brand side.
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The relevant post advises a brand evaluating TikTok Shop agencies to check who is staffed on the account and whether the lead has ever owned a P&L.
It contrasts the brand-side experience of living with a wrong decision against an agency-side career spent on one account.
The business is named in the post (Sohva), and the argument offers a firsthand operational read of a buyer task — how to judge an agency — that Christopher's posts do not attempt.
For a campaign whose success depends on a brand team choosing and managing a creator-commerce partner well, this practiced judgment is the closer match.
One of the two posts is a parenting account about being present at home; the other is a personal story of being dismissed from an agency role.
The buyer analysis is anecdotal rather than dataset-based, and neither post addresses ad or AI sales dynamics.
The claim about brand-side operators rests on one person's experience, with no supporting figures.
For a broad campaign on shifting ad and AI sales, Singh is a narrower choice; the value is concentrated in the agency-evaluation question.
Christopher Dorsey's LinkedIn posts cover go-to-market hiring at OpenAI and Anthropic, Microsoft's Agent 365 governance release, Costco's retail-media and membership economics, and ElevenLabs' creator payouts.
The posts do not show publication dates, and the longer pieces they link to are not included here.
The posts show what Dorsey writes about and how, but not audience composition, reach, or commercial terms.
Christopher Dorsey's LinkedIn profile shows 4,066 followers as of 11 October 2026.
No media kit, sponsorship disclosure, rate, or brand inquiry route is published in the posts here.
Similar-creator comparisons appear in the discovery section.
