The Day the Bidding Died: Life After Programmatic

There is a TV show called; “Life After People” which describes what would happen if people were suddenly not on this planet. It looks at what would decay and what would be regenerated. It describes the steps of destruction and rebirth.

The “Programmatic Era” has defined digital advertising for over fifteen years. It is a world governed by milliseconds, Real-Time Bidding (RTB), and an increasingly complex labyrinth of middlemen—DSPs, SSPs, DMPs, and exchanges. But what if every advertiser on earth ceased programmatic buying simultaneously, what would we experience as marketers in the real world?

Would we see a shift in marketing strategy? (Yes)

Would we witness the total systemic shutdown of internet’s advertising plumbing? (No)

What would crumble and what would be reborn? (Jury is out)

This thought experiment explores a digital “extinction event.” Much like the asteroid that cleared the way for mammals, the collapse of programmatic media could harbor a healthier, more balanced ecosystem—one built on trust, context, and performance rather than high-frequency tracking.

In creating this thought experiment, I leaned heavily on AI to detail the great unraveling. Obviously, this is not a “likely scenario” and a bit ridiculous but at the same time, this thought experiment helped me see clearly there is life after programmatic. I can imagine how we can move past the assumption that programmatic as it is today is immovable – as dominant in the world as dinosaurs were in their day. AI helped me conceptualize a digital marketing system where programmatic is an important channel for many advertisers but unsuitable for the needs of many, many other marketers who need to drive leads and revenue. For these marketers, programmatic media is where acquisition campaigns go to die. We must reckon with the reality that programmatic is a powerful ecosystem but it is not well-suited for every marketer.

With that, our thought experiment journey begins.

PHASE I: THE DAY THE BIDDING DIED

To understand the unspooling and reconstruction, lets look at each stakeholder in the system: DSPs, data companies, analytic companies, publishers, and ad agencies – from the first impact moment and on. Each segment in the ecosystem will see dramatic changes but ultimately a rebalancing of the adtech system that includes other options and opportunities that embrace the  basic tenants of trustworthy marketing like viewability, contextuality, accountability and frequency.

Within first 5 minutes.

If the global programmatic “off-switch” were flipped at 9:00 AM, in the first five minutes we see a cascading failure across key tech stacks; Publisher, SSP, and DSP.

1. The Ad Server (Publisher Side): This is the first to “panic.” The Publisher’s ad server (like Google Ad Manager) sends a request to the SSP. When the SSP returns nothing, the ad server enters a “timeout” loop, trying to find a “backfill” that no longer exists.
2. The SSP (Supply-Side Platform): Within minutes, SSPs see their “Fill Rate” drop to 0%. Since most SSPs operate on a “take rate” (percentage of cleared bids), their revenue drops to zero instantly.
3. The DSP (Demand-Side Platform): Paradoxically, DSPs might crash due to “Negative Logic.” Their algorithms are designed to optimize based on feedback. When billions of “bid requests” go unanswered, the data-processing engines may hit “divide by zero” errors or overflow errors as they try to calculate why 100% of their bids are failing.

The First Hour: The Technical “Brownout”

In the first 60 minutes, the impact is felt primarily by machines and “on-call” engineers.

• Latency Spikes: Because the ad server is waiting for a “bid” that never comes, website load times skyrocket. Users see “Loading…” spinners where banners should be. The page logic waits for the ad-call to time out before rendering the rest of the content.
• The “House Ad” Takeover: Most sophisticated publishers have “House Ads” (e.g., “Subscribe to our Newsletter”) as the lowest priority in their waterfall. Suddenly, the internet is covered exclusively in self-promotional publisher ads.
• Automated Panic: Every major agency has “Spend Alerts” set up. Within 15 minutes, thousands of Slack and PagerDuty notifications go off. “Spend for Client X has dropped 99% below threshold.”
• The Fraud Engines: Verification partners (DoubleVerify, IAS) see a total drop in telemetry. To their systems, it looks like a global “bot attack” or a “null-route” of the entire internet.

Hour 4: The Financial Realization

The focus shifts from the server room to the C-suite.

• The Spend Halt: Brand Managers realize that millions of dollars in committed daily spend are sitting idle. The “pacing” bars on their dashboards are flat.
• The “Open Web” Blackout: High-traffic news sites, which rely heavily on the “Open Exchange,” begin to see the financial implications. If they generate $100k a day from programmatic, they have just lost $4,000 in the last hour.
• Search and Social “Safe Havens”: Because Google Search and Meta (Facebook/Instagram) use “Closed Loops” (they are their own DSP and SSP), they remain unaffected. Money begins to panic-shift toward “The Walled Gardens.”

Hour 12: The Operational Pivot

The industry begins to realize this isn’t a “glitch,” but a permanent change.

• The Return of the Spreadsheet: Media buyers at agencies start calling publisher sales reps directly. “I can’t buy you via the DSP. Can we set up a ‘Tag-in-Tag’ or a manual ‘Insertion Order’ (IO)?”
• Creative Reset: Since programmatic “Dynamic Creative Optimization” (DCO) is dead, agencies realize they can’t serve personalized ads. They have to go back to “One Size Fits All” static banners.
• The Death of Retargeting: All “Follow-me” ads (the shoes that follow you from site to site) vanish. Brands lose the ability to speak to their own customers on third-party sites.

Hour 24: The Economic “Hard Landing”

By the end of the first day, the structural damage is visible.

• Publisher Layoffs/Furloughs: Small-to-mid-tier publishers who operate on thin margins realize they cannot meet payroll if this lasts a week.
• The “Stock Market” Shock: Publicly traded AdTech companies (The Trade Desk, PubMatic, Magnite) see their stock prices crater. Investors realize these companies have no “product” if the bid stream is gone.
• User Experience (UX) Shift: For the first time in 15 years, the internet is “quiet.” There are no pop-unders, no mid-roll video ads on independent sites, and no tracking pixels firing. The web is faster, but the content behind it is now officially unfunded.
• Legal “Force Majeure”: Law firms begin reviewing “Service Level Agreements” (SLAs). Advertisers demand to know where their data went; Publishers demand to know why the SSPs didn’t deliver.

PHASE II: THE IMPACT OF THE SHOCK WAVE

The Fallout after 60 days

The dominance of the “Programmatic” era is over. On millions of websites, “remnant” ad slots—the spaces not sold via direct sales teams— would suddenly fail to load. In their place, users would see broken image icons, “white space” collapses, or default house ads for the publishers themselves.

The $500B+ AdTech ecosystem would undergo a violent transformation.  

1. DEMAND-SIDE PLATFORMS (DSPS): FROM “TRADERS” TO “WORKSTATIONS”

DSPs like The Trade Desk, MediaMath, or Adobe Advertising Cloud are currently built for real-time bidding (RTB). Without programmatic, their “Bidding Engines” become useless overnight. They can pivot in various ways:

The Impact:

• Workflow Automation (SaaS Transition): DSPs would attempt to rebrand as Automated Insertion Order (IO) Managers. Instead of bidding on impressions, the platform would become a project management tool where buyers click a button to “send a manual purchase request” to a publisher’s sales team.
• Direct-to-Publisher APIs: To bypass the loss of the “Open Exchange,” DSPs would scramble to build custom APIs directly into the ad servers of top publishers (The NYT, Hearst, Vox). They would transform into Private Marketplace (PMP) Aggregators, focusing only on “guaranteed” deals where the price is pre-negotiated.
• Infrastructure Downsizing: DSPs currently pay millions in cloud hosting costs (AWS/GCP) to listen to billions of bid requests per second. They would immediately shut down these “listening” servers, drastically reducing overhead but also reducing their value proposition to a mere “buying dashboard.”

2. Data Companies (DMPs & Identity Providers): The Value Evaporation

Companies like LiveRamp, Oracle Data Cloud, and various “Identity Graph” providers rely on matching user profiles to bid requests. If there is no bidding, there is no place to “inject” their data.

The Data Desert

The $200 billion data industry would evaporate. Data Management Platforms (DMPs) and third-party data brokers exist to fuel the “targeting” within the DSP. If there are no programmatic bids to inform, the data has no destination. The billions of profiles tracked across the web would become digital landfill—vast repositories of consumer behavior with no engine to monetize them.

The Impact:

• Loss of Real-Time Activation: Third-party data providers currently make money by charging a “data fee” (e.g., $0.50 CPM) every time an ad is served to a specific profile. Without programmatic, they lose their distribution channel.
• The Pivot to “Planning & Insight” Only: These companies would shift from Activation to Consulting. Instead of helping a machine buy an audience, they would sell “Market Research Reports” to agencies, telling them: “Our data says car buyers visit these 500 websites; you should manually call those publishers.”
• Clean Room Dominance: Data companies would double down on Data Clean Rooms. Since they can’t track users across the web, they would facilitate “safe rooms” where a brand (like Nike) and a publisher (like NBC) can match their first-party email lists to find overlap without using programmatic rails.

3. ANALYTICS & MEASUREMENT PLATFORMS: THE GREAT “BLIND SPOT”

Measurement companies (DoubleVerify, IAS, Moat) and Multi-Touch Attribution (MTA) providers (like Neustar) would see their core product—tracking the “path to conversion”—break.

The Impact:

• The End of MTA: Multi-Touch Attribution relies on seeing every ad a user saw before they bought a product. Without the unified logs of a DSP, it is impossible to know if a user saw an ad on Site A and then Site B. MTA companies would likely go bankrupt or pivot entirely to Media Mix Modeling (MMM).
• Verification Shift: Companies like IAS (Integral Ad Science) would stop focusing on “Pre-bid” filtering (blocking a bad ad before it’s bought) and move entirely to Post-bid Auditing. They would become “Digital Accountants,” checking publisher logs weeks after the fact to prove the ads actually ran.
• The Return of the “Pixel”: We would see a massive resurgence in basic tracking pixels. Since the centralized “brain” of the DSP is gone, every single ad execution would require a bespoke set of 10-15 tracking pixels to be manually implemented, leading to massive “page weight” issues and slow load times.

PHASE 3: LONG-TERM EQUILIBRIUM RE-ESTABLISHED: PUBLISHERS AND AGENCIES EMERGE AS THE BIG WINNERS

PUBLISHERS’ COMEBACK STORY:

For most publishers, this is the worst of times but will herald in the best of times. The impact would be catastrophic in the short term. News giants like The New York Times or The Guardian still maintain direct sales forces. However, for the “mid-tail” and “long-tail” of the internet—niche blogs, local news sites, and utility apps—programmatic is their only source of oxygen. Without the automated flow of bids, their revenue would drop by 60% to 90% instantly.

Adaptation in a Post-Programmatic World

The disappearance of programmatic rails creates a paradox: while it removes the “middlemen” publishers hate, it also removes the “demand” they rely on for survival.

Short-Term Chaos (0–6 Months): Survival at all Costs

The immediate aftermath would be characterized by a “Liquidity Crunch” that would likely force many mid-tier publishers into insolvency.

• The Revenue Cliff: For many publishers, programmatic “Open Exchange” revenue accounts for 40–70% of total income. This would drop to near zero overnight. Since manual sales cycles take 4–8 weeks to close, publishers would face a massive cash flow gap.
• The “Unfilled” Inventory Crisis: Currently, if a direct salesperson doesn’t sell a banner, programmatic “fills” it for a few cents. Without that backfill, websites would be littered with “House Ads” (ads for their own content) or blank white boxes.
• Massive Layoffs in AdOps: Ad Operations teams are currently trained to manage “yield” through platforms. They would suddenly be forced to manually “tag” every single ad creative. The sheer labor required to manage a site’s inventory would skyrocket, leading to a desperate rehiring of manual traffickers.
• Data Blindness: Publishers would lose the ability to see who is on their site in real-time. Without the “bid request” (which carries user data), publishers would only know their raw traffic numbers, not the demographic value of that traffic.

True – Ad Servers like Google Ad Manger and “Walled Gardens” might see a temporary bump, this would be a short-lived upturn until a more substantial restructuring can take place. After the trauma of the first six months, we would see a new business model emerge that now skews adtech in publishers’ favor.  

Mid-Term Restructuring (6–18 Months): The Publishers’ Rebirth After Programmatic

As the dust settles, the industry would reorganize into a “High-Intent/ High-Touch” marketplace.

• The Rise of the “Private Marketplace” (PMP) API: Publishers would build proprietary, direct-access portals. If P&G wants to buy the New York Times, they won’t use a DSP; they will log into a “NYT Self-Serve Portal.”
• Aggressive Paywall Expansion: Realizing that ad revenue is now volatile and labor-intensive, publishers would pivot hard toward “User-Supported” models. This could decrease the amount of “free” content in the “Free Web.”
• Contextual Re-Birth: Since tracking users across the web is dead, publishers would sell their Context. Instead of selling “Men 18-34,” they will sell “The Sports Section.” The value of editors and niche content creators would skyrocket because the content is the only proxy for the audience. With better contextual ad placements, all metrics are improved including conversions. This further puts a premium on high performing publishers.

Long-Term Market Equilibrium (18+ Months)

The long-term landscape favors the “Giants” and the “Niches,” while the “Middle” weakens.

1. The Consolidation of “The Great Middle”
   1. General news sites and “lifestyle” blogs that rely on scale but lack deep loyalty will struggle.  They cannot afford the sales staff required to sell ads manually, and they aren’t unique enough for a subscription. We would see a massive wave of M&A (mergers and acquisitions).
2. The Return of the “Bundle”
   1. Publishers would form Sales Collectives. Ten small tech blogs might hire one single sales team to sell them as a “Tech Package.” This mimics the early days of ad networks where scale is expressed in thousands not millions.
3. Premium Publishers Win: In a programmatic world, a user on The Wall Street Journal can be “retargeted” on a cheap weather app for 1/10th the price. Without programmatic, if you want the WSJ audience, you must pay WSJ prices. CPMs (cost per thousand impressions) for premium sites would actually increase significantly.
4. Efficiency Loss/ Impact Gain: While prices go up, the “volume” of ads sold goes down. The internet becomes less cluttered with ads, but the ads that remain are more expensive and higher quality.
   1. Integration of Commerce: Publishers would stop being “billboards” and start being “stores.” We would see a massive move toward Affiliate Revenue and Shoppable Content. If you can’t make money selling an ad for a shoe, you make money by selling the shoe itself through a direct partnership with the brand.

The comeback for publishers rests with new value placed on contextuality, premium ad placements, brand safety, and transparency. From the wreckage, new alternatives outside of programmatic can exist that creates new value for publishers and advertisers.  

THE AGENCY’S RENAISSANCE EMERGES

For agencies, this could be a rare moment of rebirth and reimagining their future and that of their clients. Like other stakeholders, initially, agencies will be scrambling behind the scenes to figure out how to continue advertising without the scale of programmatic.

Without automated Demand-Side Platforms (DSPs), the immediate problem is scale. A single programmatic trader today can manage millions of dollars in spend across thousands of sites. Without automation, that becomes impossible and as a result, we see

• Massive Rehiring of Media Buyers: Agencies would need to rapidly expand their “Media Buying” departments. The role of the “Programmatic Trader” (who optimizes algorithms) would be replaced by “Media Negotiators” (who talk to human publishers) and AI Agent media buying. This reverses the workforce reductions of the past 10 years.  
• The Media Management Boom: Agencies would revert to curated media buying. Instead of a machine buying an impression in 10 milliseconds, humans would reach out directly to publishers like the New York Times, ESPN, or niche blogs – at least for a while.

Then, rather dramatically, a new balanced set of options will present themselves that agencies can leverage like never before.

A. Shift in Strategy: From “Audience” to “Context”

Programmatic is built on Audience Targeting (following a specific user across the web based on their cookies/ID). Without it, agencies would lose the ability to “stalk” a user. The absence of programmatic media buying can allow for other systems to emerge:

• The Return of Contextual Advertising: If you can’t follow a car-buyer to a weather site, you simply buy ads on Car and Driver. Agencies would focus on where the ad is placed rather than who is looking at it.
• Direct-to-Publisher Deals: Agencies would move budgets into Premium Direct buys. Large “Walled Gardens” (Meta, Google, Amazon) would likely become even more powerful because they offer “logged-in” environments that don’t require external programmatic rails.
• Ad Networks 2.0: Agencies would build and own the “Intent Networks”— curated networks based on topics that bundles hundreds of small sites together and sell them as a single package to brands. These outlets would be transparent to brands and amped up with a performance orientation.
  
  This is when there be a new constellation of contextual ad networks will be created by agencies and by publisher groups. Buying in these networks will be automated via AI but it will not rely on real time bidding procedures. Instead, brands can pay premium for contextual ad placement leading to a new class of ad placements can provide brands with high-quality ad placements. This would also overcome banner blindness and low viewability standards of today.

B. Impact on Measurement and Reporting

Real-time dashboards would break but attribution platforms would come online based on topic-centric performance. Using UTM, agencies could link marketing spend with business outcomes.

• Econometric Modeling: Since granular “click-path” data would vanish, agencies would lean more heavily on Marketing Mix Modeling (MMM)—statistical method on what worked based on total sales vs. total spend, similar to how TV is measured.

C. Creative Renaissance

In the programmatic era, creative is often an afterthought to the “targeting.” If you can no longer target with surgical precision, the message must do the heavy lifting.

• High-Impact Units: Agencies would move away from standard 300×250 banners toward custom, “high-impact” executions that require manual implementation but command more attention.
• Creative Strategy Over Data Science: The power dynamic in agencies would shift back from the Data/Math departments to the Creative/Strategy departments.

D. The Great Fee Rebalancing

This is possibly the biggest upside agencies will see because it provides the context for a renegotiation of fees. Media buying needs a contextual buying layer, creative is more important in contextual media buys and data centers on revenue realization not shallow behavioral metrics like clicks.

All this allows for a realistic re-evaluation for brands to realign how their agencies are compensated – across the board.

Creative Fees:

• High-Intent Creative: Agencies would design for high-intent advertising that drives “high-impact” executions. This approach can be powered by AI but requires deep strategic insights and executions.
• Creative Versioning at Scale: While the agency might use AI to generate 500 variations of an ad for 500 different publishers, they will charge the client for the strategic oversight of those 500 versions, not the cost of the AI generation itself.

Media Buying and Management Fees:

• The New Role of AI: “The Human Multiplier.” Without programmatic bidding, AI’s role shifts from “buying ads” to “augmenting human talent” in research, creative versioning, and predictive modeling.
• AI-Enhanced Research: Agencies will charge for access to proprietary AI tools that analyze millions of pages of content to find the “perfect contextual fit” for a brand.
• Inventory Scarcity Management: Without an open exchange, premium inventory becomes finite. Agencies will charge a premium for “First-Look” access to publisher inventory that they have secured through long-standing relationships.
• The Increased Labor from Advertising Curation: Every single dollar spent requires oversight on everything from ad placement and frequency to trafficking and analytics. This increases the billable hours for the media department perhaps even justifying a move back to the traditional 15% Media Commission or higher. Some specific media functions that emerge in a post programmatic world include:
  • The Return of the High-Stakes Negotiator where media buying becomes a specialized craft of relationship management and leverage.
  • Inventory Scarcity Management: Without an open exchange, premium inventory becomes finite and scale is redefined. Agencies will charge a premium for publisher inventory that they have secured through long-standing relationships.
  • Volume Aggregation: Agencies will charge clients for the ability to aggregate spend across multiple accounts to force lower rates from publishers—a service that was out of favor in the reign of programmatic with endless ad inventory.   

Analytics and Data Fees:

• Revenue realization tracking. This type of revenue realization is an integration of attribution, marketing spend and sales management system that would be bespoke development for each company.
• The “Accountant” Fee: Agencies will act as financial auditors, reconciling publisher logs against client CRM data. This “Data Clean Room” management is a specialized service that commands a much higher hourly rate than simple dashboard reporting.

Strategic Services Fees:

• Consulting vs. Execution: Agencies will move away from being “vendors” toward “business consultants” who prove revenue growth, allowing them to charge management-consultancy-level fees.
• Strategic Margin: AI allows the agency to handle the increased workload of a post-programmatic world without hiring an infinite number of people, effectively increasing the Profit Margin per Employee.

Part II: The Great Adtech Renaissance: The Rise of the AI Direct Buying

In the weeks and months following the collapse, we would see a frantic return to “The Way Things Were”—but with a 21st-century desperation. Advertisers, still needing to move products, would have to pick up the phone.

This is the moment when AI is activated to best use. This is also the moment when agencies can rise up to lead this new era. With agencies as architects of this system, we would see the return of media planning but in a new context to align the brands to the publisher content.  Media planners would once again have to vet individual sites and negotiate rates but AI can automate all this.

Contextual advertising would not be the only game in town in the open web but it would compete for ad dollars effectively compared to programmatic media and walled garden.

The AI Direct Era – A New Architecture

AI will create a different architecture that allows marketers to package tasks into SOPs (Standard Operating Procedures) and workflows for easier automation. This architecture can continually update the SOPs and the workflows to adapt to changing business conditions.

Most importantly, this structure can be applied to everything from media and creative to strategy and research.

For example, in media buying and management, in “life after programmatic” we don’t return to the media buying of the 90s; we emerge into an AI-Driven Direct-to-Publisher (DTP) Buying.

Programmatic can be characterized by the middlemen required to facilitate the automation. In the next generation, Artificial Intelligence replaces the DSP and possibly the SSP entirely, creating a “Liquid Direct” market.

How AI Bypasses the DSP

In the current model, a DSP is a central brain that looks at every impression and decides whether to bid. In the AI Direct model, an advertiser’s proprietary AI agent communicates directly with the publisher’s API.

1. Direct API Interfacing: Instead of an “Exchange” where everyone screams at once, an advertiser’s AI “crawls” the web to find relevant content. When it finds a publisher that matches its brand safety and audience criteria, it initiates a direct, encrypted handshake via a standardized API.
2. Generative Creative Optimization: In the programmatic era, you sent one banner to a thousand sites. In the AI Direct era, the brand’s AI analyzes the publisher’s CSS, layout, and content tone in real-time. It then generates a “native” ad that perfectly matches the aesthetic of that specific site, delivering it via a direct server-to-server call.
3. The “Smart Contract” Settlement: Without the clearinghouses, payments are handled via automated smart contracts (yes – Blockchain may have finally found its useful role). As soon as the AI verifies the ad was served to a human (using advanced edge-computing verification), the payment is transferred directly from the brand’s treasury to the publisher’s account.

This is Better for Advertisers – Obviously

This “Next-Gen Adtech” removes the “Middleman Tax.” If a brand spends $1.00, the publisher receives $0.98, not $0.40. This creates a more sustainable web where quality content is rewarded, not just “clicks.”

Furthermore, AI avoids the “Privacy Trap.” Because the AI is buying context and direct relationships rather than “tracking people,” it doesn’t need to harvest third-party cookies. The brand’s AI understands the intent of the page better than any 2015-era tracking pixel ever could. It sees that a user is reading an article about “Sustainable Gardening” and knows, through deep linguistic processing, that this is the perfect moment for a composting tool ad—no “shadow profile” required.

Conclusion: A Diverse, Leaner, Smarter Web – The Trust Web

This entire scenario is absurd given the impossible premise. Yet even if we suspend common sense, and look at the worst case (and improbable) scenario, we realize a terrifying tale is actually a tale of redemption.  

At the moment, too many people think programmatic is too big to fail and would take down the entire digital marketing ecosystem with it.

This thought experiment proves otherwise. Programmatic became the dominant media system to the detriment of too many marketers. The opportunity is not to eliminate programmatic but to allow the emergence of higher quality adtech systems, such as a robust contextual system, that may be more expensive but higher performing in terms of sales outcomes.

It’s true – a programmatic “extinction” event would cause an economic shock for thousands of “AdTech” firms, but it would result in a more “human” internet with fewer junk ads and more meaningful partnerships between brands and publishers.

“Life After Programmatic” is a tale of resilience and reinvention. It is the opening needed for an elegant, direct AI-to-Publisher relationships. It is a world where the “Long Tail” of the internet survives not by selling their users’ data to the highest bidder, but by providing high-quality environments for brands to connect with through intelligent automation.

We move from a world of “Bidding” to a world of “Matching”—and in that transition, both the advertiser and the reader win.

This is how a more trusted contextual adtech system can emerge. It is how adtech gets its grove back.