As a global leader in SEO and data analytics, Anastasia Braitsik has spent years at the intersection of technical precision and high-level marketing strategy. In an era where artificial intelligence is no longer a futuristic concept but a daily operational reality, she advocates for a radical shift in how brands value and pay for agency expertise. The conversation today centers on the “we are not in Kansas anymore” moment for digital marketing—a transition where foundational AI models are now directly integrated into the very platforms agencies use, rendering many traditional manual tasks obsolete. We explore why the industry is seeing a potential 25% to 75% drop in certain fee structures and how the focus is shifting from repetitive labor to high-stakes strategic judgment.
The discussion highlights the convergence of three powerful forces: generally intelligent AI, platform-owned foundational models, and real-time data integration. These factors are dismantling the old agency scope, particularly in areas like keyword research, manual bidding, and routine reporting, which used to consume the lion’s share of marketing budgets. Anastasia breaks down the necessity of renegotiating contracts to prioritize incremental profit and verified revenue lift rather than vanity metrics or activity-based billing. By moving toward a structure that rewards outcome over effort, she explains how SEO teams can stop paying for the past and start investing in the future of search and generative experience optimization.
How is the integration of foundational AI models into modern advertising platforms fundamentally changing the cost structure of traditional agency work like keyword structuring and campaign build-outs?
The shift we are seeing is nothing short of a tectonic plates movement in the digital marketing landscape, where the heavy lifting of account architecture is being swallowed by the platforms themselves. In the past, humans spent countless hours slicing campaigns for granular control, but now that platform algorithms handle segmentation and targeting with superior precision, that specific work can shrink by close to 80%. When you realize that these foundational AI models are wired directly into the tools agencies use daily, the justification for a massive monthly retainer based on “setup” begins to crumble. It creates a scenario where clients should realistically expect savings between 25% and 75% on existing scopes of work because the machine has simply replaced the manual laborer. This isn’t just about efficiency; it’s about the fact that the work which once occupied a fifth of a typical contract’s cost now happens in milliseconds behind a digital curtain.
You’ve mentioned that manual bidding and pacing adjustments are becoming obsolete; how do human interventions in these automated processes actually impact campaign performance today?
There is a visceral tension when a human feels the need to “rescue” a campaign during a slight dip, but in the age of AI, that instinct is often the worst thing you can do. Since late 2024, AI has consistently outperformed human pacing decisions, yet many agencies still feel the need to jump in and make manual adjustments to justify their management fees. What they don’t realize—or perhaps don’t want to admit—is that every time a human interferes with an AI learning cycle, they are actively sabotaging the algorithm’s ability to optimize and essentially resetting the learning clock. It’s like trying to correct a self-driving car by grabbing the wheel every time it encounters a pebble; you’re not helping, you’re just creating chaos in a system that needs data stability to perform. We have to move away from the idea that manual intervention equals value, because in reality, that intervention is often an expensive way to hinder growth.
Reporting often consumes a massive portion of an agency’s budget, so how can brands transition from paying for manual spreadsheets to a more efficient, AI-fronted analytical model?
It is staggering to think that weekly decks and hand-typed commentary on numbers that already exist in a dashboard can eat up close to a third of a contract’s total cost. We are entering an era where AI-fronted data tools can explain the “what” and the “why” of performance without a human middleman translating a spreadsheet into a PowerPoint slide. By automating this explanatory layer, brands can slash about 60% of their reporting costs, freeing up that budget for work that actually moves the needle on revenue. The goal is to move the agency’s role away from being a “data reporter” and toward being a “data navigator” who decides what the machine should optimize toward. When you stop paying for the physical act of reporting, you start buying the mental capacity to act on the insights that the AI is already surfacing in real-time.
What does a modern, high-performance agency contract look like when it’s built around the three-way split of base retainers, project fees, and outcome incentives?
A future-ready contract must be split to reward strategic judgment rather than just the passage of time or the volume of deliverables. I advocate for a lean base retainer, roughly 40% to 50% of the total, which focuses purely on governance, steering, and the critical architecture of data engineering. Then, you allocate 30% to 40% for project fees that cover high-level human judgment tasks like complex strategic analysis, portfolio strategy, and creative concepting that machines cannot yet replicate. The final piece—the most important 15% to 25%—should be an outcome incentive tied directly to incremental profit or verified revenue lift, moving away from platform-reported metrics like ROAS which can be easily inflated. This structure ensures that the agency is a true partner in your growth, rather than a vendor checking boxes on a list of activities that may or may not impact your bottom line.
For SEO teams specifically, how should they categorize their current statement of work to identify which tasks are “past-oriented” versus “future-ready” strategic judgment?
SEO leaders need to be incredibly honest with themselves and perform a cold-blooded audit of their current SOW, sorting every line item into buckets based on its actual value in an AI world. Anything that smells like keyword research busywork, manual rank tracking, or templated technical audits belongs in the “machine-ready” pile because automated crawlers and GA4 anomaly detection have already closed that gap. You have to look at the hours being billed for blog posts and “audits shipped” and ask if that activity is actually driving organic revenue or just filling a folder with PDFs. The future-ready tasks are those involving content architecture for AI Overviews, entity building, and GEO strategy—work that requires a deep understanding of how generative engines interpret brand authority. If you’re still paying for the “past” of manual link lists and rank reports, you’re essentially writing a check for a world that no longer exists.
Why is owning your own data—from GA4 to log files—the non-negotiable first step before entering any renegotiation with an external partner?
Ownership of your data is the only real leverage you have; if your agency holds the keys to your Search Console, GA4, and log files, you are effectively a hostage in your own marketing department. You cannot ask for a 25% to 75% reduction in fees if you don’t have the independent data to prove that the platform is doing the work previously handled by human hands. Having your own AI citation tracking and data warehouse in-house allows you to see the “why” behind the performance without a biased third party filtering the results. It provides the clarity needed to see through the “activity” trap and demand a contract built on verified revenue and Citation Share of Voice. Before you even sit down at the negotiating table, you must ensure that every byte of performance data sits in your hands, giving you the power to walk away or restructure as the market evolves.
What is your forecast for the survival of agencies that continue to sell manual labor in an era where machines handle the heavy lifting?
I believe we are approaching a “survival of the smartest” moment where agencies that continue to sell hours and manual rebuilds are going to lose their clients before they even realize they’ve lost the argument. The agencies that survive the next two years will be the ones that transform into “judgment engines,” selling the high-stakes decisions that a machine simply cannot supply. We will see a massive shakeout where “deliverable-heavy” shops go under, replaced by leaner, more strategic partners who thrive on outcome-based compensation and complex entity-based SEO. If an agency cannot show how they are using AI to lower your costs while simultaneously increasing your growth through 15% to 25% new, strategic work, they are effectively a relic. Ultimately, the industry is moving from a model of “doing the work” to “directing the intelligence,” and those who can’t make that leap will be left behind in the archives of digital marketing history.
