Ajarro, LLC is advising Amazon sellers to evaluate product profitability, inventory availability and advertising costs before expanding the use of artificial intelligence (AI) in campaign management and e-commerce operations. The consulting firm’s position, outlined by founder Brett Lemker, is that automation can accelerate decisions but cannot compensate for weak business economics or inadequate operational oversight.
The guidance comes as Amazon expands AI capabilities for sellers and advertisers. Although automation can reduce the time required to analyze performance reports, prepare product content and manage campaigns, Ajarro argues that brands must first establish whether those activities contribute to sustainable profit.
A campaign can generate sales and report an attractive return on ad spend (ROAS) without producing a healthy margin after product costs, marketplace fees, freight, discounts and returns. Similarly, increasing sales velocity can create inventory shortages if replenishment cannot keep pace with demand.
For Amazon advertisers, the distinction is important: improving campaign metrics does not necessarily improve the financial performance of the business.
Contribution Margin as the Starting Point
Ajarro recommends that brands establish product-level contribution margins before increasing advertising budgets or expanding promotions. The assessment should account for the costs that materially affect individual products rather than relying solely on blended account-level averages.
Contribution margin helps businesses evaluate how much revenue remains after relevant variable costs. When combined with advertising expenses, it can help sellers determine how much they can afford to spend to acquire customers while maintaining acceptable profitability.
This approach changes how advertising performance is assessed. Instead of judging campaigns primarily by sales volume or ROAS, sellers can compare products according to their economics and identify where additional investment is justified.
Discounting requires similar scrutiny. Promotions may increase order volume but still weaken profitability when lower selling prices combine with advertising expenditure and fulfillment costs. A product that attracts more customers is not necessarily a stronger commercial proposition if each additional sale contributes less toward covering operating expenses.
For advertising teams, this means campaign optimization should reflect product-level financial constraints. Budget increases, bidding adjustments and promotional activity need to be evaluated against the margin available to support them.
Connecting Advertising With Inventory Management
Ajarro also highlights the relationship between advertising decisions and inventory availability. Campaigns that increase demand for products with limited sellable stock can accelerate stockouts, potentially interrupting sales and creating additional replenishment pressure.
Reducing advertising indiscriminately presents a different risk. Profitable products with sufficient inventory may lose visibility and sales opportunities if budgets are cut without considering stock levels and expected demand.
Addressing these trade-offs requires coordination between advertising, merchandising, inventory management and finance teams. Campaign performance data is only one part of the decision. Warehouse stock, incoming shipments, listing status and the cash required to fund replenishment also influence whether additional demand can be supported.
For sellers managing multiple products, this integrated approach can help distinguish between campaigns that should scale, those that need tighter controls and those that should be paused while operational constraints are resolved.
Setting Boundaries for AI-Driven Decisions
Ajarro’s recommendations do not reject AI adoption. Instead, the company advocates establishing explicit limits before allowing automated systems to execute consequential changes.
Those controls can include advertising spending thresholds, minimum pricing rules and approval requirements for actions that could materially affect profitability. Businesses should also establish which tasks can run automatically, which require human review and who is accountable when results deviate from expectations.
AI can assist with identifying performance anomalies, processing reports and executing approved workflows. However, a recommendation to increase spending still needs to be assessed against product margins, available inventory and the company’s financial priorities.
Lemker, who brings 20 years of Amazon and e-commerce experience to his consulting work, argues that experienced oversight remains important when interpreting recommendations and weighing commercial trade-offs.
Ajarro has not provided quantitative evidence comparing AI-managed campaigns with human-led alternatives, nor has it disclosed performance benchmarks or a specific software platform associated with its recommendations. Its announcement is best understood as operational guidance rather than a measured assessment of any particular AI product.
Market Landscape
AI-assisted advertising is part of a broader shift toward automating campaign analysis and routine optimization. For Amazon sellers, however, marketplace advertising operates within a business model that also includes fulfillment costs, inventory financing, pricing decisions and product-level profitability.
This creates a distinction between automating campaign execution and automating the broader commercial decision. The former can reduce repetitive work; the latter requires reliable business data, clearly defined constraints and an understanding of operational consequences.
Ajarro’s position reinforces the need to connect advertising technology with financial and inventory information rather than optimize campaigns in isolation.
Strategic Outlook
Amazon sellers adopting AI will need governance processes that connect automated recommendations to measurable business objectives. Product-level margins, inventory thresholds and spending limits provide practical controls for deciding when systems can act independently and when experienced staff should intervene.
For agencies and e-commerce consultants, this creates an opportunity to move beyond campaign management toward broader commercial analysis. For brands, the priority is to ensure that faster decisions translate into sustainable profitability rather than simply higher sales volume.
The central question is not how much advertising work AI can automate, but whether the decisions it accelerates improve the economics of the business.
Top Insights
- Profitability first: Ajarro recommends assessing product-level contribution margins before scaling advertising.
- ROAS has limits: Strong advertising returns do not automatically indicate healthy net profitability.
- Inventory affects campaign strategy: Advertising budgets should reflect available stock and replenishment timelines.
- AI needs guardrails: Spending limits, pricing floors and approval rules can constrain automated decisions.
- Human oversight remains relevant: Experienced operators must evaluate trade-offs that extend beyond campaign metrics.
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