Report: U.S. E-commerce Companies Adopt AI but Remain Cautious About Marketing Spend Decisions

A report published on November 13, 2026, shows that U.S. e-commerce companies are actively adopting artificial intelligence (AI), but remain cautious about allowing AI to manage actual marketing budgets and spending decisions. This reflects the trust and compliance considerations that remain between integrating AI into business processes and granting it authority over financial decisions.

The report’s key focus is not whether companies use AI, but how far its use extends. When a system processes information or makes recommendations, companies need to assess the quality of those recommendations. When a system can allocate budgets or directly affect spending, companies must also consider decision-making authority, accountability, and potential business consequences.

The decision-making boundary shifts from making recommendations to managing spending

Marketing budgets involve actual business expenditure. AI can contribute to analysis or support decision-making, but whether to accept a recommendation, when to adjust spending, and who bears ultimate responsibility are separate decisions. Caution around spending decisions means that, alongside adopting the technology, companies also consider whether automated decisions can be understood and monitored.

The difference between the two approaches lies in whether the system’s output directly triggers a financial action. For example, if AI recommends a budget adjustment and relevant personnel review it and decide whether to implement it, a clear decision-making step involving people remains. If the system is authorized to adjust spending on its own, oversight must also address the authorization granted before the adjustment and the monitoring that follows its execution.

This does not mean that the companies covered by the report have adopted a uniform management model. The findings only show that a positive attitude toward AI adoption coexists with caution about authorizing marketing spending. The findings alone do not establish which tools companies actually use, how much authority they grant them, or how they prioritize their concerns.

Questions to address when automating budgets

When AI is involved in marketing spending decisions, the first step is to distinguish between recommendations and execution: can the system only propose a plan, or can it adjust budgets under certain conditions? If automated execution is allowed, the scope of authorization and the circumstances requiring human intervention will both affect how much companies trust this arrangement.

The next question is whether the decision-making process can be traced. Budget adjustments involve actual costs, so relevant personnel may need to understand the rationale for an adjustment, its results, and subsequent changes in order to assess whether the system is operating in line with its objectives. The key is not just seeing the final spend, but also being able to identify which adjustments were proposed or executed by the system and how to determine the cause of any deviation.

The allocation of responsibility is equally important. Marketing decisions may involve business objectives, financial management, and compliance requirements. Even when some actions are performed by a system, companies still need to clarify who sets permissions, reviews results, and handles exceptions. Concerns about AI managing spending may therefore relate not only to its technical capabilities, but also to how the organization oversees the system and assumes responsibility.

Compliance considerations depend on the specific business and applicable requirements. The report summary does not list specific rules or violations, so it cannot be used to conclude that companies have already faced a particular penalty or compliance issue. What is clear is that once automation involves actual spending, requirements for authorization, recordkeeping, and review directly affect the scope of work a system can take on.

The impact may first be seen in the scope of authorization, rather than in whether AI is adopted

For e-commerce companies, the more immediate question in the short term may be how to define AI’s permitted scope of use, rather than simply whether to use it. Companies can use system-generated analysis while retaining human decision-making, or grant limited authorization for specific budgets. These approaches differ in execution efficiency, oversight costs, and how risks are managed.

For those providing marketing automation tools, this trend also highlights considerations beyond product capabilities: support for clear permission settings, decision records, and human intervention may influence whether companies accept a tool’s role in spending management. Having these features does not automatically mean that companies will grant broader authorization; the actual outcome still depends on the tool’s performance, business needs, and each company’s management requirements.

Going forward, it will be worth watching for further details in the report about the scope of the survey and related concerns, as well as companies’ publicly disclosed AI marketing practices. Areas to watch include which spending decisions are the main focus of caution, how companies set up human review, and whether the results of system-executed actions are continuously evaluated. This information will help distinguish companies’ acceptance of AI-assisted marketing from their willingness to authorize AI to make autonomous financial decisions.