Bot and AI traffic: how to protect your ad budget in 2026

The context: why non-human traffic has become a budget problem

For years, bot traffic was treated as a minor nuisance. In 2026, the situation has changed structurally. AI agents, from shopping assistant crawlers to answer engine spiders, generate traffic volumes comparable to human ones in many e-commerce categories. According to an analysis published by Digiday, digital retail brands are facing a real dilemma: non-human traffic interferes with retargeting strategies, but not all of it is without commercial value.

The problem is therefore twofold. On one hand, ad platforms bill impressions and clicks on bot-generated sessions, eroding budget without producing conversions. On the other, blindly blocking AI agents means cutting off potential touchpoints with tech-assisted buyers. So the answer can be neither "ignore it" nor "block everything."

For Italian SMEs, the impact is proportionally heavier. Paid media budgets are often limited. So every percentage point of unqualified traffic entering the retargeting funnel translates into a direct, measurable cost.

The numbers reshaping marketers' priorities

The phenomenon isn't uniform across sectors. The hardest-hit categories are e-commerce, travel and finance, the verticals where AI shopping agents are most active. The problem is set to grow, not shrink.

Moreover, the cost per acquisition (CPA) of retargeting campaigns is distorted when the audience pool includes bot sessions. Ad platforms (Google Ads, Meta, programmatic) don't automatically filter all non-human traffic uniformly. As a result, marketers who don't act proactively pay an invisible premium on every conversion.

A second relevant finding concerns the quality of first-party signals. If the tracking pixel records bot sessions, lookalike audience models and smart bidding strategies are fed polluted data. So the effect isn't limited to immediate cost: it extends to the quality of future campaigns. That's why we at SHM Studio consider first-party data cleanup an operational priority, not an optional task.

Not all bots are equal: an operational taxonomy

Before defining a strategy, you need to classify non-human traffic. There are at least three distinct categories, with very different implications for marketers.

• Malicious bots: scrapers, click fraud, automated competitor intelligence. Block them without exception. They drain budget and pollute data with no commercial value.
• Neutral crawlers: search engine spiders, web archives, monitoring tools. They don't generate direct ad costs, but they can skew organic traffic metrics if not segmented correctly.
• Commercial AI agents: crawlers of shopping assistants like those built into Amazon Alexa Shopping AI or other recommendation systems. These agents gather product information on behalf of real buyers. Blocking them could reduce your catalog's visibility in AI-assisted channels.

So the strategic decision isn't binary. It requires granular segmentation based on user agent, behavioral patterns and access frequency. In particular, commercial AI agents deserve different treatment from malicious bots.

The strategic view: the dilemma dividing marketers

The debate among paid media professionals reflects a real tension. On one side, those who argue for aggressively blocking all non-human traffic to protect data purity. On the other, those who argue that AI agents are an emerging channel for commercial distribution, and that shutting them out means giving up future visibility.

Much like personalized purchase notifications, as we explored in our deep dive on Alexa Update Me When and purchase notifications, the behavior of AI agents is evolving toward ever more sophisticated forms of commercial intermediation. Ignoring this traffic today could mean starting late tomorrow.

Still, the pragmatic view is that the two needs aren't mutually exclusive. You can block malicious bot traffic, segment neutral traffic and open dedicated channels for commercial AI agents. This setup does require technical investment and structured data governance. It's not something you can improvise in a week.

A useful parallel comes from the world of content. The question of visibility in AI systems, covered for example in our analysis of ChatGPT Ads and the implications for Italian SMEs, shows how companies that ask the right questions early gain a structural advantage. The same principle applies to managing non-human traffic.

The cost of indecision: what happens if you don't act

Not taking an explicit position on bot traffic has concrete, measurable consequences. First, the CPA of retargeting campaigns rises progressively as the audience pool gets polluted. Second, smart bidding platforms optimize toward distorted conversion signals, creating a negative compounding effect over time.

Attribution reports also get worse. Bot sessions that complete micro-conversions, such as viewing a product page or adding to cart, are recorded as real events. As a result, the attribution model overstates the effectiveness of some channels and understates that of others. The budget allocation decisions that follow are systematically skewed.

Operational implications: three priorities for Italian SMEs

Turning this analysis into action takes a structured approach. At SHM Studio, we identify three operational priorities for companies that want to tackle the problem systematically.

Priority one: audit your current traffic. Before any intervention, you need to quantify the share of non-human traffic across your company's digital properties. Tools like Google Analytics 4, with advanced filters, and specialized solutions like DoubleVerify or Integral Ad Science allow granular segmentation. This analysis should be run separately by channel: organic, paid, direct, referral.

Priority two: set up exclusions in paid platforms. Google Ads and Meta offer brand safety and invalid traffic exclusion options that many SMEs don't fully use. In particular, retargeting campaigns should explicitly exclude audience segments with anomalous behavioral patterns. Combined with a well-structured Google Ads campaigns strategy, this can significantly reduce CPA within a few weeks.

Third priority: set an explicit policy for commercial AI agents. This is the newest and least-covered area. Companies need to decide which AI agents to allow, how often, and on which sections of the site. The decision has both technical implications (robots.txt and rate limit configuration) and commercial ones, tied to visibility in AI-assisted channels. The topic also overlaps with emerging engagement strategies, like those explored in TikTok and the new engagement formats for brands: content distribution is changing, and access policies need to keep pace.

Tools and resources for a data-driven strategy

The market for bot detection tools is mature, but choosing the right one depends on your context. For SMEs with limited budgets, combining Google Analytics 4 with advanced filters and the built-in invalid traffic exclusion features of paid platforms is an accessible starting point.

For companies with higher traffic volumes or high-margin e-commerce, dedicated solutions like DoubleVerify offer finer granularity and more detailed reports. These platforms classify traffic in real time and can integrate directly with programmatic DSPs, cutting spend on unqualified impressions before they are bought.

Finally, if you run LinkedIn campaigns, where bot traffic is structurally different from the open web, the considerations change. LinkedIn campaigns run in a more controlled environment, but they aren't immune to the problem. Here too, audience segmentation and monitoring engagement patterns remain essential practices.

To explore the full landscape of paid media and advertising strategies, our hub on advertising, paid media and video collects our latest analyses on these topics.

Toward digital traffic governance: the framework that's still missing

The current debate among marketers reflects the lack of a shared standard. There is still no universally accepted taxonomy for classifying commercial AI agents, nor a communication protocol between sites and agents that allows transparent access management. This gap is structural and won't be closed in the short term.

As a result, companies waiting for an industry standard before acting are falling behind competitively. By contrast, those who build internal traffic governance today, even if imperfect, gain data, skills and processes that will become a differentiating asset when the standard arrives.

At SHM Studio, we recommend treating this as a structural component of your digital marketing strategy, not a technical problem to hand off to IT. Decisions about which agents to allow, which to block, and how to set up paid campaigns accordingly are business decisions with a direct impact on ROI. They should therefore be made at the marketing management level, with the support of the right technical expertise.