Agentic AI represents a fundamental shift in how people - and now, machines - navigate digital interactions.
AI is no longer limited to providing suggestions or answering prompts. They’re starting to research, compare, and even complete transactions on behalf of users.
This changes the entire buyer journey.
For marketers, this creates both opportunity and uncertainty. Agentic AI introduces a new category of traffic: non-human, but not invalid.
These are digital agents acting on behalf of real buyers. They aren’t here to waste budgets or skew reports. In many cases, they’re delivering legitimate, conversion-driving interactions.
The challenge is knowing how to adapt. Which touchpoints will disappear? How should paid media strategies evolve? And how do you protect budgets from harmful automation while preserving valuable agent-driven traffic?
Let’s discuss what agentic AI means for marketing, performance, and ad fraud - and how Lunio is helping marketers stay ahead.
What is agentic AI?
Agentic AI refers to autonomous artificial intelligence systems capable of taking goal-directed actions without continuous human input. Unlike traditional AI tools, which respond to rules or prompts, agentic AI can initiate actions, plan, and execute complex tasks across digital environments.
Examples include AI agents that can:
- Independently browse websites
- Compare products and services
- Complete purchase flows
- Book appointments or meetings
- Read reviews and optimise decisions to achieve a specific outcome
In short, these agents act as self-directed digital concierges. While agentic traffic currently accounts for less than 1% of web interactions, that share is expected to rise as costs fall and adoption grows.
Will buyers embrace agentic AI?
The appeal of agentic AI for buyers is clear: it saves time, cuts out complexity, and makes decisions more accurate:
- Time savings: Agentic AI can save consumers hours of browsing or endless product/service comparison tables.
- Better objectivity: Agents weigh multiple variables - price, reviews, delivery times - without the emotional bias that can skew human decision-making.
- Always on: AI agents don’t sleep - meaning they can act overnight to catch flash sales or reserve hard-to-get bookings.
- Hyper-personalisation: Agents go beyond standard recommendation engines, making choices based on individual goals, preferences, and past behavior.
Imagine a B2B buyer delegating software research to an AI agent. Instead of sitting through endless demos, the agent could pull pricing, check integrations, compare customer satisfaction ratings, and recommend the best fit - all before the buyer has opened their inbox. That’s the level of convenience and efficiency we’re talking about.
And if that efficiency becomes widely accessible, there's a strong chance buyer behavior (and expectations) will permanently shift.
How agentic AI changes marketing
For marketers, agentic AI represents a seismic change. Buyer journeys compress, touchpoints shrink, and much of the “persuasion” work happens out of sight.
Buyer journeys will shorten
Instead of nurturing a buyer across weeks or months, entire research and decision processes may be condensed into a handful of machine-driven interactions. That means:
- Faster decision cycles
- Fewer interactions with your brand content
- Greater reliance on structured, factual, machine-readable information
Visual design and clever storytelling matter less. Agents will be looking at things like refund policies, customer reviews, and logistics guarantees.
Go-to-market strategies will shift
You may never directly interact with a buyer if their agent manages the transaction. Instead of swaying humans, marketers need to “convince the AI” by providing transparent, trustworthy data. Pricing, product specs, and satisfaction scores become more influential than emotional hooks.
Platforms that make this easier - marketplaces with real-time pricing, APIs, and comparison-friendly structures - are likely to attract more agentic attention .
Websites will need dual design
Sites will need to serve two audiences at once: humans seeking immersive brand experiences and AI agents seeking fast, structured data.
- Schema markup and structured metadata will be essential
- APIs and fast-loading headless architectures will be more common
- Emotional UX copy will have less impact, since agents can’t be swayed by storytelling
Implications for performance marketing
Paid media is particularly exposed to the rise of agentic AI. Campaigns will need to adapt across creative, targeting, and channel strategies.
Messaging shifts from emotional to functional
Traditional ad creative leans heavily on emotion. But AI agents will make decisions based on cold logic. Marketers will need to surface factual value props - pricing, specs, trust signals, delivery speed - alongside emotional hooks. Campaigns that only rely on one or the other will miss part of their audience .
Targeting and bidding logic will change
Agents won’t neatly fit into existing audience models. Since they act on behalf of humans, they obscure demographic or behavioral traits that ad platforms rely on. Match rates could suffer.
Marketers will need to:
- Invest in first-party data
- Lean more on contextual targeting
- Prepare for broader targeting models
Channels and discovery will shift
AI agents may favor structured environments where information is clear and easy to extract. Marketplaces like Amazon or Booking.com could become more central to discovery compared to brand-owned sites.
Formats matter too. Text-rich or structured listings may be preferred over visual-heavy ads that don’t provide extractable value .
Traffic quality will be harder to judge
The old binary model of “bot vs. human” won’t work. Some agentic traffic will look like bots - fast navigation, consistent decision-making - but actually be high-value, user-authorized sessions. Marketers will need to adopt intent-based classification to distinguish helpful automation from malicious bots .
Ad fraud in the age of agentic AI
Sophisticated AI-driven bot traffic has surged in recent years, capable of easily bypassing the basic filters put in place by ad platforms. That’s made advanced invalid traffic protection essential for any business looking to protect ad budgets and maintain campaign efficiency.
But, with agentic AI on the rise, the challenge isn’t to block all automation. It’s to block the bots that drain ad budgets and distort analytics - not the AI agents that can deliver real, conversion-ready interactions.
Ultimately, agentic AI is a double-edged sword for traffic integrity. It creates both new risks and new opportunities in ad fraud prevention:
Risks
- Blurring the line: Legitimate agentic sessions may look like invalid traffic, while fraudsters can mimic agent-like behavior.
- Spoofing and mimicry: Malicious actors may disguise traffic as agentic to bypass filters, draining budgets in the process.
- Legacy detection gaps: Traditional techniques - IP lists, device fingerprints, user agents - will struggle, since agents often run from residential IPs or authenticated browsers .
Opportunities
- Intent-based profiling: Shift detection focus from what the traffic is to why it behaves the way it does.
- Cross-channel pattern recognition: Agentic AI often behaves consistently across systems. Multi-channel analysis can spot legitimate intent.
- Continuous learning: Detection must evolve in real time to track new mimicry tactics and subtle shifts in behavior .
So, here’s how we’ve moved beyond simply blocking bots, and work to recognize and preserve value in all its forms - including non-human ones.
How Lunio is adapting
At Lunio, we see agentic AI as an opportunity, not a threat. Our job is to help marketers protect budgets, preserve valuable automation, and stay confident in traffic quality. We’re approaching this through four strategic pillars.
1. Significant investment in data science
We’ve tripled our data science investment this year, building models that can detect new IVT sources without blocking legitimate agent-driven traffic.
What it means for you: faster innovation, earlier protection, and confidence that valuable automation isn’t mistakenly filtered out.
2. Nuanced, intent-based detection
Our detection philosophy has always been built on intent, not binary rules. Now, we’re expanding by:
- Adding new signals to better detect agentic behavior
- Simulating bad traffic in controlled environments to refine detection
- Evolving systems to separate genuine automation from harmful bots
What it means for you: your budgets stay protected as traffic diversifies, without cutting off high-quality agent-driven conversions.
3. Enhanced transparency
We’re building deeper reporting into traffic sources and IVT classification. You’ll be able to track agentic traffic as a distinct category and understand how it’s shaping your campaigns.
What it means for you: more control, clearer visibility, and smarter optimization decisions.
4. Continuous model evolution
Our detection models aren’t static. They’re retrained and improved continuously in response to new data, emerging threats, and evolving buyer behavior.
What it means for you: peace of mind. You’ll always be protected, no matter how fast the traffic landscape shifts.
Final thoughts
Agentic AI is set to change marketing in profound ways. Buyer journeys will be compressed. Paid media strategies will need to pivot toward factual messaging, new targeting models, and machine-readable formats. And the definition of valid traffic will evolve.
The good news is that this isn’t a problem to fear - it’s a frontier to navigate.
With the right detection systems, marketers can embrace agentic AI without losing confidence in their campaigns.
At Lunio, we’re focused on helping you make that shift. By preserving valuable automation, protecting budgets, and keeping traffic quality a competitive advantage, we’ll make sure you stay ahead in the agentic future.
FAQs: Agentic AI in marketing
Will agentic AI replace human buyers?
No. Agentic AI will act as an assistant, not a replacement. It will streamline research, comparisons, and transactions, but humans will still set goals, preferences, and final approvals.
How can I prepare my ad campaigns for agentic AI?
Focus on machine-readable value props: structured data, transparent pricing, clear specs, and strong trust signals. Campaigns should appeal to both human emotion and agentic logic.
Does agentic AI make ad fraud worse?
It changes the challenge. Some automation will be legitimate and conversion-driving, while malicious actors will try to spoof agentic behavior. The key is intent-based detection to separate good from bad.
Which platforms will agentic AI favor?
Agents are likely to prefer structured environments where data is easy to extract - think marketplaces like Amazon, Booking.com, or APIs that deliver real-time pricing.
What is Lunio doing to adapt?
We’re investing heavily in data science, building intent-based detection, enhancing transparency, and continuously evolving our models to protect ad spend while preserving legitimate automation.
Learn more about how Lunio can help you maximize your ad budget here.
