In May 2025, Google announced Marketing Advisor—an AI agent that lives in Chrome and helps advertisers manage campaigns across platforms. A month later, Amazon unveiled Ads Agent, promising to "reimagine the advertising experience" with autonomous campaign planning.
These aren't just chatbots or automation scripts. They're agentic AI systems—capable of pursuing goals autonomously, making decisions, and taking actions without constant human prompting.
Welcome to the era of agentic advertising.
What is Agentic Advertising?
Definition
Agentic advertising introduces AI-driven agents into the ad ecosystem. These agents are capable of making real-time decisions on behalf of advertisers, agencies, DSPs, SSPs, or publishers based on highly complex inputs and data computation.
— Scope3
Unlike traditional automation (which follows pre-defined rules), agentic AI can:
- Reason about goals — Understand high-level objectives like "reduce CPA by 20%"
- Break down complex tasks — Decompose objectives into research, planning, execution steps
- Use tools — Call APIs, read data, create campaigns via platform integrations
- Adapt in real-time — Respond to performance data, market changes, and new information
- Operate autonomously — Execute workflows without requiring a human prompt at each step
How Agentic Advertising Works
An agentic advertising system typically has four components:
1. Large Language Model (LLM) Brain
The reasoning engine—typically GPT-4, Claude, or Gemini—that understands natural language, makes decisions, and orchestrates tool usage. This is what makes the agent "intelligent" rather than just automated.
2. Tool Access (APIs)
Connections to advertising platforms—Google Ads API, Meta Marketing API, LinkedIn Marketing API, etc. The agent uses these tools to create campaigns, pull performance data, adjust bids, and upload creative.
3. Memory & Context
Knowledge of your business, historical campaign performance, brand guidelines, and goals. This context allows the agent to make decisions aligned with your specific situation.
4. Human Oversight Layer
Guardrails that define what the agent can do autonomously vs. what requires approval. For example: "Auto-pause ads with CTR below 0.5%, but get approval before budget changes over $1,000."
Who's Building Agentic Advertising?
The race is on. Here are the major players:
Big Tech Platforms
Google Ads
Google is building agentic capabilities directly into Google Ads. Their "agentic expert" will offer personalized recommendations for campaigns—keyword suggestions, creative ideas, bid adjustments—and can implement changes on the advertiser's behalf.
They're also building Marketing Advisor, a Chrome-based agent designed to help advertisers manage marketing tasks across different platforms.
Amazon Ads
Amazon's Ads Agent combines agentic AI with Amazon's first-party shopping data. It can plan campaigns, generate creative, and optimize based on purchase intent signals that only Amazon has access to.
Independent Platforms
Multi-Platform Agents (like Synter)
While Google and Amazon build walled-garden agents for their own platforms, startups are building agents that work across multiple platforms—Google, Meta, LinkedIn, Microsoft, Reddit, and X.
The advantage: unified strategy across channels, consistent brand voice, and budget optimization that considers the full funnel rather than one platform in isolation.
Agency-Focused Tools
Companies like MINT are building agentic workflows for media operations—automating the routine work that eats up agency time. Early users report 30% reductions in time spent on routine media operations.
Agentic AI vs. Rule-Based Automation
Here's how agentic advertising differs from the automation you're already using:
| Capability | Rule-Based Automation | Agentic AI |
|---|---|---|
| Decision Making | If X, then Y | Reasons about goals, adapts approach |
| Handling Exceptions | Fails or escalates | Troubleshoots, tries alternatives |
| Multi-Step Tasks | Pre-defined workflows only | Breaks down novel tasks dynamically |
| Natural Language | Keywords, structured input | "Reduce CPA on LinkedIn by testing new audiences" |
| Learning | Static rules | Improves from performance data over time |
Think of it this way: rule-based automation is like a script that follows instructions exactly. An AI agent is more like a junior media buyer—it can be given a goal, figure out how to achieve it, and ask for help when needed.
Use Cases Across the Ad Ecosystem
Agentic AI applies to every role in advertising:
For Advertisers (Buy-Side)
- Intelligent bid managers that adjust strategies based on evolving goals
- Cross-channel budget optimization in real-time
- Automated creative testing with statistical rigor
- Negative keyword mining from search term reports
For Publishers (Sell-Side)
- Dynamic floor price optimization
- Automated deal negotiation with buyer agents
- Inventory forecasting and yield management
For Agencies
- Scaling client management (5 brands → 25 brands with same team)
- Automated reporting and insight generation
- Campaign launch workflows across platforms
The Consumer-Side Revolution
Here's where it gets interesting: consumers will have agents too.
Imagine a personal AI that filters and personalizes advertising based on your actual needs. Instead of brands competing for ad space on platforms, advertisers would engage directly with AI agents that act in users' best interests.
Consumer Agent Example
"I'm looking for a CRM under $50/user/month with good Salesforce integration. Show me relevant options and filter out anything that doesn't match."
The agent negotiates with advertiser agents, surfaces relevant options, and blocks irrelevant ads entirely.
This shifts advertising from interruption to invitation—brands that provide genuine value win; brands that rely on spray-and-pray lose access entirely.
Challenges & Considerations
Transparency & Explainability
If an agent decides to pause a campaign or shift budget, advertisers need to understand why. 2025 marks a shift toward explainable AI—platforms showing why specific decisions were made.
Governance & Guardrails
Autonomous doesn't mean unsupervised. Organizations need frameworks for:
- What actions require human approval
- Budget limits for autonomous spending
- Brand safety constraints
- Audit trails for compliance
Adoption Curve
According to IAB's State of Data 2025 report, only 30% of agencies, brands, and publishers have fully adopted AI across media campaigns—though half expect to do so by 2026.
Frequently Asked Questions
What is agentic advertising?
Agentic advertising uses AI agents that can autonomously plan, launch, and optimize advertising campaigns. Unlike rule-based automation, agents make real-time decisions, adapt to changing conditions, and execute multi-step workflows without constant human prompting.
How is agentic AI different from marketing automation?
Traditional marketing automation follows pre-defined if/then rules. Agentic AI can reason about goals, break down complex tasks, use tools (like APIs), and make decisions based on context—more like a junior media buyer than a script.
Which companies are building agentic advertising tools?
Google announced Marketing Advisor and agentic capabilities in Google Ads. Amazon launched Ads Agent for campaign planning and optimization. Startups like SynterMedia are building multi-platform AI agents that work across Google, Meta, LinkedIn, and more.
Will AI agents replace human media buyers?
Not replace—augment. Agents handle routine tasks (bid adjustments, negative keywords, reporting) while humans focus on strategy, client relationships, and creative direction. Teams that previously managed 5 brands can scale to 25 with AI assistance.
The Bottom Line
Global advertising revenue is projected to reach $1.08 trillion in 2025, with digital ad revenue growing 15% year-over-year. The companies that master agentic AI will capture a disproportionate share.
For advertisers, the message is clear: agentic AI isn't a "nice to have" for 2026—it's table stakes for staying competitive. Start experimenting now.
Try Agentic Advertising Today
Synter's Campaign IDE is an AI agent for cross-platform advertising. Chat to research, plan, validate, and launch campaigns across Google, LinkedIn, Meta, and more.