What makes AI ‘agentic’, and why it matters for the future of advertising
As excitement builds around agentic advertising and AI’s broader role in the industry, there’s also a lot of confusion. One of the biggest knowledge gaps is around “agentic” AI — what it really means and why it matters.
Having a clear, and widely recognized understanding of the concept is critical, especially given our vision for the future of advertising: agents will be essential to the foundation of the next generation of adtech responsibly and intelligently.
Here’s how we define the term and why Scope3 is committed to leading the agentic future.
What is an agent
A large language model (LLM) like GPT-4 can generate text. It can answer questions, summarize documents, and simulate conversation. But an LLM can’t take action in the world. It can’t launch a campaign, optimize a bid, or enforce a brand’s safety and suitability standards without human involvement.
An agent, by contrast, is designed to:
- Reason (understand goals and constraints)
- Plan (sequence steps to achieve a goal)
- Act (execute tasks autonomously in real systems)
As Aki Ranin put it in a particularly elucidating blog post: “Agents are what takes us from you using AI to AI running your company.”
Or in Scope3 CEO Brian O’Kelley’s words: “Agents are what take us from AI on top of existing tech to building tech on top of AI.”
Why agentic AI is different
Agentic AI moves intelligence from suggestion to execution. It enables systems that:
- Evaluate opportunities
- Make tradeoffs
- Enforce brand-specific or regulatory rules
- Learn and improve through real-world feedback
Without the ability to act, AI remains a passive tool. With agentic AI, infrastructure becomes dynamic: able to adapt, optimize, and govern according to human-defined standards.
This transformation isn’t about chasing efficiency alone. It’s about building resilient systems.
As Ruben Schreurs, Group CEO at Ebiquity, shared at Scope3’s Landscape event, autonomous systems must be guided carefully to prevent instrumental convergence, where an agent pursues goals in ways that are surprising, harmful, or misaligned with human intent.
Scope3’s approach to building agentic products involves embedding guardrails like common sense brand safety standards, sustainability mandates, and compliance frameworks directly into agentic decision-making, alongside a brand’s own suitability needs, ensuring every outcome reflects what our individual clients value most.
The agent landscape: assistants, orchestrators, operators, and specialists
The term “agent” is being applied to a wide range of technologies. We’ve mapped out four major types:
- Assistant: Chatbots embedded in apps to answer questions or guide setup
- Orchestrator: Agents that assemble steps across multiple tools to complete a workflow
- Operator: Agents that simulate human clicks and actions in browsers and apps
- Specialist: Domain-specific agents trained to achieve complex goals autonomously
At Scope3, our focus is on helping partners build and deploy specialists, or intelligent agents that:
- Make autonomous decisions
- Take real-world actions across media and marketing systems
- Adapt to changing conditions and evolving data
How this changes advertising
Advertising demands systems that can think, act, and adapt at scale. The industry can’t meet this need by layering AI onto legacy workflows.
The future of media buying will be shaped by agents that:
- Enforce brand standards, sustainability criteria, and regulatory rules → read more about Brand Standards!
- Optimize media buying decisions in real time
- Govern supply chains for integrity and quality
- Continuously learn and refine based on real-world outcomes
Scope3’s Agentic Media Platform is built specifically for this shift, providing brands, agencies, and platforms with intelligent, aligned, and actionable AI.
The next era of advertising won’t rely on static systems with occasional AI assistance. It will be dynamic, agentic, and built for change. Find an explainer on agentic advertising here.
And it’s already taking shape.
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