
Agentic advertising is transformative for brands. By powering more efficient campaigns, fostering deeper cultural resonance, and generating lasting ROI, brand agents deliver clear wins for advertisers.

But the impact doesn’t stop there. 

When agents direct spend toward quality media, align brand messaging with cultural nuance, and free advertising professionals to focus on strategy, the benefits ripple across the entire ecosystem. The result: advertising that is intelligent, more transparent, and more sustainable.

Read on to see how agentic advertising rewards quality, reduces waste, and creates better experiences for everyone involved.

**In this blog:**

1. Why the ecosystem needs a reset
2. How agents clean up waste and restore value
3. How agents align brand values and narratives with media richness
4. How agents enhance the human ad operations experience
5. The ecosystem-wide business case

## **Why the ecosystem needs a reset**

Digital advertising has long been plagued by inefficiency and misalignment. Too much budget disappears into fraud, bot traffic, or low-quality placements. Publishers producing trusted journalism and premium content [often lose out](https://scope3.com/news/how-scope3-brand-standards-solves-for-overblocking-of-news-content) to cheaper, less meaningful inventory due to clunky brand safety solutions. Meanwhile, brands struggle with tools that reduce nuanced, crafted strategies into rigid categories and keyword blocks.

Agentic AI offers a way to reset, restoring value to high-quality media and reconnecting brands with the environments that reflect them best — making the industry and our ecosystem better as a result. 

## **How agents clean up waste and restore value**

At the heart of agentic AI is discernment. Agents analyze every impression and filter out what doesn’t deliver value, whether that’s fraudulent traffic, low-quality content, or placements misaligned with brand values and narratives. 

This clean-up work matters at scale. By removing waste, agents redirect spend to the publishers producing journalism, storytelling, and cultural content that audiences trust. The outcome is a healthier marketplace where dollars flow more directly from advertisers to meaningful, aligned, and high-quality media.

That transparency also carries an [environmental dividend](https://scope3.com/news/how-ai-agents-can-make-programmatic-advertising-carbon-efficient). When wasted impressions and excessive processing are cut out of the supply chain, emissions for ad delivery fall too. Efficiency, performance, and sustainability are all linked — and they’re all boosted with agentic advertising.

## **How agents align brand values and narratives with media richness**

Brands are not one-dimensional. They’re built through years of creative strategy, cultural resonance, and consumer connection. Media is just as rich, shaped by journalists, editors, artists, and creators. Yet in today’s system, both are often flattened into categories that strip away this vibrancy.

Agents change that. With a more sophisticated understanding of context, they can connect brands with the media environments that genuinely reflect their values. For example, instead of avoiding “all news about climate disasters,” an energy provider’s brand agent can distinguish between fear-mongering clickbait about dormant supervolcanoes, and a thoughtful piece on the ability of Bay Area infrastructure to withstand earthquakes.

This precision creates brand-media alignment that respects the creative equity poured in by both sides. Brands retain the intent and crux of their meticulously-crafted identity, and publishers are rewarded for the quality, valuable media they create. 

## **How agents enhance the human ad operations experience**

Another ecosystem benefit is how agents reshape the work of ad professionals. Too often, skilled people spend their time managing manual controls: maintaining keyword lists, setting filters, adjusting targeting criteria. It’s tedious and — at times — fatiguing, and it distracts from the higher-value work of strategy, creativity, and connection.

Agents take on those repetitive tasks. They enforce brand standards, analyze inventory quality, and make targeting decisions. And because they’re designed to be transparent and tunable, brands can choose the right balance of autonomy and human-in-the-loop oversight. 

This flexibility frees ad ops professionals, traders, and strategists to focus on what humans do best: interpreting culture, building meaningful brand narratives, and strengthening partnerships.

## **The ecosystem-wide business case**

When agents operate at scale, the benefits are felt across the ecosystem:

- **Publishers** expand revenue opportunities as spend flows back into quality journalism and high-quality content.
- **Advertisers** run more efficient, narrative-driven campaigns that deliver growth and reduce risk.
- **Agencies** empower teams to move beyond manual operations and into strategic execution.
- **Consumers** experience advertising that feels more relevant, less intrusive, and tied to media they trust.

What emerges is an ecosystem that’s commercially, creatively, and environmentally sustainable.

By cutting waste, aligning brands with quality media, and amplifying human expertise, agents strengthen the connection between advertiser intention and publisher creativity. That connection restores balance by funding meaningful content, creating better ad experiences, and driving growth in a way that benefits the entire system.

The business case for agentic AI is clear: when the media ecosystem thrives, everyone wins.

Agentic advertising is transformative for brands. By powering more efficient campaigns, fostering deeper cultural resonance, and generating lasting ROI, brand agents deliver clear wins for advertisers.  But the impact doesn’t stop there.

Agentic AI: Building a better advertising ecosystem


In agentic advertising, your brand agent is only as good as the instructions you give it. Prompting teaches your agent how to think about your values, your standards, and the kinds of media environments where you want to show up.

For brands ready to design their own brand agent, mastering prompting is critical for ensuring your agent consistently drives performance and sustainability while enforcing your standards.

## Included in this blog:

1. [What does prompting mean in agentic advertising?](#1-what-does-prompting-mean-in-agentic-advertising)
2. [What goes into an effective brand prompt?](#2-what-goes-into-an-effective-brand-prompt)
3. [What should you leave out of your prompt?](#3-what-should-you-leave-out-of-your-prompt)
4. [How do you refine prompts over time?](#4-how-do-you-refine-prompts-over-time)
5. [Why does mastering prompting give your brand an edge?](#5-why-does-mastering-prompting-give-your-brand-an-edge)

## 1. What does prompting mean in agentic advertising?

Prompting is the process of giving your brand agent clear, natural-language instructions about how to evaluate content and make media decisions. Here, you’re doing more than simply configuring a tool; you’re teaching an AI agent how to think like your brand team about what’s on-strategy, what’s off-limits, and how to interpret any gray areas.

Because prompts shape how your agent classifies and enforces standards in real time, getting them right is crucial for aligning campaigns with your brand’s voice and values.

## 2. What goes into an effective brand prompt?

An effective prompt reflects what makes your brand unique. Strong prompts should include:

- **Company and industry context** related to the spaces you operate in, how you position yourself, and who your customers and audience are.
- **Tone and values**, based in language and descriptors that capture your brand’s identity (which can be lifted from existing guidelines or other assets).
- **Content to embrace** when your agent is targeting, including topics, tones, or contexts that align with your message and campaign goals.
- **Content to avoid** for brand safety and suitability - those themes, tones, and associations that don’t reflect your brand or put your brand at risk.

A well-structured prompt also avoids vague phrases, separates positive and negative guidance, and uses complete sentences for precision.

### Effective vs. ineffective guidance:

✅ “Avoid articles highlighting product recalls in the automotive industry.”

❌ “Avoid recalls.” 

✅ “Avoid content that sensationalizes market crashes or promotes high-risk investment strategies.” 

❌ “Avoid content mentioning politics.” 

These examples show that clear, concrete language teaches your brand agent how to think in context, while vague or overly broad instructions can lead to overblocking.

## 3. What should you leave out of your prompt?

Some instructions don’t belong in your prompt because Scope3’s platform handles them automatically or through separate controls:

- **Default brand safety exclusions** block violence, hate speech, or illegal content by default.
- **Media controls** such as geo restrictions, language filters, and domain blocklists are applied separately.

Leaving these out keeps your prompts clear and focused on your brand’s unique standards.

## 4. How do you refine prompts over time?

With the Scope3 platform, calibrating an agent typically takes 1-2 weeks, during which you’ll see how it classifies real content through artifact decisioning - meaning the platform explains to you why it made a particular decision.

This feedback loop is your chance to:

- **Reclassify** edge cases and simplify concepts
- **Adjust** wording for clarity and precision
- **Strengthen** alignment by refining based on real misclassifications

Once your agent is live, you can continue to refine it as needed based on its decisions or refinements to your campaigns, but ongoing adjustments aren't necessary. This calibration process ensures your agent stays aligned with your brand's standards and goals.

## 5. Why does mastering prompting give your brand an edge?

Brands that master prompting gain a powerful advantage in the age of agentic advertising:

- **Greater precision:** Your agent enforces standards exactly as you define them.
- **More control:** You decide how your brand shows up in every impression.
- **Better performance:** Well-trained agents reduce waste and align with your KPIs.
- **Increased sustainability:** Efficient prompting reduces unnecessary AI processing, lowering emissions and costs.

Put simply, a brand agent built with strong prompts is a brand agent that delivers better outcomes.

Ready to build and train your own brand agents? Reach out to Scope3 today to discover strategies for getting started.


In agentic advertising, your brand agent is only as good as the instructions you give it. Prompting teaches your agent how to think about your values, your standards, and the kinds of media environments where you want to show up.

Why It’s Critical to Master Prompting in the Age of Agentic Advertising


In agentic advertising, a brand agent is an AI system built and trained by you to represent your brand in every media decision. These agents are designed to think like your team, apply your brand values, and work to select the right impressions and avoid the wrong ones.

Because they’re crafted, refined, and always owned by *you*, brand agents on Scope3’s platform ensure that your advertising is consistently aligned with your goals around performance, safety, suitability, and sustainability.

**Included in this blog:** 

1. What makes a brand agent different from other ad tech tools?
2. What goes into building a brand agent?
3. Why is prompt engineering essential for brand agents?
4. How does Scope3 power your brand agent?
5. What’s next for brand agents in agentic advertising?

**What makes a brand agent different from other ad tech tools?**

Most media buying tools are static, meaning users set parameters, toggle a few switches, and hope that the filters hold. A brand agent, on the other hand, is dynamic, making decisions the way your team would and consistently deploying the standards and strategies you’ve taught it.

Because you build it yourself, your brand agent reflects:

- **Your values** around inclusivity, sustainability, or risk tolerance.
- **Your strategy** by optimizing for performance, brand safety, or both.
- **Your context**, or how you want to show up in specific cultural moments, markets, or verticals.

**What goes into building a brand agent?**

Every brand agent starts with a foundation of built-in safety, automatically excluding violent, hateful, or illegal content without the need for manual blocklists.

From there, you calibrate and train your agent, shaping it to fit your brand through a human-in-the-loop process:

1. **Label sample content.** Show the agent what’s aligned and what’s not.
2. **Add natural language guidance.** Describe tone, values, and guardrails in your own words.
3. **Layer in media controls.** These can include approved or blocked domains, geographic filters, sustainability goals, and category targeting.
4. **Deploy in live campaigns.** Connect the agent as a pre-bid segment to your DSP or as a deal ID to SSPs and publishers. 
5. **Refine over time.** Reclassify edge cases, adjust prompts, and retrain as your priorities evolve.

**Why is prompt engineering essential for brand agents?**

Your agent’s decisions are only as good as the instructions you give it. The practice of crafting clear, effective inputs, or [prompt engineering](https://scope3.com/news/prompt-engineering-for-performance-and-sustainability), determines how your brand agent will interpret and apply your standards (brand safety) and stories (contextual targeting).

Scope3 makes this easy by allowing you to:

- **Use imaginal prompts** to give your agent a point of view. For example, “You are in my brand’s target audience: find inventory where my brand’s message will be most relevant for you.”
- **Refine prompts** by reviewing how your agent classifies sample content, explains its decisions, and offers feedback on inputs — then adjusting your instructions to strengthen alignment.
- **Keep prompts clear and efficient** to improve quality and eliminate the need for ongoing manual edits, saving time and lowering emissions.

It’s important to remember that prompting is never one-and-done. Instead, it’s a process of ongoing calibration that will ensure your agent adapts to new content types, market shifts, and your evolving brand priorities.

**How does Scope3 power your brand agent?**

Your brand agent lives inside the Scope3 platform, where it can access real-time data, classification tools, and performance signals. And because it deploys from the platform to your chosen destinations, it’s entirely yours in terms of design, decision-making, and adaptability.

Think of it as your always-on media buyer that enforces your standards and aligns every decision with your goals.

**What’s next for brand agents in agentic advertising?**

We’re always rolling out new features to make agent creation and refinement even easier. Start by exploring two strategies for your agent that are already delivering for brands:

- [**Brand Standards**](https://scope3.com/news/a-step-by-step-guide-to-brand-standards-what-goes-into-an-agent) defines and enforces your suitability, safety, and sustainability criteria.
- [**Brand Stories**](https://scope3.com/news/story-time-three-major-updates-from-the-front-lines-of-the-agentic-advertising-revolution)  curate environments that amplify your creative narrative.

In agentic advertising, the agent is everything. But it’s only when it’s *your* agent — built by you, for you — that it becomes one of the most powerful levers for shaping your presence on the open web and in walled gardens alike.

Ready to start building your brand’s next AI media agent? Reach out to us today.

In agentic advertising, a brand agent is an AI system built and trained by you to represent your brand in every media decision. These agents are designed to think like your team, apply your brand values, and work to select the right impressions and avoid the wrong ones.

The Most Important Part of Agentic Advertising: Your Brand Agent


**AI agents make programmatic advertising more sustainable by removing waste before bids are even placed.**

The programmatic ecosystem has long struggled with inefficiency. Too much spend flows to low-quality or high-emissions inventory. Too many auctions and hops drive up both costs and carbon. And legacy tools are too blunt to filter for performance, brand alignment, and sustainability all at once.

Agentic AI changes that. By making impression-level, content suitability-informed decisions that balance business goals with carbon efficiency, AI agents are giving media buyers and sellers the tools they need to eliminate waste in their media plans.

**What’s covered in this blog:**

1. What’s driving carbon waste in programmatic
2. How AI agents work in media buying
3. Applying carbon signals to every impression
4. Higher ROAS for buyers, better monetization for publishers
5. The road to a carbon-efficient ad ecosystem

## **What drives carbon waste in programmatic**

Programmatic’s complexity has created an invisible emissions problem. The key drivers include:

- **Over-reliance on indirect supply paths** that add steps without adding value
- **Overblocking and underblocking** that lead to missed inventory opportunities and brand safety issues, respectively
- **High-emissions inventory**, including MFA, IVT, fraud, non-viewable placements, and data-heavy creative

Buyers end up spending more ad dollars for less impact, and producing more carbon in the process. 

## **How AI agents work in media buying**

AI agents act as autonomous decision-makers embedded in the buying process:

- They operate prior to bidding, evaluating each impression against brand, performance, and sustainability criteria.
- They use **LLM-powered content analysis** to understand context and nuance beyond static keywords.
- They can incorporate **Scope3’s carbon reporting** to factor environmental impact into every decision.

Because these agents make decisions in milliseconds, they replace slow, manual, and blunt rules-based tools with dynamic, adaptable logic. 

## **Applying carbon signals to every impression**

Scope3 provides CO₂e estimates for every ad impression.

Your brand's AI agent can use this signal alongside performance metrics and brand suitability preferences to:

- Prioritize low-emissions inventory without sacrificing reach, ROAS, or other KPIs
- Avoid low-quality, high-emitting impressions that don’t drive business outcomes
- Make trade-offs such as paying a slightly higher CPM for premium, low-carbon inventory that delivers better business results

## **Higher ROAS for buyers, better monetization for publishers**

Every overblocked bid, wasted impression, and unnecessary hop in the supply chain means advertisers will waste less time, spend, and carbon. It also rewards publishers for high-quality, low-emitting content. 

Media buyers will see:

- **Reduced waste in media plans:** Target the high-performing impressions with precision.
- **Media plans that are sustainable by design**: Integrate Scope3 carbon data directly into buying decisions.
- **Transparent reporting**: Measure both performance and carbon savings in one place.

Media sellers will:

- **Unlock monetization:** Get rewarded for quality and sustainability as agents select high-quality, low-emissions inventory.
- **Avoid unnecessary blocking**: Keep relevant, brand-safe inventory available to the right buyers.
- **Improve transparency**: See why content was blocked and dispute cases of overblocking.

## **The road to a carbon-efficient ad ecosystem**

Cleaning up programmatic isn’t about adding more filters — it’s about changing how media decisions are made.

With always-on measurement and agentic decisioning, the industry can align every impression with both business and sustainability goals. That means less waste, lower emissions, and better performance for brands and publishers alike.

Agentic media buying gives us a chance to build a programmatic ecosystem that works smarter, performs better, and leaves a lighter footprint.

Ready to see how AI agents can slash carbon emissions and boost performance for your next campaign? Contact us today.

AI agents make programmatic advertising more sustainable by removing waste before bids are even placed.

How AI agents can make programmatic advertising carbon-efficient



**AI agents are changing how media buying works, making advertising smarter, more sustainable, and more aligned with a brand’s values. Here’s how.**

Agentic AI will power the next wave of digital advertising. But what does that mean in practice? How do AI agents evaluate content, make decisions, and work with the advertising ecosystem in real time?

In this post, we explain how Scope3’s Agentic Media Platform powers AI agents that evaluate every impression across platforms, publishers, and programmatic. You’ll learn how they operate technically, and what it means for advertisers and media owners.

## In this Article:
- [What are AI agents in advertising?](#what-are-ai-agents-in-advertising)
- [Where do the content signals come from?](#where-do-the-content-signals-come-from)
- [How AI agents classify and evaluate content](#how-ai-agents-classify-and-evaluate-content)
- [How AI agents make real-time decisions across the ecosystem](#how-ai-agents-make-real-time-decisions-across-the-ecosystem)
- [Why AI agents matter for media buyers](#why-ai-agents-matter-for-media-buyers)
- [Why AI agents matter for media sellers](#why-ai-agents-matter-for-media-sellers)
- [Ready to activate an agent?](#ready-to-activate-an-agent)

## **What are AI agents in advertising?**

In advertising, AI agents are intelligent, automated decision-makers that evaluate media opportunities on behalf of a brand. These agents combine brand-specific preferences — like safety, suitability, sustainability, and narrative goals — with real-time data about content and context.

In Scope3’s Agentic Media Platform, each brand or advertiser can create and deploy their own AI agent that evaluates impression opportunities before making a buy-or-skip decision. The agents integrate seamlessly across the media ecosystem, operating within demand-side platforms (DSPs), supply-side platforms (SSPs), publisher ad servers, and platforms like Meta.

## **Where do the content signals come from?**

Scope3’s classification engine starts with high-quality content inputs. To evaluate the content behind each impression, we gather signals from multiple sources, including:

- **Publisher direct**: Integrations with publisher technologies and ad servers provide access to URL-level content and multi-modal data (such as text, images, audio, and video).
- [**Scope3 crawler:**](https://docs.scope3.com/docs/scope3-crawler) Our crawler regularly scans the open web to extract page-level content and contextual cues, with frequent recrawling to keep data fresh and accurate.
- **Platform data**: We ingest content and metadata from large media platforms, enabling robust analysis across diverse content types.

Each of these sources feeds into our content pipeline, ensuring that classification is always based on real-time, accurate data.

## **How AI agents classify and evaluate content**

As content signals are gathered, brand agents evaluate them in real time.

- **Powered by LLMs**: Agents use large language models to assess the content of a page, as well as the intent, tone, and nuance. This approach improves classification accuracy and reduces over-blocking by enabling Scope3's LLM to interpret context before acting.
- **Brand-specific logic**: Each agent uses two major modules:
    - **Brand Standards** for safety, suitability, and sustainability rules
    - **Brand Stories** for targeting based on marketing narratives
- **Tokenized content**: Content is broken into artifacts (or tokens), which are scored and classified for alignment with brand objectives

The result? Media classification that understands both content and brand objectives **with unrivaled nuance*.* 

**Example**: A financial article flagged for mentioning the word “crisis” might actually be a valuable placement for a bank running a campaign around financial planning. The bank’s AI agent, by understanding the article’s nuance and framing, can classify it as safe and contextually relevant. 

## **How AI agents make real-time decisions across the ecosystem**

Agents operate across the entire ad ecosystem to make decisions at scale. Here’s how:

- **Connected to programmatic pipes**: Agents deliver real-time decisions via integrations with:
    - **DSPs** like The Trade Desk, DV360, and Amazon
    - **SSPs** like Index Exchange and Equativ
    - **Publisher ad servers**
    - **Platforms** like Meta
- **Runs within auction latency limits**: Agents evaluate and respond to each impression within the ~100ms constraint of real-time bidding
- **Same logic across channels**: Whether the impression is programmatic, direct, or in-platform, the same brand-specific logic is applied.

This infrastructure makes Scope3’s agentic model uniquely adaptive and scalable.

## **Why AI agents matter for media buyers**

For media buyers, AI agents mark a shift from manual, fragmented decision-making to consistent, intelligent, and adaptive buying – with much greater control at every step. 

Instead of juggling separate tools and rules across channels, buyers gain precise control over what qualifies as suitable, high-quality media and what goes into targeting segments. This control and logic are embedded into agents which can be deployed seamlessly and consistently across platforms, optimizing for performance, brand standards, and sustainability in real time.

Key benefits include:

- **Greater control with consistent decisioning:** Define exact criteria once, and have agents apply that same logic across programmatic, publishers, and platforms
- **Smarter, customizable targeting**: Build and reach truly bespoke audiences based on context and narrative, not just standard segments, giving you greater control over who you reach
- **Reduced carbon emissions**: Buy media aligned with your sustainability goals using Scope3’s sustainability signals
- **Higher quality, lower waste**: Avoid misaligned and low-quality inventory, as defined by your specific criteria

## **Why AI agents matter for media sellers**

For publishers, platforms, and SSPs, AI agents unlock new, more controlled ways to connect high-quality inventory with the right buyers at the right moment. By evaluating content, context, and audience signals in real time, agents can help sellers maximize yield, improve buyer trust, and surface inventory that might otherwise be overlooked.

Media sellers can expect:

- **More accurate classification**: LLM-powered agents reduce false blocks and unlock monetization for previously overlooked inventory
- **Clearer brand fit**: Agents match content to the right buyers precisely and in real time
- **Direct monetization**: Agentic media supports publisher-direct pipes—not just programmatic auctions.

In short, AI agents help quality media owners capture more demand from aligned advertisers.

## **Ready to activate an agent?**

The future of media buying is agentic — defined by real-time, AI-powered decisioning that reflects each brand’s goals, values, and carbon standards.

**Ready to see it in action?**

Explore the Scope3 Platform and build your agent today:

<a class="cta-button" href="/?authType=sign-up">Get Started</a>


AI agents are changing how media buying works, making advertising smarter, more sustainable, and more aligned with a brand’s values. Here’s how.

How AI agents work in media buying and programmatic


The systems that power digital advertising haven’t kept up with the speed and complexity of the modern media landscape. Despite years of innovation, most of programmatic still relies on rigid rules, static filters and limited inputs. For marketers and brands alike, this has resulted in operational inefficiencies, performance issues, and, ultimately, wasted spend.

[Agentic advertising](https://scope3.com/news/what-is-agentic-advertising) offers a new beginning. Rather than simply optimize outdated systems, agentic AI leverages intelligent agents that operate on behalf of brands. When used in advertising, these agents evaluate context, apply brand guidance, and make real-time decisions at the impression level, which leads to safer, smarter, and more sustainable campaigns.

So why is this shift happening now? And why are AI agents poised to take a leading role in media decisioning?

**Why can’t traditional advertising tools keep up?**

Legacy advertising tools were designed for a different era with fewer channels, simpler formats, and more stable identifiers. But today’s marketers face a more fragmented ecosystem that makes it difficult to ensure that every impression is safe and can deliver outcomes.

Unfortunately, traditional programmatic systems weren’t built for this new reality. Some of the biggest challenges with using them include:

- **Blunt brand safety tools** that rely on outdated keyword lists and broad exclusions
- **Poor media quality controls** that result in wasted spend on MFA, fraud, or low-value inventory
- **Opaque supply chains** that distort signals and prevent optimization
- **Mounting pressure to decarbonize digital media** with no clear path forward using legacy tools

Taken together, these issues cause campaigns to underperform, sustainability goals to be missed, and media teams to choose between speed, control, and scale.

**What makes agentic advertising different?**

Agentic advertising makes these difficult choices a thing of the past. As a new layer of infrastructure, intelligent software agents are trained to make decisions that align with your brand’s values, goals, and standards. These agents operate autonomously at the point of decision, analyzing each impression in real time and taking action accordingly.

For instance, you can configure agents to prioritize:

- **Performance** — bidding only on inventory that meets ROAS or reaches goals
- **Brand suitability** — enforcing tone, topic, or safety guidelines with real nuance
- **Contextual alignment** — selecting inventory based on narrative or cultural relevance
- **Sustainability** — avoiding carbon-intensive supply paths using Scope3 emissions data

Unlike static rules or filters, your agent will learn continuously, enabling your advertising approach to adapt quickly to new data, evolving standards, and changing campaign needs.

**How does agentic AI unlock better marketing outcomes?**

Scope3’s agentic media platform is purpose-built to make this shift actionable. It allows advertisers to design, train, and deploy intelligent media agents that reflect their unique campaign goals, whether those be safety, performance, sustainability, or storytelling.

These agents aren’t just limited to programmatic pipes — they’re built to traverse the entire media ecosystem. Whether it’s social platforms, direct publishers, or emerging retail and streaming environments, agents can operate wherever media decisions happen. This connectivity and fluency ensures consistent decisioning logic and campaign optimization across touchpoints.

When activating agents across programmatic and direct channels, brands and marketers can lean on Scope3 to:

- **Tailor** **agents** to campaign objectives, including sustainability, suitability, or ROAS.
- **Avoid waste and misalignment** by evaluating impressions with real-time data from the source.
- **Maintain brand integrity** by enforcing nuanced, consistent guidance across every channel.
- **Reduce environmental impact** by excluding low-quality, carbon-intensive media paths
- **Unify agent strategy** across agencies, DSPs, and publishers for greater control and scale.

Because agents designed on the Scope3 platform operate as close to the publisher as possible, they also restore those quality signals that are often lost in long supply chains, resulting in cleaner buying, better outcomes, and more transparency for every player in the media ecosystem.

**Are you ready to ride the agentic wave?**

The move toward agentic media infrastructure is well under way, brands and agencies are deploying AI agents in live campaigns across the buy and sell sides. Tools like [Brand Standards](https://scope3.com/news/scope3-allows-brands-to-build-bespoke-and-automated-standard-models-offering-enhanced-brand-protection-for-advertisers-on-meta) agents are live and ready to activate in your next campaign.

Ready to be part of the future of advertising? Get in touch today.

Legacy advertising tools were designed for a different era with fewer channels, simpler formats, and more stable identifiers. But today’s marketers face a more fragmented ecosystem that makes it difficult to ensure that every impression is safe and can deliver outcomes. Agentic advertising offers a new beginning. 

Why Agentic AI Is 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](https://akiranin.substack.com/p/what-exactly-are-ai-agents) 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](https://www.linkedin.com/posts/brianokelley_ive-been-thinking-a-lot-about-how-ai-agents-activity-7292863377008197632-uRY2?utm_source=share&utm_medium=member_desktop&rcm=ACoAABZ_dOIBnEw4FWv8XDmfKAPtSGg592XyfPE): "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](https://youtu.be/kKoIwEU8Nnw?si=VpoaPt7raI0XXJV8) 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](https://scope3.com/news/media-buyers-get-safety-and-suitability-at-scale-with-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](https://scope3.com/news/what-is-agentic-advertising). 

And it’s already taking shape.

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 

What makes AI ‘agentic’, and why it matters for the future of advertising


**In Cannes, we partnered with PwC France to host "AI-led Marketing and Sustainability Commitments," bringing together leaders from companies like LVMH, AXA, Google, UDM and PwC to tackle a critical challenge: How can energy-intensive generative AI align with ambitious climate commitments?**

**The conversation revealed clear consensus — AI is here to stay, but adoption must prioritize sustainability and responsibility, highlighting a distinctly European cultural approach that brings valuable perspective to the global AI debate.**

Brands must accept that AI is here to stay. We're far from the disappointing tech waves of previous years, like the metaverse or blockchain.

> "We can't go back," said **Marine Gissy, Global Media Lead at AXA**. "We use AI every day—even on confidential documents with our internal secured AI we are lucky to have. But now the real question is: How do we remain responsible while moving forward so quickly? The significant transformation will stem from the trust people have in AI responses, such as those from chatbots and social searches, especially during purposeful inquiries, but also from how it's built and its responsible impact on the entire ecosystem."
> 

Every brand marketer must be asking themselves how to be properly indexed on these new tools that will render traditional search methods obsolete, and how to redefine the right time, right place, right person in an agentic internet. There's no room for evasive marketers anymore. We're facing a fundamental shift that's transforming the very nature of marketing itself.

## **What drives the surge in AI adoption across industries?**

European companies are rapidly deploying AI technologies, especially in marketing and media. According to recent data shared by Mckinsey and the WFA, over 90% of global advertisers now have working groups focused on integrating AI across all functions, from supply chain to advertising.

> “This isn’t just a trend,” noted **Marion Setiey, Deputy Group International Media Director at LVMH.** “It’s a structural change. AI adoption began with individual users, not businesses, and now companies are racing to catch up. AI must enhance—not replace—human creativity. At LVMH, for example, creative decisions remain deeply rooted in brand heritage, DNA and craftsmanship. Technology and innovation are intrinsically linked to creativity. For us, it’s about keeping the human at the center.”
> 

## **Why is AI’s carbon footprint a major concern?**

While AI offers clear productivity gains — estimated at nearly one hour per day — concerns over its carbon footprint are rising. Generative AI models like ChatGPT or Gemini require massive computational resources, and thus, energy. This puts achieving climate commitments at risk. . Google, for instance, has pledged to be carbon neutral by 2030, even as it accelerates AI innovation.

> “We committed to carbon neutrality before the AI boom,” said **François Loviton, Managing Director Google Advertising France**. “We still aim for 2030, but predicting the future environmental impact of AI is complex and evolving, and our historical trends likely don't fully capture AI’s future trajectory.”
> 

Moreover, measuring emissions accurately remains a technical and collaborative challenge. Estimates of AI’s energy usage vary wildly, from 1x to 100x, due to inconsistent data sources and methods.

> “There’s a huge variance,” François added. “We need rigorous, shared metrics. Otherwise, we risk acting on misinformation. AI isn’t just hype—it represents structural change driving disruptive team upskilling gains and sustainability issues. To help drive change, we’re giving advertisers newfound insight into the emissions of ads running on our platform, inclusive of AI emissions, with Carbon Footprint for Google Ads first party reporting data.”
> 

## **How are European brands measuring sustainable AI?**

To address sustainability concerns around AI, European brands are investing in tools and frameworks to measure and mitigate AI’s environmental impact. At LVMH, this began two years ago with the creation of a proprietary tool to track media-related carbon emissions. The tool aligns with [Ad Net Zer](https://adnetzero.com/the-ad-net-zero-action-plan/)o and the [Global Sustainability Framework (GMSF)](https://adnetzero.com/wp-content/uploads/2024/09/The-Ad-Net-Zero-Global-Media-Sustainability-Framework-2024-1.pdf), but achieving accurate measurements has been difficult due to differing standards and data access issues across media partners. This collaboration will also need to extend  to generative AI. While LLM-based advertising isn’t yet fully mainstream, Marion confirmed that LVMH plans to measure its carbon footprint once it becomes viable.

> “We wanted our own methodology to account for our partners, the media vendors’ progress," **said Marion Setiey.** “Each brand in our Group now uses that tool to build their own sustainability roadmap. It is very interesting because every Maisons have different carbon emissions profile in media, depending on their very own media strategies. Now that our measurement capabilities are in place, we are in the process of accompanying the Maisons to optimize their carbon footprint, but not at the cost of their media strategy and performance of the campaigns as both should be led in parallel.”
> 

## **What role do efficiency, innovation, and regulation play?**

Despite the energy concerns, there is reason for optimism.

According to François Loviton, advancements in prompt optimization have already reduced the energy cost per prompt by 80%. Google is also exploring ways to serve user needs without resorting to the most resource-intensive AI processes. The push for greener AI also intersects with economic imperatives.

Serving AI-powered ads at scale, for example, may not be financially viable unless energy efficiency improves. At a regulatory level, the conversation acknowledged Europe’s leadership in proactive governance but cautioned against overregulation.

> “If someone just wants the weather, there’s no need to use a large language model,” he noted. “Traditional search is faster, cheaper, and greener. It’s not just about sustainability—it’s also about making AI affordable to run,” he emphasized. “We’re already regulating something that’s barely off the ground,” **warned Jean-Luc Chetrit, General Manager at the French “Union des Marques”:** “If we move too fast, we risk slowing down European innovation.”
> 

## **How Is the ad industry building a responsible AI future?**

Ultimately, striking a balance between innovation and environmental responsibility requires a shared framework. That’s why a coalition of European firms — including Bouygues, Nestlé, and LVMH — [recently co-authored a guide for deploying responsible generative AI.](https://uniondesmarques.fr/l/en/library/download/urn:uuid:a445e1fc-39d4-4d93-840a-c873a5a5d816/guide+ai+for+good+union+des+marques+-+short+version.pdf?format=save_to_disk)

> "We built a set of 23 best practices, covering everything from sovereignty and diversity to carbon impact," **said Jean-Luc Chetrit.** "It's about asking the right questions—and updating the answers constantly. This highlights the governance challenge companies face: how to integrate all departments to effectively manage AI strategy, ensuring brands develop value-creating innovations within a defined framework before sharing them with stakeholders across our initiatives."
> 

Above all, the human element must remain at the core of AI strategy.

> “We believe strongly in test-and-learn,” **Marion Setiey added.** “But creativity, heritage, and human must always stay central. We must maintain a consumer-centric perspective, prioritize people first in all AI and sustainability discussions, and aim for better performance through a more for less approach. The future of advertising lies in balancing technological advancement with human expertise & creativity and environmental responsibility.”
> 

The European advertising industry is rapidly evolving as AI opportunities and growing demand for sustainable advertising reshape the sector, creating new complexities and choices. As the "digital burden" escalates , advertisers can already leverage a variety of strategies to reduce their carbon footprint through deploying agentic solutions, partnering closer with their media agencies, or increasing internal resources.

> “Regardless of how brands go about putting sustainable AI and advertising into practice, what brands need is trust above all.” said **Eleonore Ogrinz Marketing & Media Director Europe at PwC.**
> 

The opportunity lies in AI's ability to deliver on plans that reduce carbon footprint while achieving stronger consumer resonance and better ROI. [AI](http://roi.ai/) [makes sustainability goals more accessible](https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html#ai-will-be-a-value-play--and-a-boon-for-sustainability).  Despite advances in technology, decisions will continue to be made by humans, supported by experts who help advertisers navigate their ever expanding list of choices.

> “The human element remains crucial as we transform our organizations and adapt operational models at unprecedented speed. We must be careful not to create 'digital overload' and stay sensitive to the increased demands AI places on our colleagues and partners.”
> 

## **Key Takeaways:**

- European companies like LVMH or AXA are leading responsible AI adoption by aligning technology with sustainability goals.
- Emissions tracking tools are emerging but still face data standardization challenges, while efficiency innovations reduce AI's energy footprint.
- Regulation must balance supporting innovation without stifling technological progress.
- Human control and oversight remain critical, with humans managing strategy and decisions while AI provides the execution layer.
- Europe's cautious, collaborative approach could become the global model for sustainable AI development.

European companies are leading the charge by aligning AI adoption with climate commitments. Brands can balance AI media buying and sustainability by adopting energy-efficient AI practices, using emission-tracking tools, and building responsible frameworks that prioritize environmental impact without compromising innovation.

How Can Brands Balance AI Media Buying With Sustainability Goals? The European Example


AI is unlocking new levels of creativity, speed, and performance across the marketing industry. From copywriting and creative production to audience targeting and performance optimization, generative AI is helping teams move faster and achieve more.

Each of these applications relies on underlying AI models that are resource intensive. They are powered by cloud-based data centers, which are themselves powered by a range of energy sources including fossil fuels. As AI usage grows, so, too does its energy footprint, making it crucial for marketers to understand the carbon and water cost associated with the tools they rely on.

That’s why Scope3 collaborated with 55 and The Brandtech Group on a new white paper exploring the carbon impact of generative AI in marketing. The paper introduces a high-level methodology to estimate the emissions generated by common AI use cases like text and image generation.

We believe this kind of transparency is vital. 

As AI becomes deeply embedded in day-to-day marketing operations, it’s clear that static calculators and one-off estimates are positive first step. Next, the industry needs to invest in ongoing, activity-based measurement that tracks emissions and waste across tools, teams, and outputs, just like we already do with advertising.

That’s what Scope3’s AI measurement platform is built to do. 

Our goal is to make the environmental cost of AI visible, measurable, and optimizable from the moment you start generating. We do this using a robust methodology grounded in model-specific compute estimates and integrated across creative and workflow tools.

When sustainability is built into AI from the start, it improves efficiency, reduces waste, and unlocks smarter decision-making for businesses. That’s the path to sustainable growth.

This white paper is an important first step in laying the foundation for a more transparent, sustainable approach to AI adoption. But to avoid locking in wasteful practices, we must go further.

AI is a powerful engine for growth. By scaling it sustainably, we ensure that its benefits can be realized by businesses and individuals alike.

Download the white paper [here](https://sustainability.thebrandtechgroup.com/), and learn more about Scope3’s approach to AI measurement [here](https://info.scope3.com/ai).

Scope3 collaborated with 55 and The Brandtech Group on a new white paper exploring the carbon impact of generative AI in marketing. The paper introduces a high-level methodology to estimate the emissions generated by common AI use cases like text and image generation.