65. Agentic Autonomy – Agency Version

This is the reality of agentic automation in advertising. In simple terms, agentic automation refers to AI “agents” that can make decisions and take actions independently, without needing step-by-step human instructions. These agents use advanced AI (including large language models and other smart algorithms) to analyze data, understand goals, and execute tasks autonomouslyuipath.com. For professionals in the advertising business, this technology promises to handle the busywork and let human teams focus on big-picture strategy and creativity.

So what is the difference?

An AI agent is a software system that autonomously performs tasks on behalf of users or other systems. These agents can perceive their environment, make decisions, and act to accomplish specific tasks.

Agentic AI refers to AI systems designed with a high degree of autonomy, enabling them to make decisions, take actions, and pursue complex goals with minimal human intervention. These systems integrate various AI technologies to operate independently, adapting to changing environments, learning from experiences, and accomplishing goals.

At its core, agentic automation is about moving beyond traditional marketing automation into autonomous decision-making. Traditional automation might schedule posts or adjust bids based on set rules.

Agentic AI goes further – it can “think” through complex scenarios in real time. For example, a conventional ad platform might automate bidding, but an agentic system could recognize a new trend in customer behavior and launch a tailored mini-campaign on the fly. In other words, it’s not just following rules; it’s figuring out the rules as it goes.

This means the AI can react to events (like a spike in website traffic or a competitor’s promotion) and take action immediately, often faster than a human team could.

For advertisers, caring about agentic automation means staying ahead of the curve. It’s the next evolution of AI in marketing, allowing campaigns to be more responsive, personalized, and efficient. As one industry article put it, we’re moving from using AI as just a tool for number-crunching to relying on it as “a true collaborator” in our marketing efforts. In practical terms, that translates to campaigns that practically run themselves (under human supervision), and outcomes like better ROI and more engaging ads.

One of the biggest changes agentic automation brings is in day-to-day workflows. Tasks that used to take days or weeks of human effort can be compressed into hours or even minutes.

Consider the process of launching a new ad campaign. It typically involves:

• Researching the audience;

• Creating content;

• Setting up targeting; and then

• Monitoring and adjusting once live.

Agentic AI can handle many of these steps end-to-end. It can:

• Draft ad copy and design variations;

• Set up the campaign across channels; and

• Start monitoring performance immediately.

In fact, modern AI agents can plan, launch, and optimize campaigns with minimal oversight, acting as “self-directed, always-on assistants” for marketing teams.

Campaigns that once took weeks to coordinate might now go live in a day. For example:

• An agent could identify a new trending topic in the morning.

• Have relevant ads targeting that trend by afternoon.

• The workflow shifts from manual execution to AI-managed automation, with humans providing high-level direction.

In short, the mundane chores – checking metrics, tweaking budgets, copying content into multiple formats – can be offloaded to AI, freeing up people to focus on strategy and creative thinking.

Agentic automation doesn’t just set up campaigns quickly; it makes them smarter over time.

Continuous optimization is a hallmark of these AI agents. Unlike a “set it and forget it” approach, an autonomous agent keeps watching performance data every minute and adjusts accordingly.

The AI can redirect budget toward the winner by afternoon.

The agent can refine the content or shift spend to another channel in real time.

One practical example is in A/B testing and multivariate testing. Traditionally, marketers would test two versions (A and B), wait for results, then manually pick a winner – a process that could take weeks.

Agentic AI can test dozens of variations simultaneously and adjust on the fly. It observes how real users respond and immediately allocates traffic to the best-performing content, without waiting for a human analyst. If variation “C” starts outperforming A and B, the agent will seamlessly shift focus to C and even spin up new variations to further improve results.

Figure: An AI agent orchestrating A/B and multivariate testing. The agent automatically refines and adjusts different ad versions (A, B, C, D) based on real-time user feedback, continuously zeroing in on the top-performing creative and strategy.

The result is an always-improving campaign. Automated campaign optimization means an AI agent can manage bids, ad placements, and even creative tweaks 24/7.

Agentic automation in advertising isn’t just theory – it’s already being deployed by forward-thinking companies and platforms.

Salesforce Has introduced a feature called Agentforce to bring AI agents into its marketing cloud. These agents can orchestrate campaigns, handle personalizations, and even come with an “Atlas” reasoning engine that plans and executes tasks autonomously. warmly.aiwarmly.ai. This is a major player betting on agentic AI to transform how campaigns are run within large organizations.

There are also startups and specialized platforms focused on agentic automation for advertising. Warmly is one such platform. Its AI agents autonomously launch multi-channel campaigns—across ads, emails, and more—based on real-time buying signals. They dynamically adjust audience segmentation, engage website visitors via AI chatbots, and can identify high-value prospects overnight, initiating tailored outreach without human intervention.

On the creative side of advertising, tools like Omneky are employing agentic AI to automate ad creation. Omneky’s platform uses AI to generate a variety of ad creatives (images and videos with different text, styles, etc.) and test them across social media and other channels. It can even create product imagery with AI, which cuts down the need for photo shoots. The agent in this case ensures that the ads remain on-brand while experimenting with countless creative variations to see what resonates best with each audience.

Even the big digital ad platforms like Google and Meta (Facebook) are moving toward agentic-like capabilities. They have been using AI for years in features such as automated ad bidding, budget optimization, and responsive ads that mix and match creative elements to fit the user. What’s changing now is the level of autonomy. Google’s latest campaign types (for instance, Performance Max) let the AI decide where to show ads, who to target, and which ad creative to use.

Similarly, Facebook’s Advantage+ campaigns use AI to determine the best combinations of creative and audience for your goal. These platforms aren’t fully “agentic” in the sense of the AI doing everything independently, but they illustrate the industry trend: more reliance on AI to handle the nitty-gritty decisions in campaign management.

Finally, consider the example of Finnish telecom company Elisa, which built a customer service AI agent named Annika. While not an ad campaign tool, Annika autonomously handled over 560,000 customer clients’ inquiries This showcases the power of agents in managing large-scale interactions. Translate that to advertising, and it’s easy to imagine AI agents managing millions of ad impressions and customer touchpoints autonomously.

The rise of agentic automation is reshaping roles and strategies in the ad industry. Workflows are shifting from manual to AI-augmented. Instead of media buyers adjusting bids all day, an AI handles it, and the buyers focus on strategy and creative coordination. Campaign managers start to act more like supervisors of AI agents – setting goals, defining guidelines and brand safety limits, and then overseeing the AI’s work.

As a result, advertising teams can run more campaigns across more channels than ever before, because their AI helpers scale their capacity. One recent analysis predicted that by 2028, 1 in 5 marketing roles might be held by an “AI worker”, with human staff concentrating on strategy, creativity, and ethics. While that stat may sound a bit futuristic, it highlights a clear direction: routine tasks in campaign creation, management, and analysis are increasingly handled by AI agents, and humans are moving to higher-level functions.

Another big change is in campaign outcomes and performance expectations. With continuous optimization and data-driven targeting, advertisers are seeing improved metrics. More personalized ads can lead to higher engagement. Always-on optimization can yield better ROI since the AI is quick to cut wasteful spend and reallocate budget to what works. Moreover, marketing becomes more agile – if a new trend or crisis emerges, AI can adapt the messaging or strategy in minutes, which is crucial in today’s fast-paced digital environment.

Of course, adopting agentic automation comes with considerations. Companies need to ensure they maintain brand voice and ethics in what the AI is doing. Proper guardrails are necessary so an autonomous agent doesn’t, say, overspend or target the wrong audience by mistake.

The good news is that tools are evolving to include transparency (so you can see why the AI made certain decisions) and controls to tweak the AI’s behavior.

Agentic automation is ushering in a new era for the advertising business. It’s making marketing more efficient and data-driven, but also more creative and personalized. By entrusting routine and reactive tasks to AI agents, advertisers can focus on strategy, storytelling, and innovation – the things humans do best. The technology is still evolving, but even now we see practical benefits: faster campaign launches, smarter optimizations, richer personalization, and teams that can do more with less.

And while humans are still very much in charge, the partnership between marketers and intelligent agents is proving to be a game-changer.

Sources: infillion.com, warmly.ai, accelirate.com, blogs.idc.comblogs.idc.com, nogood.io