When it comes to AI, the hype can take a long time to settle into a sober reality. When we first started seeing AI-generated images, many were quick to declare the graphic designer a relic of the past. The same was true for marketing copywriters, but I’m still around. Or am I?

The reality is that AI is not yet able to maintain a visual brand identity or write content that doesn’t feel like it was written by a bureaucrat trying to put his children to sleep. It may one day soon create on-brand visuals and thrilling stories, but today is not that day.

What Is Agentic AI And How Does It Differ From Traditional AI?

Agentic AI is not just a tool but also the tool operator itself. It’s an autonomous agent that can work out the steps required to achieve a goal, working independently like a human employee rather than simply responding to prompts.

See more definitions in our Commerce Media Marketing Glossary >>

Agentic AI represents a fundamental shift in how businesses approach automation and decision-making. Unlike traditional AI systems that require a human to boss it around, agentic AI can plan, execute, and adapt strategies autonomously. You can give it a job, leave it alone, and expect results. At least, that’s what the marketing promises, and we all know what they’re like (I jest).

This evolution signals a large departure from generative AI, which excels at content creation but requires a living human for strategy and next steps. Agentic AI combines the creative capabilities of generative systems with the kind of independent decision-making that can manage end-to-end workflows.

Agentic AI is one of the latest innovations in AI, and it is not just a tool but also the tool operator itself. It’s pitched as an autonomous agent that can work out the steps required to achieve a goal. You can give it a job, leave it alone, and expect results. The agent can work independently just like a human employee—well, the good ones anyway

How Can Agentic AI Address Commerce Media’s Scale Challenges?

The timing of agentic AI’s arrival could be good news for retail media. Advertisers and marketing leaders are running into numerous bottlenecks that largely revolve around the complexity of the retail media network (RMN) landscape. With a growing number of RMNs, each with its own specifications and measurement standards, brands face mounting challenges:

Current Commerce Media Pain Points

  • Creative Production Bottlenecks: Brands are overburdened with creative production requirements while struggling with a lack of transparency over performance across networks.
  • Measurement Inconsistencies: Without a standard for measurement, advertisers are often left comparing apples to oranges, or at least Royal Gala to Granny Smith—apples on opposite ends of the sweetness spectrum.
  • Platform Fragmentation: While Amazon represents the majority of retail media ad spend, numerous other RMNs still offer access to valuable customer segments for brands seeking growth opportunities beyond Amazon’s green pastures.

Media Buying With Agentic AI

We’re not at the point where agents can buy for us, but the agency Monks has been experimenting with their media mix modelling tool, Clarity. With this currently unreleased platform, buyers could potentially rely on thousands of AI agents to predict the best-performing media buys.

This strategy would theoretically take much of the nerve-racking guesswork out of buying across RMNs, enabling marketers to make data-driven decisions based on real-time market trends and consumer behavior insights. The goal is creating a seamless brand experience that optimizes campaign performance while reducing the manual work which nobody likes.

Tools For Improving Creative Compliance

Why Creative Approvals Slow Down Campaign Success

Creative approvals are easily one of the biggest bottlenecks in commerce media. Brands must navigate their own brand guidelines and satisfy the requirements of the retail media network. It’s enough to make a human graphic designer scream, and a generative AI platform to… I don’t know, make more computer noises.

The Challenge: As a result, many campaigns are being slowed down by creative failing compliance tests or by approvals requiring more consideration from the retailer. As commerce media opens up to more complex ad formats, such as video and display, the approval process is bogged down even further.

How AI-Driven Solutions Address Creative Compliance

In response to this problem, Jivox launched its own agentic AI tool, the Creative Compliance Checker. This feature is part of Jivox’s retail media platform, DaVinci IQ+. The new feature predicts whether your creative will be approved or not. Brands and advertisers simply select which RMN guidelines they are using, and the platform will determine a score based on the number of criteria met by the creative.

How It Works: Brands and advertisers simply select which RMN guidelines they are using, and the platform determines a compliance score based on the number of criteria met by the creative. This AI-driven automation reduces the risk of campaign delays and helps ensure faster time-to-market.

Business Impact: The Creative Compliance checker won’t guarantee retailer approval, but it will improve the odds. Jivox is using continuous learning from data and feedback to improve the tech even further, creating greater efficiency in the approval process for businesses across all commerce channels.

What Role Does Agentic AI Play In Creative Production?

Creative Production With Agentic And Generative AI

As with media planning, numerous companies are experimenting with agentic AI in creative production. Monks for example, collaborated with Nvidia to produce a 30-second spot using AI agents for much of the process. Using only a client brief, the agents created a script and mood board to be used for the rest of the production.

Autonomous Creative Roles: Each agent took on a comparable creative role normally occupied by the flesh (humans), such as the director of photography. This approach demonstrates how intelligent systems can handle complex creative decision-making while maintaining brand consistency.

The Future Of Hyper-Personalized Experiences

Adobe is similarly developing agentic AI tools to accelerate the creative process. Agents will theoretically contribute creative ideas and help with execution. They’re also pushing agentic AI to create one-to-one customer experiences.

Customer Journey Optimization: This technology enables brands to create personalized content at scale, across channels, improving customer engagement and potentially increasing conversions through more relevant, contextual interactions.

Bringing Agentic AI Back Down To Earth

Let’s Get Real About What Agentic AI Can’t Do (Yet)

Is agentic AI ready for mainstream commerce adoption? While the idea of cutting down creative production time may be exciting for some, agentic AI has some major hurdles to overcome. Brands still have trust issues with generative AI, which agents depend on for their output.

  • AI Reliability Issues: They’re concerned about AI hallucinations and copyright issues that are still playing out in the courts.
  • Budget Risk Management: We’re also not quite at the point where agentic AI can take over your commerce media buys. Can you imagine leaving your campaign budget in the virtual hands of an agentic AI team? If something goes wrong, humans will ultimately have to take responsibility. It’s still best practice to treat agentic AI as a helpful assistant and not as a worker replacement.

What Are The Most Promising Agentic AI Use Cases For Commerce?

Grounded Applications Delivering Real Business Value

However, there are more grounded and uncontroversial use cases showing immediate business potential: 

  • Creative Compliance Automation: The compliance checker will help you avoid approval headaches that bog down retail media campaigns, enabling faster campaign launches and reduced operational costs.
  • AI Shopping Assistants: Agentic AI shoppers can also help consumers find the best product for their needs. 75% of retailers believe that they will be essential for having a competitive edge in 2026.
  • Recommendation Engines: Advanced product recommendations based on customer behavior analysis can improve customer loyalty and drive repeat purchases.

Why These Applications Work Today

In both cases, the problems agents are solving can be addressed with approximations, like a score or recommendation. They don’t require something as specific as an ad meeting brand requirements, making them more reliable for immediate implementation.

The Future Of Agentic Commerce: What Marketing Leaders Should Expect

Preparing For An AI-Driven Commerce Landscape

There will be a day when agentic AI is the best co-worker you’ve ever had, but for now, more modest use cases will save you time, money, and headaches with commerce media bottlenecks.

Strategic Approach: Marketing leaders should focus on identifying specific areas where agentic AI can add immediate value—such as automating repetitive tasks, improving customer interactions, and streamlining approval processes.

Growth Opportunities: As the technology matures, businesses that embrace these intelligent systems early will be better positioned to capitalize on the shift toward automated, AI-driven commerce experiences.

The key is finding the right balance between automation and human insight, ensuring that agentic AI enhances rather than replaces the strategic thinking that drives successful commerce media campaigns.

Key Takeaways For Commerce Media Success: Your Agentic AI Game Plan

Start with What’s Driving You Crazy: That weekly creative compliance disaster where someone inevitably mutters “why is this so complicated”? Perfect starting point. AI-driven creative compliance checkers can turn that three-hour ordeal into something you actually finish before lunch. But keep the big-picture decisions where they belong: with humans who understand your brand.

What Your Future Self Will Thank You For: Agentic AI in commerce media is coming whether we’re ready or not. Clean up your data systems now because messy data and AI go together about as well as oil and water. Organized content and trained teams will be the difference between thriving and scrambling to catch up later.

Reality Check Time: Agentic AI isn’t going to solve all your problems while you sip coffee and doomscroll on the internet. Think of it more like having a brilliant sous chef who can perfectly dice vegetables and follow recipes but still needs you to decide if the dish actually tastes good enough for customers.

The brands winning this game aren’t throwing money at every flashy new tool. They’re the ones who pick their battles wisely and remember that great campaigns still need someone who gets why people buy things in the first place.