What Is an Agent and Should You Build One for Marketing Review?

Two years ago, most legal and compliance teams treated AI with polite skepticism. Today, tools like Claude for Legal, Harvey and others handle contract review, research, and summarization well enough that using Claude for legal compliance work barely raises an eyebrow anymore. This growing comfort with AI is probably why someone on your team has started asking whether AI can review marketing content as effectively as it reviews contracts or summarizes filings.

With reduced headcount and increased content production, an AI agent for marketing compliance- something that acts on its own across multiple steps, without you checking each one- looks like the obvious answer. Marketing wants this too, for a different reason. Self-serve review means fewer bottlenecks, more insight to not make the same mistakes again, and less waiting on legal's availability. Both sides are pushing toward the same outcome from different pressure points.

Why AI Agents Are On The Table Now

AI usage among legal professionals jumped from 19% to 79% in a single year, per a 2024 Legal Trends Report. Most of the profession is bringing legal ops AI tools into daily use for the first time.

At the same time, legal teams are doing more with less. Thomson Reuters' Legal Department Operations Index found that 79% of corporate law departments report rising matter volumes, while 67% report flat or shrinking attorney headcount. The study also found that roughly three-quarters of a law firm’s billable tasks could potentially be automated with AI. Together, those findings help explain why legal teams are increasingly open to automation, especially for repetitive review work. Marketing content review automation looks appealing because it promises relief without adding headcount.

The Version Of "Agent” Worth Being Precise About

An agent doesn't simply draft or summarize and hand the output back to you. It takes a goal and acts on it in sequence, without approval at each step. For content review, the important distinction is whether the system supports a reviewer or starts making decisions in their place. The tools you use today for researcher first-draft summaries still keep a human between the output and anything happening in the real world. For marketing compliance, the question is where automation should stop, and human judgement should begin.

As Antonia Walters, Blee's Head of Legal Engineering and Operations, put it in a recent webinar: "The question is not what is this tool going to flag. The question is how does this tool fit into the way our legal and marketing teams actually do their work."

When it comes to content review at scale, the appeal is straightforward: an autonomous system can speed up early review by flagging issues without waiting on a person at every step. But before it acts on a bank’s co-branded affiliate campaign or rate-and-fee disclosure, the bar should be much higher.

Why Marketing Compliance Carries Different Stakes Than What You're Already Using AI For

Reviewing a contract and reviewing marketing content for regulatory compliance can look similar on the surface because both involve reading text against a rule set and flagging problems. In regulated industries, though, compliance depends on context. A claim may be technically accurate and still be misleading because of how it’s presented or what disclosure sits beside it. The system has to apply regulatory frameworks alongside your firm’s own policies and approved language, context a general-purpose agent lacks by default. Someone still has to encode it and keep it current as guidance shifts. 

Context is only part of what’s missing. The system also needs to apply those policies consistently, route work to the right reviewer, and preserve a clear record of how content changed, why it was approved, and which rules informed the decision. None of that comes from a better model. It comes from infrastructure built for the job. 

This isn't a hypothetical risk. In September 2024, the SEC charged nine registered investment advisers for Marketing Rule violations, mostly untrue or unsubstantiated claims and missing disclosures around testimonials and third-party ratings, resulting in $1,240,000 in combined civil penalties. None of this is unique to securities regulators, either. The FTC has stated there's "no AI exemption" from existing consumer protection law as part of its Operation AI Comply enforcement effort, a reminder that FTC marketing compliance obligations don't disappear just because AI produced the claim.

The disconnect between contract review and marketing review isn’t just about whether someone catches an error afterward, but what happens once content is released. A missed clause in a contract can usually still be corrected through negotiation or amendment. A missed compliance issue in marketing content can reach customers or partners as soon as it’s published, creating exposure before the compliance team can act. 

And the mistakes worth worrying about aren't always outright lies. In a January 2026 disciplinary action, FINRA fined TPEG Securities $175,000 for using aggregated performance metrics that masked how individual deals actually performed, a violation of Rule 2210's standards for communications with the public. The numbers were technically accurate, but they were misleading once you saw the context. 

A general-purpose agent doesn’t automatically have the regulatory and company-specific context needed to make that distinction. It may confirm that a number is correct while still missing how its presentation could mislead, because it lacks the context to know the difference. 

Legal teams already seem to sense this distinction. Research on how lawyers deploy AI found trust was earned most in tasks where a human still reviews the output. In practice, this means the key line is between using AI for support and allowing it to make final decisions.

Who Owns The Agent When The Rules Change

Even setting the trust question aside, an agent isn't a one-time build. Building one means more than writing prompts. Ownership extends to the workflows, policy retrieval, testing, monitoring, and updates that keep the system reliable over time. Legal review automation is often pitched as a clean, one-time build. Teams spend far less time planning for that ongoing responsibility. 

Regulations change, and enforcement priorities shift, but the bigger driver is often closer to home. Your business changes every week: new products, updated campaigns, approved claims, revised disclosures, and evolving approval workflows all need to stay current too. Someone has to own keeping the agent's rules current against all of that, and someone has to own what happens when it flags something wrong, or worse, misses something. 

That responsibility lands on a team that's already stretched by the same volume and headcount pressure driving this conversation in the first place. Building a compliance-specific agent in-house means owning a new internal product. Your team has to keep it current and be ready to defend how it works during an examination, while the existing review queue continues to grow. Marketing review workflow automation is only as good as whoever keeps updating the workflow.

What Purpose-Built Compliance Infrastructure Needs To Provide 

The alternative isn’t to stay on spreadsheets and email while marketing content volume keeps climbing. Any better system also needs to look beyond the formal review queue.

The FCA reported that financial promotions withdrawn or amended rose to nearly 20,000 in 2024, a 97.5% increase over 2023, with finfluencer activity specifically named as a growing enforcement priority. Partner, influencer, and employee content may be published without entering the normal submission process at all. Shadow content compliance becomes difficult here because agents built only to review submitted assets do not solve the visibility problem. Purpose-built infrastructure also needs to monitor content after publication, including partner and influencer channels outside the formal review process.

A general-purpose agent built from scratch probably isn't the answer. Purpose-built systems for AI marketing compliance, like Blee, are designed around the realities of this work. They apply the relevant regulatory frameworks alongside your own policies and risk tolerance. They also check content against approved disclosure language and review the formats marketing actually uses. Reviewers keep control of the final decision, while the system preserves a defensible record and monitors content beyond the formal review queue. For marketing, this also means less waiting. Low-risk content can move through faster without requiring a reviewer to handle every submission manually.

Just as importantly, these platforms preserve the reasoning behind each decision. Reviewers can follow the full decision path, from the initial flag through to final approval. The system improves through reviewer feedback without removing legal or compliance judgment from the process.

AI Agent vs Compliance Platform

The question shifts from “should I build an AI agent for compliance?” to “do we have the infrastructure to maintain meaningful oversight of marketing content at the volume we’re now producing?” 

When the choice is framed as an autonomous agent versus purpose-built compliance infrastructure, the platform is often the more practical option. An agent can be one component of a system, but the harder part is everything built around it - the policy management and reviewer workflows to the monitoring this piece has already pointed to. Agents can be useful technology. In this case, using one also means taking ongoing responsibility for the domain-specific context it depends on.

A homegrown agent asks your team to take on an ongoing software ownership role in a domain where a missed issue can become a missing disclosure or a stat stripped of context in published content. It’s a different kind of failure than a software bug your team can patch after the fact. 

Before committing to an internal build, confirm whether purpose-built infrastructure  already covers:

• The regulatory frameworks and audit trail your review process depends on
• Reviewer controls that keep the final decision with your team
• Shadow content monitoring beyond the formal review queue
   

If it does, your reviewers can spend less time on repetitive checks and more time on the judgment calls that require their expertise. Explore Blee's approach to marketing compliance review. 

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