If you work in legal marketing, this may feel familiar. Expectations around content have grown steadily over the last few years, but the time and resource behind it rarely have. Most teams are expected to support more practice areas, more channels, and more internal stakeholders, often with a small team and limited capacity. That pressure is now part of day-to-day legal marketing, not an exception.
At the same time, AI tools have quietly embedded themselves into the software many teams already use. They sit inside search, email platforms, document tools, and content workflows. For most legal marketers, AI has not arrived as a single decision or initiative. It has arrived by default. The question is no longer whether AI will feature in legal marketing. The real question is how to use AI support in a way that saves time, protects credibility, and does not introduce unnecessary risk.
This post sets the foundation for our series on AI support for legal marketers. It is not about trends or predictions. It is about understanding what AI is genuinely useful for in legal environments, what it is not, and how to approach it with confidence rather than caution for its own sake.
⸻
What AI is (in plain English)
When AI is discussed in a marketing context, it usually refers to generative AI. These are tools that can produce text, ideas, summaries, and structures in response to prompts. The most common type you will encounter is a large language model. You do not need to understand how it is built to use it well, but it is helpful to understand how it behaves.
AI predicts language. It generates likely next words based on patterns in its training data and the information you give it. That is why it can produce content that feels polished and coherent. It is also why it can sometimes produce content that sounds confident while missing context or accuracy.
In legal marketing, this distinction matters. Much of the work involves shaping language rather than inventing ideas, which makes AI genuinely useful. At the same time, credibility depends on precision and AI does not understand consequence.
AI generated paragraph (plausible but risky)
Our commercial disputes team has extensive experience advising on high value, complex litigation across a broad range of sectors. Members of the team are regularly instructed in significant High Court matters and have a strong track record of achieving successful outcomes for clients through strategic, commercially focused advice.
Why this could cause problems internally
On the surface, this sounds fine. In practice, it raises several red flags:
“Extensive experience” is vague and unqualified. Someone will ask, “Compared to what, and evidenced how?”
“High value, complex litigation” implies scale and seniority that may not be consistent across the whole team.
“Regularly instructed in significant High Court matters” invites scrutiny. Which members? How regularly?
“Strong track record of achieving successful outcomes” suggests outcomes that may not be provable or appropriate to claim.
What AI is not (and why that matters)
AI is not a substitute for judgment. It does not understand professional risk, reputational nuance, or internal sensitivities. It cannot read the dynamics between clerks, practice heads and marketing teams. It cannot tell when a phrase feels overstated. It does not know which claims will prompt internal resistance, or which wording will quietly undermine trust.
This is not a limitation to work around. It is the reason AI works best as support rather than replacement. AI can help you produce language. It cannot decide whether that language should exist. In legal marketing, that distinction is critical.
Why AI matters specifically in legal marketing
Legal marketing has characteristics that make AI support particularly effective when it is applied carefully.
Accuracy is non-negotiable
In many industries, marketing language can afford to be loose. In legal matters, small inaccuracies can have an outsized impact. They can trigger internal challenge, create confusion for clients, or weaken credibility in subtle ways. Often, the issue is not that something is obviously wrong, but that it implies more than can safely be said.
AI can help teams move faster but it also introduces the risk of language that sounds reasonable without being defensible. That does not mean AI should be avoided. It means it should be used with intention.
The role is translation, not invention
Most legal marketing is not about creating ideas from scratch. It is about translating expertise into clear, accessible language. This might involve turning a technical update into something clients can understand, shaping a barrister’s experience into a consistent profile, or structuring a practice area page so it answers real questions.
AI is well-suited to this kind of work because the challenge is usually clarity and structure, not originality.
Time and coordination are constant constraints
Many legal marketing teams are small. Even larger teams often support a wide range of contributors who are understandably cautious about how they are represented.
AI can reduce friction by helping teams start faster, reduce repetition, and create workable drafts without waiting for perfect input. Used properly, this is not about lowering standards. It is about removing bottlenecks that stop good work from progressing.
The most useful way to think about AI
The most effective mental model is simple. AI works best as a capable assistant that you supervise, not as an expert you outsource to. When teams approach AI as a shortcut, quality drops and risk increases. When they approach it as support, outcomes improve.
In legal marketing, AI is strongest when it is used to draft, structure, clarify, and repurpose. It is weakest when it is asked to decide, interpret, or assert. This line should guide every use case.
Where AI genuinely adds value in legal marketing
There are several areas where AI support consistently proves useful and low-risk.
Drafting first versions
Starting is often the hardest part of writing. AI removes the blank page problem.
This might include outlines for blog posts, initial versions of website copy, or alternative introductions that improve clarity. The value is not in publishing what AI produces, but in having something concrete to refine.
Improving clarity without changing meaning
Legal writing can be dense. Marketing needs to be readable. AI can help shorten sentences, improve flow, and remove repetition without altering substance, provided the output is reviewed carefully.
A simple instruction such as “make this clearer and more client-friendly without changing the meaning” often produces useful results.
Repurposing content across formats
Repurposing is one of the most effective uses of AI support.
A single update can be reshaped into a website news item, a LinkedIn post, a newsletter summary, and supporting FAQs. This is where teams often regain time without compromising quality.
Creating consistency across profiles and pages
Over time, bios and profiles tend to drift. Length, tone, and structure become inconsistent.
AI can help standardise content while still allowing for individuality, particularly when clear templates are in place. This improves overall credibility and reduces internal back and forth.
Where teams need to be careful
AI limitations are manageable if they are understood early.
Confident-sounding inaccuracies
AI can produce incorrect information that sounds entirely plausible. In legal marketing, this might show up as an implied outcome, an overstated role, or a subtle factual shift that changes meaning.
This is why AI should support language, not be relied on for facts.
Generic tone
AI has a default voice that often feels vague or overly polished.
Legal audiences tend to respond better to calm, precise language. Human editing is essential to ensure content still sounds grounded and professional.
Governance and process gaps
Most AI-related problems arise not from the tools themselves, but from unclear expectations around use.
Without guidance, people will experiment inconsistently. That creates uneven tone and unnecessary risk. A simple internal framework goes a long way.
Will AI replace legal marketing roles?
In practice, AI changes how work is done more than whether it is done. AI reduces time spent on drafting, reworking, formatting, and repetitive variations. It increases the importance of strategy, judgement, and quality control.
Human marketers remain responsible for positioning, stakeholder management, deciding what should be published, and ensuring content is credible and appropriate.
AI accelerates output. Humans protect standards. In legal marketing, standards are central.
A practical AI maturity model
Most teams fall somewhere along a spectrum.
- At an early stage, AI use is informal and inconsistent. Output varies in quality, and confidence is low.
- As teams gain experience, AI becomes a drafting and repurposing tool with clear review steps.
- More mature use involves consistent workflows, agreed tone, and clear boundaries around risk.
- At its most effective, AI supports planning and optimisation rather than just production.
Most legal marketing teams are still early in this process. That is entirely normal. Progress comes from structure, not speed.
How to start using AI support without disruption
A sensible starting point does not require a strategy overhaul.
- Choose one task where time is consistently lost, such as rewriting bios or creating first drafts.
- Use AI for structure and language, not for factual decisions.
- Build in a simple review habit that checks tone, accuracy, and implication before anything is shared. Small changes here make a noticeable difference.
The bottom line
AI support is not a shortcut. It is a skill. Used well, it helps legal marketing teams work more consistently, respond faster, and focus attention where it matters most. Used poorly, it introduces risk and erodes trust. The difference lies in approach, not technology.
That is what this series will focus on.
⸻
Next up
The next post looks at the safest ways to use AI in legal marketing, including a simple framework teams can adopt without creating friction internally.
