Artificial intelligence has been part of financial services marketing much longer than you might think. While chatbots and predictive analytics have been around for a number of years, content generation tools are newer to the scene. AI has quickly become an enticing tool for time-poor marketing teams across banks, forex brokers and fintechs. Three years after the launch of ChatGPT, and other engines like Google’s Gemini, and Midjourney, regulators are finally sharpening their focus on AI usage. This is particular true for financial brands using AI in their promotion to traders, investors and clients. In this article looking at how you can use AI in financial services marketing, while remaining compliant and on brand.
The Main AI Engines You Should Know
When people talk about “AI” in marketing and content creation, they’re usually referring to generative AI. That’s models that can create text, images, audio, or video from simple prompts. Most mainstream AI tools your marketing team will touch, from HubSpot’s AI to Canva’s Magic Write or Grammarly’s AI, are powered by one or more of these core engines or built on open-source versions of them.
The main engines behind these tools are developed by a few big players:
OpenAI (ChatGPT, GPT-4, GPT-4.5, GPT-3.5)
- What it does: Large language models (LLMs) trained on vast internet data to generate human-like text.
- Used for: Drafting emails, writing blogs, summarising documents, coding assistance, chatbot development.
- Where you see it: ChatGPT, Microsoft Copilot in Office products, integrations in thousands of SaaS tools.
Google DeepMind (Gemini, formerly Bard)
- What it does: Google’s family of advanced LLMs and AI tools for text, code, and research assistance.
- Used for: Similar to ChatGPT — but deeply connected to Google Search data, making it useful for quick fact checks (but still must be verified!).
- Where you see it: Gemini app, Google Workspace AI tools.
Anthropic (Claude 3)
- What it does: Another conversational AI, known for safer and more transparent AI behaviour.
- Used for: Generating content, drafting, and conversational tasks.
- Where you see it: Integrated in some business tools and available through Anthropic’s own Claude chatbot.
Meta (LLaMA series)
- What it does: Large open-weight language models (LLaMA) used more by developers and researchers to build custom AI applications.
- Used for: Research, experimentation, private company chatbots.
- Where you see it: Mostly behind the scenes or in open-source projects.
Stability AI (Stable Diffusion)
- What it does: Generates images from text prompts. It’s one of the most popular open-source image models.
- Used for: Visual content like marketing imagery, concept visuals, creative ideas.
- Where you see it: Many AI art tools are built on or inspired by Stable Diffusion.
Midjourney
- What it does: Highly popular AI image generation model. Known for creating stunning visuals from text prompts.
- Used for: Marketing visuals, design concepts, mood boards.
- Where you see it: Used via Discord or integrations with design tools.
How to Use AI in Financial Services Marketing
AI, used responsibly, can be a powerful asset for financial services marketers. Here are some practical, low-risk ways you can leverage AI today.
#1 Planning Events and Expos
Organising a financial expo or attending a key industry event requires enormous coordination. AI-powered tools can help streamline your planning by:
- Generating action plans and checklists for tasks such as booth design, logistics, and promotional activities.
- Suggesting event hashtags and audiences to target on social media.
- Drafting initial outreach emails to prospects and partners.
AI won’t replace your event manager or PR team. But it can handle the heavy lifting on mundane planning tasks, freeing up your people for the strategic work that matters.
#2 Conducting Competitor Research
AI tools like ChatGPT, Gemini and various AI-driven market research platforms can gather and summarise publicly available data on your competitors. They can:
- Give you an overview of your rivals’ digital footprint.
- Summarise recent news articles, press releases and marketing campaigns.
- Generate quick SWOT-style summaries for internal presentations.
However, it’s worth remembering that AI’s summaries are only as good as their training data. Always check the information against primary sources before using it to inform strategic decisions.
#3 Automating Marketing Workflows
AI can boost productivity across your marketing funnel. For example:
- Drafting initial social media posts (which you then adapt and approve).
- Suggesting A/B test variations for ads or email subject lines.
- Generating customer sentiment reports from reviews or surveys.
- Preparing article briefs with SEO focus.
Used properly, these tools help you react faster to trends and manage campaigns more efficiently, without replacing human oversight.
What to Avoid: AI Pitfalls in Financial Content
AI isn’t a magic wan. And nowhere is that truer than in highly regulated sectors like finance. Here’s where caution is critical.
#1 Compliance Risks in Financial Content
Financial promotions are tightly regulated by the FCA, ASIC, CySEC and other global regulators. AI-generated copy often looks polished but may:
- Include outdated figures or incorrect product information.
- Miss mandatory disclaimers and risk warnings.
- Over-promise on investment returns or benefits.
- Be inaccurate on trading education.
For instance, an AI tool may draft a blog suggesting a ‘guaranteed’ trading return, language that would never pass a compliance review. It may inaccurately depict how certain chart patterns work. Publishing unchecked AI copy can lead to fines, legal action, or damage to your brand’s reputation.
Rule of thumb: Never publish AI-generated financial content without a rigorous human review. They should be reviewing for:
- Branded tone of voice.
- Accuracy of information.
- Relevant, timely sources.
- Most importantly, compliance oversight.
Tools like ChatGPT can throw out non compliance answers depending on the prompts given. We asked it if forex trading will make us rich…
#2 Unreliable Sources and Hallucinations
One of AI’s biggest weaknesses is its tendency to “hallucinate”. In plain terms, that means it can fabricate sources, cite non-existent studies or mix up facts. This is particularly risky for:
- Market outlook pieces referencing economic data.
- Thought leadership that quotes trends or surveys.
- Research-heavy whitepapers aimed at investors.
Always verify facts, quotes and statistics. If an AI tool gives you a source link, check it. If the link doesn’t exist, treat the information as unreliable.
#3 Social Media Legal Risks
AI can churn out captions and hashtags in seconds, but using them blindly can cause IP headaches.
For example:
- It may suggest slogans that infringe trademarks.
- It might generate imagery with protected logos or stock elements you don’t have rights to use.
- Some AI image tools reuse copyrighted training data.
In the worst case, you could face takedown notices or fines. Always check that your AI-generated visuals, captions and hashtags are legally sound and aligned with your brand’s approved style guide.
Why is AI Content so Bland?
We’ve all received the emails telling you to “elevate” or “enhance” your brand. Readers have quickly come to recognise AI content and nothing turns them off faster than repetitive, unrelatable content.
Here’s why AI content can be so bland:
Designed to be predictable: At its core, a large language model works by predicting the most statistically likely next word or phrase. This is based on its training data (billions of words scraped from the internet). This means it’s optimised for average, safe, and common wording. Not for sharp opinions, bold creativity, or a strong human voice. The output is smooth and readable, but rarely original or surprising.
It avoids risky opinions: Most generative AI engines are trained to avoid controversy. So they tend to hedge, stay neutral, and steer clear of strong stances or edgy humour. All of which are often what make great human writing stand out. When you strip away risk, you also strip away personality.
It doesn’t understand subtext or true emotion: AI mimics tone, but it doesn’t feel. It doesn’t understand your brand’s history, the mood of your audience, or the subtle context behind why this article matters right now. It can replicate sentiment but nuance, wit, sarcasm, or cultural references usually land flat or feel oddly generic.
It can’t create truly fresh ideas: AI doesn’t invent new thoughts. It remixes what’s already out there. So the more original or opinionated your content needs to be, the less value a pure AI draft brings. This is why when you ask an AI for “thought leadership,” you often get a rehash of Google’s first page.
No stake in the game: Humans write with lived experience, company knowledge, and emotional investment. AI just writes words. That lack of real stake is why its output is often grammatically correct but soulless.
So, Should You Ditch AI?
Not at all, but you should see it for what it is. A tool for speed and structure, not for final polish or big ideas. The best results come when you use AI to:
- Draft rough frameworks or outlines.
- Summarise existing material.
- Do low-risk, high-volume tasks (like basic FAQs or metadata).
Then, skilled human writers layer in your brand voice, personality, specific examples, real insights, authority and compliance checks. In short, AI gives you something instead of a blank page. But only a human can turn bland copy into credible, differentiated financial services content that genuinely builds trust.
AI Is Not a Substitute for Original Thinking
Another trap to avoid is mistaking AI’s speed for strategic brilliance. Many tools can generate entire marketing plans or campaign calendars. But the output is often generic, and sometimes plagiarised from competitor sites or outdated templates. Senior marketers know that brand positioning, audience insight and differentiated messaging are what set firms apart in the crowded financial sector. These fundamentals can’t be outsourced to a bot.
Bottom line: Treat AI as a useful first draft or idea starter. But the final strategy, messaging and positioning must be crafted by people who understand your market and your compliance obligations.
Best Practices for Using AI in Financial Services Marketing
So how do you harness AI’s benefits without inviting risk? Here are a few key principles:
- Establish a Human Review Process: Make it policy that all AI-generated content is fact-checked, edited and signed off by compliance before publication.
- Use AI for Repetitive Tasks: Automate admin-heavy work like drafting emails, list segmentation or keyword suggestion. But keep creative strategy and writing in-house.
- Train Your Team: Make sure everyone understands AI’s limits, especially its tendency to produce plausible but incorrect information.
- Secure Proper Licensing: Be clear on IP rights for AI-generated images, audio or video. Some AI tools restrict commercial use.
- Stay Compliant: Monitor evolving guidance from regulators like ASIC, CySEC and FCA.
Balancing Innovation with Responsibility
The pace of AI innovation is huge and it’s tempting to jump on every new tool that promises more clicks, leads or conversions. But the real edge for financial services firms will come from smart, responsible adoption.
Successful brands will blend the efficiency of AI with the judgement and expertise of skilled financial marketers and compliance teams. They’ll use AI to cut costs and boost output without cutting corners on accuracy or ethics. The result? Faster, more personalised campaigns that build trust with investors and traders, rather than risking that trust with careless shortcuts.
For financial services marketing, the challenge is no longer whether to use AI, but how to do so safely and smartly. Used wisely, it might save your team hours, improve campaign performance and sharpen your competitive edge. Misused, it could land you in hot water with regulators and clients alike.
If you’re ready to integrate AI into your financial services marketing, without compromising on compliance or quality, speak to our team at Contentworks. We’ll help you find the right balance between innovation and responsibility.