A quick start guide to AI for marketing

Are you a confident AI power user or still searching wildly for help and assurance in a sea of garbled guru speak? If you’re in the second camp, you’re in the right place. In this article, we share some of the key strategies for AI in marketing that our CEO, Matthew Stibbe, shared in a webinar, including getting found by AI search, improving marketing team productivity and navigating the ethical and legal challenges.

Get found by AI search tools

The question Matthew has been encountering most in the past year is: ‘How do I get found by AI?’ Matthew described the challenge as ‘PR for AI’: in other words, how do you become a trusted, visible source for AI to cite?

In practice, it means:

Focusing on improving your visibility in Bing for ChatGPT (its primary source for answers)
Publishing crawlable, informational content (ungate your content unless there’s a really good reason)
Monitoring your LLM citations using tools like Ahrefs or HubSpot’s AI Search Grader (and make sure you check your competitors’ citations too)
Studying Google AI Overviews and ‘People Also Ask’ to understand how your sector is being summarised and referenced in AI summaries
Getting familiar with Reddit and Quora which appear in 5.5% and 4% of Google AI overviews respectively, and starting to post if it’s relevant for your target audience
Explore using schema and llms.txt for key company information and your top-performing content (visit llmstxt.org and Firecrawl to learn more)

There’s also a formatting shift to consider. If your best thinking sits behind a gated PDF, it’s invisible to AI. Matthew’s recommendation is open publication, paired with a downloadable version as added value, to increase both citations and conversions.

Create compelling original thought leadership

While technical tweaks matter, original thinking matters more. ‘The biggest thing you can do is create compelling thought leadership content,’ according to Matthew. Google and traditional SEO aren’t going anywhere anytime soon, so this covers both bases.

HubSpot’s AI search guidance emphasises conversational clarity, credible sourcing, structured long-form content and close alignment with user intent. Write clearly, cite properly, go deep and answer the questions that your users are asking.

If you want more expert insights about thought leadership, these are some of our best blogs and webinars on the topic:

Improve your marketing team’s productivity

It would be remiss of us to talk about AI in marketing without talking about one of its most valuable applications: supercharging your marketing team’s output.

These are some of the best examples we’ve seen and have experience with:

HubSpot and ChatGPT integration: With the right configuration, you can run deep research queries across your own CRM data using natural search questions, like ‘What are our best converting offers for marketing leaders, and why?’
Editing support: Most (paid) accounts for ChatGPT, Perplexity and the like will let you add guidelines for tone of voice, writing style, personas, business plans and other key documents which allow AI to support with brand consistency and proofreading copy.
AI meeting assistants: Tools like Notion AI, Fathom and Granola now generate accurate summaries, transcripts and action lists from live calls. It lets you be fully present in conversations instead of trying to split your attention across tasks.
Content production: We use Riverside for podcasts and webinars, and its AI-generated transcripts, social clips and show notes shrink the post-production burden significantly.

Understand what AI can (and can’t) do

We see the immense value AI has for marketers, but we also acknowledge the risks of becoming over-reliant. Research from Microsoft found that, ‘while GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term over-reliance on the tool and diminished skill for independent problem-solving.’

Here are some issues we’re aware of, to keep in mind when you’re using AI tools:

Sycophancy: Agreeing with everything you say, which often isn’t helpful for improving work or processes.
Out of date information: Don’t rely on AI to provide the latest news or data on a certain topic (see also: hallucinations).
In-built bias and censorship: All AI output originated with human input, and bias and self-censorship have already been well-documented.
Hallucination: AI can make things up and be very convincing about it. Always fact-check anything it tells you.

Navigate the ethical and legal challenges of AI

Before you dive headfirst into AI wonderland, make sure you’ve got your governance (and compliance) sorted. The key elements you need are:

An AI policy: Articulate has an AI policy you can read, but other companies in your industry will have them too if you want something industry-specific point of reference. Take extra special care if you have environmental commitments (or regulations) as AI’s role in the climate crisis is under increasing scrutiny.
User training: Beware unleashing your teams on AI tools, policies and regulation without any training. The best case scenario is inefficient usage. The worst case scenario is legal proceedings stemming from issues such as copyright infringement or privacy breaches.
Technical, legal and HR oversight: Related to said legal proceedings, make sure you involve the right internal stakeholders from the start. While there are notable gaps in existing laws, there are several ongoing cases that may set new precedents, particularly around copyright.

What’s next with AI technology?

If you’d like to hear Matthew’s AI predictions for the next two years, as well as more pearls of wisdom for how to make the most of it now in your marketing, sign up to watch our on-demand webinar. Looking for more personalised expertise to level up your marketing and fuel your sales cycle? Book a free marketing strategy session with our team.