Do you know these AI marketing terms?
Whether you're creating content, optimizing campaigns, or engaging customers, you must understand key AI terms to make smart, strategic marketing moves in 2025. Some elements of AI seem pretty intimidating at first glance, but we've got your back.
Let's start with the star of the show:
#1 – Artificial intelligence (AI)
Artificial intelligence is a machine (computer) simulating human intelligence processes.
Now, for the fun stuff.
Foundational AI concepts and terms
#2 – Machine learning (ML)
Machine learning is a subset of AI where systems improve automatically through data and experience. For example, your email platform learns over time which subscribers click most, and adapts accordingly.
#3 – Natural language processing (NLP)
Natural language processing is technology that helps machines understand and interpret human language. It's behind everything from grammar-correcting tools to sentiment analysis and AI-driven chat.
#4 – Large language model (LLM)
Large language models are a type of AI model trained on massive amounts of text to generate or analyze language. ChatGPT, Gemini, and Claudeare examples of LLMs. They're powering everything from content writing to customer service bots.
#5 – AI training data
AI training data is information fed into an AI system to teach it how to perform tasks. The quality and bias of this data have a huge impact on how well an AI performs.
#6 – Retrieval-augmented generation (RAG)
RAG combines two key things to make AI smarter. 1) Retrieval: It pulls relevant, accurate information from reliable sources like knowledge graphs, websites, or reviews; and 2) Augmented generation: Using this data, the AI crafts responses that feel conversational and are grounded in facts.
Terms about how AI "thinks" and "learns"
#7 – Explainability (of AI models)
Explainability models articulate the degree to which you can understand and explain how an AI made a decision. They're crucial for trust and compliance. (They also help you avoid looking misinformed in front of others.)
#8 – Hallucination
When an AI confidently spits out false or made-up information, it's called hallucination. (Yes, even the best models do this sometimes.) Marketers using generative AI need to fact-check everything.
#9 – Supervised vs. unsupervised learning
Supervised learning means AI learns from labeled data (e.g., "this is a happy review"). Unsupervised learning means that AI finds patterns in data without labels (e.g., segmenting customers by behavior clusters).
Content and messaging tools terms
#10 – AI-generated content
AI-generated content refers to text, images, video, and audio created by artificial intelligence. From blog intros to ad headlines to synthetic voiceovers, AI-generated content is emerging as a staple in content production. This post explores how AI-generated content supports local competitiveness. Not to be confused with…
#11 – Generative AI
Generative AI, or gen AI, is a broad category describing AI that creates new "stuff" like text, art, code, etc. Tools like Midjourney and Runway fall into this camp.
#12 – Predictive text
Every time you type a sentence and your SMS or email client finishes it for you…that's predictive text in action. Predictive text is powered by NLP and ML.
#13 – Prompt engineering
Prompt engineering is the art of crafting the right input to get the best output from an AI model. It's become a key skill for marketers using generative AI tools — like learning how to talk to your robot copywriter.
#14 – Model fine-tuning
Model fine-tuning is the process of customizing an AI model with specific data so it performs better for your use case. For instance, think of fine-tuning a chatbot to know your brand voice and FAQs.
Conversational and voice-driven AI terms
#15 – Chatbot
The classic AI tool, chatbots are an AI-driven tool that interacts with users via text or voice. It can handle support queries, collect leads, or even inject jokes into interactions.
#16 – Conversational AI
Conversational AI is a broader term with more use cases than "chatbot." Think of it as offering more sophisticated, multi-turn interactions across platforms. Think customer support that feels like texting a friend (if your friend knew your order history). Conversational AI is also changing search because it's reshaping the way customers ask questions.
#17 – Voice AI
Voice AI powers voice assistants like Siri or Alexa. In marketing, both customers and brands use voice AI for audio search, customer support, and commerce.
Terms about marketing automation and personalization with AI
#18 – Marketing automation (AI-enhanced)
Your automation platform, now smarter. AI-enhanced automation predicts the best time to send emails, selects high-performing content, or triggers actions based on behavior.
#19 – Content personalization
Content personalization uses AI (among other technologies) to tailor messaging, offers, or creative to individual customers. For example, showing product recommendations based on browsing history or location is a type of content personalization.
#20 – Recommendation engine
A recommendation engine is the AI behind "You might also like" carousels and personalized email offers. It's a must-have for ecommerce, streaming, and any content-heavy brand.
#21 –Dynamic creative optimization (DCO):
DCO is an AI-driven advertising tech. It assembles the best-performing mix of headlines, images, and CTAs in real time based on user data. Think of DCO as A/B testing on steroids.
Terms about AI and smarter targeting and analysis
#22 – Predictive analytics
Predictive analytics use AI to forecast future outcomes, like which leads are most likely to convert or when a customer signals they're about to churn.
#23 – Lookalike modeling
Lookalike modeling is AI that identifies characteristics of your best customers and finds new audiences that resemble them. It's hugely effective in paid social and programmatic campaigns.
#24 – Sentiment analysis
Sentiment analysis is achieved when AI detects the mood in text — positive, negative, or neutral. It's powerful for understanding brand perception in reviews, social mentions, and surveys.
Terms related to cutting-edge and emerging AI search experiences
#25 – Agentic AI
Agentic AI can take goal-directed actions on your behalf. Instead of just suggesting content, agentic AImight write, schedule, and post it across platforms automatically. Customers can use an AI agent to discover brands, decide what to buy and why, and initiate a purchase on the customer's behalf. It's the next frontier in automation.
#26 – AI Overviews (AIOs)
Google introduced AI Overviews as a new feature in May 2024 to provide AI-generated summaries at the top of search results. It's reshaping SEO as we know it. This was one of the earliest mainstream implementations of AI and we expect to continue to see Google's use of AI evolve over time.
#27 – Zero-click search results
Zero-click search results are answers that appear directly on Google and other AI search engines like Gemini, ChatGPT, and Perplexity. They reduce the need to click through to brand websites (read: lower traffic to your site) and can make it harder to optimize the customer journey, analyze marketing performance, and report on attribution.
Coming to terms with AI
AI isn't coming for our jobs — but it is reshaping the way we work, shop, find healthcare, and choose financial advisors.
The more fluent you are in the language of AI, the more strategic you can be and the better you can serve your customers and patients. Whether you're fine-tuning a model, designing a campaign with DCO, or writing your next blog post (maybe even with an assist from AI), these terms are your new marketing vocabulary.
Now that you're well-versed on the terminology, let's talk AI strategy.
