This educational and resources guidance has been collated by the IAB Australia AI Working Group to help provide our industry members with a starting point when researching for resources to start getting to grips with GenAI.
Resources include some suggested tools, online courses, podcasts, newsletters, books, and basic prompt guidance – all designed to build confidence and give people the confidence to begin using these types of tools.
Some Tips for Getting Started & Building Confidence
Start Small: Begin with free, beginner-friendly resources like short online courses or podcasts. Experiment with simple prompts in tools such as ChatGPT, Gemini or Copilot to generate marketing ideas e.g., ‘suggest five email subject lines for a summer sale campaign targeting millennials‘.
Focus on Practical Applications: Apply what you learn directly to your work. For instance, use GenAI for brainstorming ad copy or analysing audience trends, which can quickly show tangible results and boost your confidence.
Just ask the LLM for Help: A good tip to start making the most of large language models (LLMs), is to simply ask the LLM for help in crafting an effective prompt. For example, you could ask i to ‘help me create a prompt to [describe your task]’. A well-designed prompt will often guide the LLM to provide more accurate and useful responses, helping to streamline your workflow and improve results.
Build a Learning Routine: Try to dedicate at least 30 minutes a day to a newsletter or podcast from the lists below. Consider joining an online community to ask questions and share experiences – remember, even experts started as beginners.
Prioritise Ethics and Governance: As an Australian marketer, align with local guidelines and always to ensure responsible use, avoiding pitfalls like data privacy issues. Ensure that you are up-to-speed on what your company policies are, particularly when leveraging any sensitive information or where client, customer and/or partner IP is involved.
Experiment Safely: Use free tiers of tools first, and test outputs for accuracy and bias. Over time, this hands-on approach will help you feel more comfortable integrating GenAI into your strategies.
Track Your Progress: Keep a journal of what works (e.g., effective prompts) and what doesn’t. Resources in this guide include prerequisites where relevant, and most assume no prior technical knowledge – unless specifically stated.
This guidance document collates resources from reputable sources and Australian-specific organisations (such the OAIC) and are categorised for ease, with some additional details on any potential costs, access types, and prerequisites.
We’ve tried to prioritise Australian-based content as much as possible and have included a dedicated section on ethics and governance. The various sections are outlined below, we hope you find them useful and as always, please feel free to feedback.
Tools and llms
Popular GenAI tools and LLMs for marketing, focusing on non-technical users.
| Tool/LLM | Type/ Main Function | Description | Access Type | Costs | Pre-requisites | Link |
|---|---|---|---|---|---|---|
| AdCreative.ai | Generative AI (Ad/Image/Copy) | Generates high-conversion ad creatives for marketing. | Open | Yes; free trial | None | AdCreative |
| Amazon Nova Pro | Generative AI | Multimodal generative model – text, image and video inputs and produce text outputs | No | Paid | Delivered through AWS Bedrock | Novo Pro |
| Canva | Generative AI (Design/Image/Text) | AI features for presentations/graphics in marketing. | Open | Free; paid pro option | None | Canva |
| ChatGPT | Generative AI (Conversational/Text) | Writing, questions, coding for marketing tasks. | Open | Free; paid pro options | None | OpenAI |
| Claude (Anthropic) | Generative AI (Conversational/ Text) | Generates campaign ideas/emails with a safe tone. | Open | Free; paid pro option | None | Claude |
| Copilot (Microsoft) | Everyday AI Companion | Microsoft’s AI companion, integrated across M365. | Open | Free; paid pro option | None | Copilot |
| DeepSeek | LLM (Budget-Friendly) | Reasoning for marketing on a budget. | Open | Free; paid pro option | None | DeepSeek |
| ElevenLabs | Generative AI (Voice Cloning) | Text-to-speech for marketing videos | Open | Yes; free trial | None | ElevenLabs |
| Gemini (Google) | Chatbot (Multi-purpose) | Questions, summarisation, image gen for marketing. | Open | Free (basic) | None | Gemini |
| Grok (xAI) | LLM (Conversational/ Reasoning) | Advanced reasoning; integrates with X for social data | Open | Free; paid pro options | None | Grok |
| Gumloop | Generative AI (No-code Automation) | Build workflows without coding for marketing. | Open/Beta | Free (beta) | None | Gumloop |
| HeyGen | Generative AI (AI Avatars /Video) | Lifelike avatars for marketing content. | Open | Yes; Free trial | None | HeyGen |
| Jasper | Generative AI (Writing/Content) | Content creation/optimisation for brands | Open | Yes | None | Jasper |
| Llama (Meta) | Multimodal & open-source | Conversational tool for text/image generation | Open | Free | None | Llama |
| Midjourney | Generative AI (Image Creation) | Text-to-image for marketing visuals. | Open | Yes | None | Midjourney |
| Mistral2 | AI Code Generation | Code generation, mathematical reasoning, general reasoning | Open | Yes; for Research. Commercial Paid | None | Mistral |
| NotebookLM (Google) | AI-powered notebook assistant | Builds a private notebook (audio or test) from uploaded documents. | Open | Free; paid pro options | Sources such as PDF files, Google Docs, Slides, or pasted text. | NotebookLM |
| Notion AI | AI (Productivity) | Notes and automation for marketing workflows. | Open | Free; paid pro option | None | Notion |
| Perplexity | Generative/Assistive AI (Search) | Research trends/competitors with citations. | Open | Free; paid pro option | None | Perplexity |
| PollFish | Predictive AI (Survey/Research) | AI surveys for market insights | Open | Pay per survey response | None | PollFish |
| Stable Diffusion | Generative AI (Image Creation) | Open-source text-to-image model. | Open | Free; paid pro option | None | SD.com |
| Suno | Generative AI (Music Creation) | AI music creation program. | Open | Free; paid pro option | None | Suno |
| Surfer SEO | AI (Content Optimisation) | Optimises content for search in marketing. | Open | Yes | None | Surfer SEO |
| Whimsical | Generative/Assistive AI (Diagrams) | Text-to-diagrams for marketing plans. | Open | Free; paid pro option | None | Whimsical |
prompt guidance
Learn to craft effective prompts for better GenAI outputs in marketing tasks like copywriting or ideation. No technical prerequisites.
Prompting Guide 101: A guide to provide users with the foundational skills to write effective prompts when using Gemini.
Access: Free. Prompting Guide 101
Learn Prompting: Free open-source guide on communicating with various LLM tools, for marketing outputs.
Access: Free. Learn Prompting
Prompt Engineering Guide: Strategies for prompts in various tools, with marketing examples.
Access: Free. Prompting Guide
Overview of prompts (Microsoft Learn): A explainer of prompts and prompt engineering as key concepts to help you create powerful generative AI capabilities.
Access: Free. Prompts Overview
Prompt Engineering for Generative AI (Google Developers): Art of prompting LLMs for marketing applications.
Access: Free. Prompt Engineering for GenAI
Prompt Engineering Overview (Anthropic): Guidance focused on success criteria that are controllable through prompt engineering.
Access: Free. Prompt Engineering Overview
Building effective agents (Anthropic): Practical advice for users keen to start building effective agents.
Access: Free. Building Effective Agents
Prompt Engineering Guide (IBM): Designing prompts for workflows in marketing.
Access: Free. IBM
A practical guide to building agents (OpenAI): Guidance for product & engineering teams to explore how to build their first agents.
Access: Free. Building Agents
The Ultimate Guide to Prompt Engineering (Lakera AI): Mastering LLM interactions for ad campaigns.
Access: Free. Lakera
Prompt Engineering for LLMs (Dextra Labs): Technical guide with marketing focus.
Access: Free. Dextra
Prompt Engineering Concepts (AWS Bedrock): Guidelines for Amazon tools in marketing. Access: Free. AWS Bedrock
Prompt Engineering Guide for Marketers (eLearning Industry): AI skills for content creators. Access: Free. eLearning
10 Best Online Prompt Engineering Courses (Learn Prompting): Free/paid options with certificates.
Access: Learn Prompting
Prompt Gallery (Microsoft): Designed to help users write, code, translate, analyze, and summarize content more effectively across various tasks. Link: Prompt Gallery
Prompt Engineering of LLM (Reddit Community Insights): Community-driven tips for marketing. Access: Free. Reddit
online courses
These are some courses that can provide structured learning courses on GenAI and LLMs, focusing on non-technical fundamentals and marketing applications. Most are beginner-friendly with no coding prerequisites.
| Course Name | Description | Access Type | Costs | Pre-requisites | Link |
|---|---|---|---|---|---|
| Generative AI for Everyone (DeepLearning.AI, Andrew Ng) | Explains GenAI basics, prompt engineering, and real-world uses like marketing and healthcare. Includes hands-on exercises and ethics. | Online (Coursera) | Free; certificate costs | None | Coursera |
| Introduction to Generative AI (Google Cloud) | Concise overview of GenAI vs. traditional AI, with marketing applications using Google tools. | Online (Coursera) | Free | None | Coursera |
| AI for Non-Techies (NonTechies.ai) | Jargon-free masterclasses on practical AI for content creation and automation, ideal for marketers. | Subscription-based academy | Free resources; premium subscription | None | NonTechies.ai |
| AI For Everyone (DeepLearning.AI, Andrew Ng) | Broader AI intro with GenAI applications; also covers ethics and bias. | Online (Coursera) | Free | None | Coursera |
| Microsoft Generative AI for Beginners | 18 lessons on building GenAI apps with minimal tech knowledge, focused on marketing tools. | Online (Microsoft Learn) | Free | None | Microsoft Learn |
| AWS Generative AI Fundamentals | Short course on business applications like customer service automation for marketers. | Online (AWS Skill Builder) | Free | None | AWS |
| Generative AI Fundamentals Specialization (IBM) | Covers prompt engineering, LLMs, and projects like chatbots for marketing. | Online (Coursera) | Free | None | Coursera |
| ADaSci Generative AI Course | Hands-on for non-tech pros, focusing on content generation & marketing. | Online | Some Free; paid pro option | None | ADaSci |
| GenAI Essentials – Full Course for Beginners (ExamPro) | Cloud-based GenAI essentials with marketing examples. | YouTube/ Online | Free | None | YouTube |
| Introduction to Generative AI for Non-tech Professionals (Udemy) | Fundamentals for work applications in marketing. | Online (Udemy) | $15.99 | None | Udemy |
| AI for Marketing (LearningVersity Australia) | Australian-focused training on AI tools for modern marketing. | Online | Various paid options | None | LearningVersity |
| Generative AI for Executives (NetCom Learning) | Framework for leading GenAI initiatives in marketing. | Live Masterclass | Various paid options | Basic business knowledge | NetCom |
| ChatGPT for Digital Marketing (Great Learning) | Free intro to GenAI in digital marketing. | Online | Free | None | Great Learning |
| AI-Driven Digital Marketing (DigitalDefynd) | Covers AI in campaigns; includes MIT/Oxford insights. | Online | Some Free; paid pro option | None | DigitalDefynd |
| Generative AI Guide for Business and Sustainability (Shortlisted Productions) | Practical guide with marketing & sustainability focus. | Online/Udemy | Some Free; paid pro option | None | Shortlisted |
| AI Training Overview (Grow with Google) | Practical AI training and tools from Google. | Online | Free | None | AI Training |
Ethical Considerations, Best Practices, and Sensible Governance
This section provides some guidance from local resources (such as the OAIC) focusing on privacy, fairness, and the responsible usage of AI in marketing.
Guidance on Privacy and Commercially Available AI (OAIC): Complying with privacy when using GenAI in marketing; recommends avoiding personal data inputs.
Access: Free. OAIC
Guidance on Privacy and Developing GenAI Models (OAIC): For developers/training models with marketing data.
Access: Free. OAIC
AI Governance and Risk Management Playbook (IAB): A playbook designed to help industry practitioners understand and approach the central governance and risk management issues that may arise when adopting AI-assisted solutions common advertising use cases.
Access: Free PDF. IAB
National Framework for AI Assurance in Government (Finance.gov.au): Ethics principles for safe AI in business/marketing.
Access: Free PDF. Finance
Australia’s AI Ethics Principles (Industry.gov.au): 8 principles for safe and reliable AI usage in marketing.
Access: Free. Industry
AI Governance (ZipThought): Fairness/accountability in Australian AI systems.
Access: Free. ZipThought
Data Regulations in Australia’s Telecom Sector (Securiti): Best practices for AI ethics in data-heavy marketing.
Access: Free. Securiti
Can GenAI Help or Hinder Sustainable Marketing? (ResearchGate): Ethical principles like justice/explainability.
Access: Free. ResearchGate
AI Standard (Practical Law): Best practices for governance in organisations.
Access: Free. Practical Law
GenAI Concepts (ADM+S Centre): Risks/regulations for Australian marketers.
Access: Free. ADM+S
New AI Guidance (LinkedIn, Nick Abrahams): OAIC best practices for privacy in GenAI.
Access: Free. LinkedIn
AI Regulation (Norton Rose Fulbright): OAIC guidance on privacy laws for AI in marketing. Access: Free. Norton Rose
OAIC Releases Guidance on Privacy and AI (Dentons): Best practices for sensitive info.
Access: Free. Dentons
Artificial Intelligence Topics (DataGuidance): OAIC priorities for 2025-26 on rights in AI.
Access: Free. DataGuidance
The Quest for Lawful AI Training (SSRN): Global regulatory landscape for data in AI marketing. Access: Free PDF. SSRN
Data and AI Governance (arXiv): Equity/ethics in GenAI for marketing.
Access: Free. arXiv
Suggested Newsletters
Stay updated with curated GenAI insights for marketing, delivered via email.
The Rundown AI (Rowan Cheung): Get the latest AI news, understand why it matters, and learn how to apply it in your work. Access: Free. The Rundown AI
Visually AI (Heather Cooper): Demystifies GenAI tools for text/image creation in marketing.
Access: Free & paid premium. Substack
Inside My Head (Ben Jacobson): GenAI use cases in marketing & e-commerce.
Access: Free & paid premium. Substack
Gradient Ascent: Explains GenAI concepts for beginners.
Access: Free & paid premium. Substack
Mindstream: Daily AI news/tools for productivity in marketing.
Access: Free. Mindstream
AI Supremacy: A list of AI newsletters with a marketing focus.
Access: Free. AI Supremacy
Superhuman AI: List of newsletters with trends and insights for non-tech marketers.
Access: Free. Superhuman
Awesome AI Newsletters: A curated list of top best AI Related Newsletters and ai agents newsletters.
Access: Free. GitHub
Everyday AI Newsletter: LLM tips for marketing.
Access: Free. Everyday AI
10 Best AI Newsletters: Updates on AI applications in marketing.
Access: Free. Jotform
A Non-Technical Guide to LLMs (Generative AI Pub): Broader impact on marketing.
Access: Free. Medium
Best AI Newsletters by Experience (Gold Penguin): Categorised for beginners.
Access: Free. Gold Penguin
Top 6 Free AI Newsletters (Roisin Bennett): Marketing transformations.
Access: Free. LinkedIn
This AI Newsletter is All You Need (Towards AI): Non-technical LLM insights.
Access: Free. Towards AI
Almost Timely News: Optimising marketing for AI.
Access: Free. Christopher Penn
Nate’s Substack (Nate Jones): Daily newsletter from the cutting edge of AI, including news, strategy, product breakdowns, and thought pieces.
Access: Free. Nates Newsletter
Useful Videos & Dedicated YouTube Channels
Visual tutorials and channels for beginners in GenAI marketing.
Intro to Large Language Models (Andrej Karpathy): 1 hour general introduction to Large Language Models. Access: Free. YouTube
MIT AI Channel: Lectures/demos on GenAI applications in art/science/marketing.
Access: Free. YouTube
Generative AI for Beginners (Microsoft): An introduction to GenAI and the range of AI-powered tools and solutions from Microsoft: Microsoft Learning
GenAI Essentials – Full Course (ExamPro): Comprehensive beginner course.
Access: Free. YouTube
Gen AI Tutorial for Beginners (Intellipaat): Marketing-focused tutorial.
Access: Free. YouTube
Top 11 YouTube Channels for GenAI (Analytics Vidhya): Curated list with marketing content. Access: Free. Analytics Vidhya
Krish Naik Channel: ML/GenAI for computer vision in marketing.
Access: Free. YouTube
Best Channels for GenAI (GUVI): Tutorials for beginners.
Access: Free. GUVI
GenAI Full Course 2025 (Simplilearn): In-depth beginner tutorial.
Access: Free. YouTube
Digital Marketing Tutorial (Simplilearn): GenAI integration.
Access: Free. YouTube
How to Build AI Agents (Simplilearn): Marketing applications.
Access: Free. YouTube
Simplilearn Channel: Digital marketing with GenAI.
Access: Free. YouTube
Generative AI Full Course (Great Learning): All-in-one tutorial.
Access: Free. YouTube
Best Channels for Digital Marketing (GUVI): AI-focused.
Access: Free. GUVI
Gen AI For Marketing Professionals: Social media tips.
Access: Free. YouTube
Every Google Gemini Feature Explained (Skill Leap): A walk-through every major Gemini feature, starting with what’s free and then paid.
Access: Free. YouTube
Stanford CS229 (YouTube): Introduction to Machine Learning with Andrew Ng, covering the fundamentals of machine learning.
Access: Free. Stanford CS229 YouTube
Recommended Podcasts
Engaging podcast discussions on GenAI’s role in marketing, suitable for non-technical listeners.
The AI Daily Brief: A daily news analysis show on all things artificial intelligence.
Access: Free. Podlink
The AI Podcast (Nvidia): Explores GenAI in gaming/science/marketing.
Access: Free. Nvidia
AI-Driven Marketer: Master AI marketing strategies.
Access: Free. Danchez.com
AI for Marketers (Everyday AI): Interviews and case studies.
Access: Free. Everyday AI
The Artificial Intelligence Show (Marketing AI Institute): Covers the latest in AI news, what it means, and how it impacts marketing and business today.
Access: Free. marketingaiinstitute
AI Inside: A weekly podcast trying to offer a balanced and engaging look at how AI is impacting our world. Access: Free. AI Inside
In-Ear Insights: Generative AI Optimization: Tactics for marketing. Access: Free. trustinsights.ai
Redefining Marketing Automation (IBM): GenAI for personalisation.
Access: Free. IBM
What Does Generative AI Mean for Marketing? (Nash Squared): Industry discussions.
Access: Free. Nash Squared
The 18 Best Generative AI Podcasts (bCast, July 2025): Enterprise success stories.
Access: Free. bCast
Recommended Books
Narrative-driven books on GenAI for non-technical readers, with marketing angles.
Artificial Intelligence: A Guide for Thinking Humans (Melanie Mitchell): Explores capabilities/limitations in creative marketing tasks. RRP: $26.99. Penguin
Machine Learning and Generative AI for Marketing: Technical instructions with strategic insights.
RRP: $68.99. Amazon AU
5 Books for Non-Technical Users (Medium): Guides like Steve Finlay’s intro to AI/ML.
25 Trending Books on AI and GenAI (Thinkers360): Includes marketing-focused titles. Thinkers360
The Modern AI Marketer: Guide to GenAI Prompts (Pam Didner): 75+ prompts for marketing. RRP: $17.69. Pam Didner
Top Generative AI Books (MentorCruise): Expert recommendations for marketers.
15 AI Books for 2025 (DigitalOcean): Diverse perspectives on GenAI applications.
A Non-Tech Beginner’s Guide to Generative AI (Medium): Basics for content creation.
Generative AI Books 2025 (Simplilearn): Transforming understanding for marketing.
Generative AI in Practice: 100 ways AI changes business/marketing.
Free: PDF
The Coming Wave: a must-read guide to the technological revolution just starting, and the transformed world it will create. RRP: $59. The Coming Wave
Glossary of Common Terms
This glossary covers the most common terms used in generative AI (GenAI) and large language models (LLMs) to help support this guidance and resources lists.
AI Agent: An autonomous AI system that performs tasks, makes decisions, and interacts with tools or APIs to achieve goals, such as automating marketing workflows.
Algorithm: A series of instructions that allows a computer program to learn and analyse data in a particular way, such as recognising patterns.
Anthropomorphism: Attributing human-like qualities (e.g., emotions) to AI systems, which are tools without actual consciousness.
Artificial Intelligence (AI): Technology that simulates human intelligence to perform tasks like pattern recognition, decision-making, or content creation.
Artificial General Intelligence (AGI): A theoretical form of AI that can perform any intellectual task a human can, adapting independently across domains.
Artificial Narrow Intelligence (ANI): AI designed to perform a single task or narrow set of functions efficiently, without broader adaptability.
Bias: Errors in AI outputs caused by skewed training data, leading to unfair or inaccurate results, such as stereotyping in marketing content.
Chain-of-Thought Prompting: A technique where prompts encourage AI to reason step-by-step, improving accuracy for complex tasks like campaign planning.
Chatbot: An AI program that simulates human conversation, often used in customer service or marketing interactions.
Context Window: The amount of preceding information (e.g., conversation history) an AI model can retain when generating responses.
Compute: This refers to the computational resources used to train and run AI models. This includes the processing power, memory, and storage needed to handle the large amounts of data and complex calculations involved in AI.
Deep Learning: A subset of machine learning using multi-layered neural networks to analyse complex data, powering advanced GenAI tools.
Diffusion Model: A GenAI method that generates images or other media by gradually adding and removing noise, used in tools like Midjourney for visuals.
Emergent Behaviour: Unexpected capabilities that arise in large AI models, such as creative problem-solving beyond initial training.
Few-Shot Learning: An AI’s ability to learn a new task from just a few examples, useful for quick adaptation in marketing scenarios.
Fine-Tuning: Adjusting a pre-trained AI model on specific data to improve performance for tasks like brand-specific content generation.
Ghibli AI: Broadly refers to AI tools, models, or filters that generate images in the distinct visual aesthetic of the Japanese Studio Ghibli.
Generative AI (GenAI): AI that creates new, original content like text, images, or videos by learning patterns from training data.
Generative Adversarial Network (GAN): A GenAI model with two competing neural networks: one generates content, the other evaluates its realism.
Guardrails: Policies and restrictions in AI systems to ensure responsible handling of data and prevent harmful or disturbing outputs.
Hallucination: When an AI generates false or nonsensical information as if it were true, a common issue in LLMs requiring fact-checking.
Large Language Model (LLM): An AI trained on vast text data to understand and generate human-like language, e.g., ChatGPT, Gemini or Claude.
Machine Learning (ML): A branch of AI where systems learn from data to improve predictions without explicit programming.
Multimodal AI: AI that processes and generates multiple types of data, such as text, images, audio, or video.
Natural Language Processing (NLP): AI technology for understanding and generating human language, foundational for chatbots and content tools.
Neural Network: A brain-inspired system of interconnected nodes that processes data to recognise patterns, the core of deep learning.
Parameters: Numerical values in an AI model that define its structure and behaviour, influencing how it processes inputs.
Prompt: The input text or instruction given to an AI to guide its output, e.g., a query for ad copy ideas.
Prompt Engineering: The skill of crafting effective prompts to get better AI responses, crucial for marketing efficiency.
Retrieval-Augmented Generation (RAG): A technique combining AI generation with retrieving external data for more accurate, grounded outputs.
Reinforcement Learning: AI training method using feedback (rewards/penalties) to improve decision-making, applied in optimising ad strategies.
Singularity: Refers to a hypothetical future point when artificial intelligence surpasses human intelligence and begins to enter a runaway cycle of self-improvement, leading to changes so rapid and profound that we cannot meaningfully predict what may happen afterwards.
Temperature: A setting controlling AI output creativity – low for consistent responses, high for varied or imaginative ones.
Token: The basic unit (e.g., word or sub-word) that LLMs process; context windows are measured in tokens.
Transformer Model: The architecture enabling LLMs to process language efficiently by understanding context and relationships between words.
Zero-Shot Learning: AI’s ability to perform tasks without prior specific examples, relying on general knowledge.
