Using AI in marketing: A 2026 guide
Great marketing comes from strong data, targeting, content, and workflows. AI makes it easier to create, maintain, and scale. Here’s how.
Great marketing comes from strong data, targeting, content, and workflows. AI makes it easier to create, maintain, and scale. Here’s how.
AI marketing refers to skilled marketers using AI to support the parts of their role that don’t require human creativity and strategy. This could include analysing data sets, running A/B tests, automating workflows, answering simple questions on the website, and much more.
As of 2026, the widespread use of AI has lifted customer expectations across the board. If a prospect can get an instant response from your competitors, it becomes hard to compete without AI support.
Despite this high expectation, 51% of marketers report that many of their campaigns still feel generic, highlighting the gap between what customers expect and what brands can deliver.
The next evolution of marketing is shifting away from one-way campaigns and towards responsive, personalised customer conversations. AI is helping make that possible. This guide explains what AI marketing is, how it works, where marketers are using it today, and how to get started.
AI marketing is an umbrella term that covers a range of technologies designed to help marketers. While these tools are often grouped together, they serve different purposes and deliver value in different ways.
For example, some AI tools help marketers generate ideas and draft content, while others analyse customer behaviour, organise data, automate repetitive tasks, or surface insights that support decision-making. Understanding these differences can help you identify and implement the right tools to reach your goals.
| Technology | What it does | Example |
|---|---|---|
| Automation | Automates repetitive tasks based on predefined workflows | Sending a follow-up email after a customer downloads a guide |
| Generative AI | Helps marketers brainstorm ideas and summarise information | Generating topic ideas, summarising research, or creating a first draft of an email |
| Predictive AI | Analyses historical and real-time data to identify patterns and likely outcomes | Highlighting customers who may be ready to buy or are at risk of leaving |
| AI agents | Carry out multi-step tasks on behalf of marketers by using approved data and instructions | Researching customer information, updating records, or preparing recommendations for review |
While today's marketers have access to more customer information and technology than previous generations, many teams still struggle to turn that information into meaningful customer experiences.
We found in our 10th State of Marketing Report that some of the biggest challenges facing marketers today include:
All these challenges are leading to marketing teams looking for a better way to get things done, often using AI to get there. AI can help marketers analyse all the data they have to identify trends and automate repetitive processes.
The goal here isn't to replace marketers, junior or senior. Instead, it's helping them amplify their communication skills to compete in an increasingly complex marketing landscape.
As customer expectations continue to rise, marketers are being asked to deliver more personalised experiences and prove ROI across every campaign. AI can help teams meet these expectations by making it easier to uncover insights they can use, from the data they already have.
We found in our 10th State of Marketing Report that organisations deploying AI are seeing measurable results, including:
If you’re finding it challenging to track results and show up for customers in the way they expect, AI can help you push your results to the next level.
Action all your data faster with unified profiles and analytics. Deploy smarter campaigns across the entire lifecycle with trusted AI. Personalise content and offers across every customer touchpoint.
Before using AI, it's important to understand both the opportunities and the challenges. While AI can help marketers, it also introduces considerations around responsible use. In fact, we found that 66% of marketers say it’s hard to balance personalisation with laws and regulations.
Let’s examine some of the reasons why that might be.
Ethical concerns about data privacy, security, and consumer trust call for compliance and regulations to safeguard customer information. There’s also the problem of AI bias, which could lead marketers down the AI path with false or misleading information. Combining these ethical concerns will require regular human intervention to verify the quality of AI's information.
Technical expertise is vital for successful AI integration. To get the most out of AI and ML models, you need specialists who understand how to capitalise on the benefits of AI while mitigating its drawbacks. Training up a skilled workforce capable of deploying, using, and optimising these tools and platforms can be a hurdle.
For AI to produce excellent output, high-quality input is required. Poor data quality can lead to inaccurate insights and flawed decision-making. As such, businesses need to ensure their data is collected, collated, and accessible for use with AI tools. Ensuring proper data quality with unified customer profiles is a big part of this.
Many marketers are concerned that AI will kill creativity, especially as more brands use these tools to create AI content. For that reason, businesses need to promote AI as an assistive tool designed to spark creativity rather than a crutch to rely on. AI-generated content and images are receiving a lot of backlash from customers online, so it’s important to assess how your audience responds to your marketing and adjust accordingly.
Most AI models were trained on copyrighted material without the knowledge or permission of original creators (authors, artists, photographers , etc.). Apart from being an ethical black mark on AI, this has resulted in multiple global lawsuits that are unlikely to be resolved soon. Can you be certain that the material you’re using isn’t copyrighted? Can you be certain the information presented hasn’t been pulled from one of your competitors? Make sure to avoid legal ramifications.
It’s estimated that one in three Australian workers is at risk of job loss by 2030 due to businesses implementing AI. This will have significant flow-on effects that cannot yet be measured, and it’s likely to be a key concern of your team. It’s especially important to think about how we can give the next generation the opportunity to build their marketing skills so we can pass the torch years down the road.
Generative AI’s use of enormous volumes of data has created more urgency for data privacy. At the same time, some companies are AI-ifying their products without ensuring customer data is 100% protected. Customers have understandable concerns about privacy issues and data mining. To address this, companies have an obligation to provide transparency around how they’re using data and to ensure data privacy .
AI in marketing has its pitfalls, but by blending AI with human creative reasoning, each of these challenges can be avoided, allowing your company to experience the full business benefits.
To put these benefits into context, let's examine a handful of AI's different applications in marketing. Here’s how businesses and brands use AI in marketing to fuel engagement, increase conversion rates, and grow their bottom lines.
AI can help marketers generate branded blogs and social media drafts with a few clicks, using business data and previous human-written content.
AI chatbots can provide 24/7 customer support, using natural language processing (NLP) to help identify relevant information and respond to common customer enquiries.
AI can analyse user behaviour and preferences to help marketers provide product recommendations and deliver more personalised customer experiences.
AI can use a wealth of historical data to identify trends and forecast potential outcomes. It can help marketers forecast demand, identify high-value customers, and anticipate potential supply chain challenges.
AI can analyse your social media data to identify the best times to post and help marketers understand which content is generating the strongest engagement. It can also make drafts for content, but be careful to give it your own spin so it doesn’t read as generic.
While AI doesn't have direct access to SEO or keyword data, marketers can feed this information into AI tools to help analyse trends and brainstorm content ideas.
AI can analyse audience data and campaign performance to help marketers optimise ad placements, timings, and budget allocation.
AI tools can analyse comments and feedback on a product or service to identify customer sentiment. For instance, social media listening tools with AI can help marketers assess how customers are responding to their marketing across social platforms.
In our State of Marketing Report , we found that personalising content is the top use case for AI in marketing.
One of the newest developments in AI marketing is the rise of AI agents. Unlike generative AI, which responds to prompts, AI agents are designed to complete specific tasks using approved data and rules.
In a marketing context, AI agents can help teams:
The growing interest in AI agents is being driven by changing customer expectations. We found that 83% of marketers say customers now increasingly expect two-way conversations with brands. At the same time, 69% marketing professionals struggle to respond quickly, and only 55% frequently reply to customer responses on channels like email and SMS.
AI agents can help bridge that gap by supporting faster, more responsive customer engagement. In fact, 81% of marketers trust AI to respond to customer enquiries, while 82% of marketers who use or plan to use agents expect moderate or significant improvements to marketing ROI.
As adoption grows, agents are becoming an increasingly important part of AI marketing. While only 13% of marketers currently use agentic AI, high-performing teams are already using AI agents to reclaim up to eight hours per week and achieve stronger marketing ROI.
Keep these nine priorities in mind as you pave the way for AI in marketing at your company.
Ask yourself what you hope to achieve, and align your team on the purpose of AI integration. This will assist with choosing the right AI tools and training your AI models to serve your business needs.
Collect all of your siloed data sets in one place and ensure they are readily available for analysis. The more data you can feed into your AI tool, the stronger the output.
This means using transparent data practices, ensuring data privacy compliance, and fostering a culture of ethical AI usage. For example, you can establish clear opt-in/opt-out mechanisms and communicate comprehensive data usage policies.
You learn more about your customers’ preferences by integrating data using AI-powered tools. This holistic view of customer behaviour helps create effective marketing.
When you use AI-driven recommendation engines on e-commerce platforms, product suggestions are based on individual preferences and purchase history. As a result, the customer experience is vastly improved.
Start small with simple applications and assess the integration's results. If all goes well, gradually iterate and expand your selection of AI tools, regularly reviewing as you go.
Providing training on how AI-driven natural language generation tools work will inspire you to craft compelling content at scale. You can generate personalised email campaigns, product descriptions, and social media posts that resonate with target audiences.
Using AI-powered automation tools for tasks such as data entry, report generation, and email scheduling enables your team to focus on more strategic initiatives and creative campaign ideation.
AI-powered analytics platforms can provide real-time data on customer engagement and conversion rates. This means you can make data-driven decisions and adjust as necessary to optimise campaign performance and ROI.
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The majority of marketing teams are now using AI in some way. While the technology is already helping marketers analyse data and automate repetitive work, its full impact on the industry is still unfolding. In many ways, we're only scratching the surface. The technology is evolving so quickly that next year we'll likely be talking about entirely new capabilities.
For marketers looking to get started, it pays to start small. Look for ways AI can support the work you're already doing, whether that's analysing customer data, brainstorming content ideas, improving personalisation, or reducing manual tasks. We recommend being curious with your testing and learning.
Ready to streamline your workflow with AI agents? Discover how Agentforce can automate tasks and boost efficiency across your business today.
Get hands on with next-gen marketing, where humans & agents work together to spark customer conversations.
No, and we don’t want it to. Marketing is all about making connections between your brand and customers; you need people to do this. AI is a tool you can use to get insights from your data, write first drafts, set up automations, and answer customer questions.
It’s important to still focus on upskilling your current team and the next generation of marketers so they can create unique strategies and creatives to stand out compared to your competitors.
Common ways people use AI are to analyse customer data, personalise content, automate workflows, support customer service, and brainstorm ideas for campaigns. Depending on the marketer, they may like to use it in different ways. Some like to use it more as an admin tool, while others will use it to help spark their creativity.
Many people feel AI-generated visuals lack authenticity and worry about copyright concerns and the impact of AI on creative industries. On top of this, many AI-generated images have a similar look and feel, which can make brands blend together rather than stand out.
Yes. Australia does not currently have AI-specific legislation, but businesses must still comply with existing laws covering privacy and intellectual property. This means marketers are still responsible for ensuring their AI-generated content doesn't misuse customer data or copyrighted material.