Automated Marketing Campaigns with AI in 2026: How to Prepare

AI isn’t just a ‘nice to have’ for marketers and advertisers anymore. A new report says 91% of Australian marketing businesses are using AI, with 87% of marketers saying it’s now essential to their work.

It seems to be everywhere, so it’s natural to wonder if you can legally use it for advertising and marketing in Australia. 

The short answer is yes, as long as you follow the laws and regulations already in place. 

Australia doesn't have dedicated AI advertising laws yet, but its use falls under broader technology-neutral laws that cover privacy, consumer protection, discrimination, copyright and fair trading.

For example, take targeted ads as part of your marketing strategy. If your AI tool builds ads around someone’s data, you have to collect and use that data according to the Privacy Act of 1988 and the Australian Privacy Principles. Additionally, when creating AI-generated ads, you cannot make any claims or say whatever you wish. Those claims need to follow Australian Consumer Law, which bans any advertising that’s misleading or deceptive.

As you plan for automated marketing campaigns using AI in 2026, the opportunity is huge, but your responsibility is equally important. Whether you’re automating ad targeting, using machine learning for customer segmentation or generating creative content at scale, setting up your systems the right way now will keep you ahead of the curve.

Simply - these  are marketing campaigns that use artificial intelligence (AI) and machine learning (ML) technologies to handle tasks that used to require manual setup. These campaigns:

• Analyse large volumes of data in real time.
  
• Make quick decisions based on trends, such as which ad creative works best or which audience to target next.
  
• Adjust campaign elements like budget, bidding, creative and targeting while the campaign runs.
  
• Scale personalisation and optimisation across many audience segments and formats.

In short, these campaigns have shifted from a ‘set and forget’ approach to a ‘set goals and let the system learn and adapt’ style. AI marketing automation uses machine learning, predictive analytics, natural language processing and other nuanced approaches to go beyond rule-based workflows and make real-time decisions that optimise performance for the best results.

If you’ve been trying to figure out how to automate ad campaigns with AI, it really starts with knowing where automation packs the biggest punch and picking the right channels.

The difference between simple digital tools and true intelligent automation that drives performance and efficiency relies on 7 factors:

• The system doesn’t rely solely on manually defined rules. It uses structured and unstructured data such as behaviour, clicks and purchases to drive decisions.
  
  Example: A tool switches the creative variant mid-flight after learning which image performs best for a specific audience segment.
  

• AI doesn’t sit back and wait. It handles bidding, audience shifts, creative swaps or budget reallocation based on live performance feedback.
  
  Example: For search or display ads, AI uses conversion probabilities instead of fixed manual bids.

• AI enables many creative and message variations, personalised by segment, context,  device and more.

  Example: A social platform’s AI generates ad variants with creative and targeting fine-tuned for each user group. Meta has announced plans to let brands “fully create and target advertisements with its AI tools by the end of 2026”. This means that advertisers will be able to upload a product image and budget, and the AI will generate the ad copy, image or video, pick audiences and recommend spend.

• These campaigns often use generative AI to produce ad copy or visuals, and then adapt creative for different audiences.
  
  Example: AI creates ad versions for multiple locations or audience types without needing manual design work.
  

• Automation spans multiple channels, like search, social, email and display, with AI deciding how to coordinate across them.

  Example: AI can move the spend between channels if performance predictions show better results.

• Over time, the system learns from the results and refines segmentation, creativity, timing and budgeting.
  
  Example: Lead scoring improves automatically as more user behaviour data becomes available.

While most tasks are automated, strong campaigns include checks such as A/B testing, monitoring and ethical standards. Validating through a human lens is important to avoid tiny oversight that can bear big costs.

Here are some key channels where you can find AI automation:

AI manages automatic bidding, dynamic search ads, creative testing and real-time targeting. If a search ad needs a bid boost because someone’s likely to buy, AI handles that instantly.

Platforms are moving towards full ad automation. Meta plans to let advertisers input a product image and budget, then have AI generate the ad and select the audience.

AI figures out the best time to send emails or texts, fine-tunes subject lines, predicts who’ll engage and personalises messages so they land with the people who are paying attention.

AI creates blog or social content, landing page copy and personalised web experiences based on user data.

AI drives automated bidding, predictive targeting and dynamic creative optimisation that adapts ad visuals or copy in real time.

It’s not just about the medium either. AI scores leads, triggers messages and coordinates between channels. For example, it can shoot out an SMS, drop an email or fire off a retargeting ad, whatever makes the most sense in that moment.

AI coordinates the customer journey across multiple touchpoints. If a user ignores an email, it may follow up with a social or display ad.

AI automation is now the engine powering modern marketing. It helps brands work smarter, move faster and create more personalised experiences across every channel. Whether you care about leads, paid ads, engagement or keeping customers coming back, there’s an AI platform out there that can do the heavy lifting.

To help you see what all the fuss is about, we’ve collated some of the best tools for managing automated marketing campaigns with AI in 2026.

HubSpot is a leader in AI for marketing campaigns. With its AI-driven insights and workflow automation, it can automatically score leads, segment audiences, send targeted emails and suggest the best next action for each contact based on campaign goals.

DotDigital’s another strong option, built for data-driven customer journeys. Its AI engine looks at how people engage and what they buy, then triggers automated workflows, picks the best send times and even predicts conversions. The AI segment builder finds your best customers and personalises campaigns for them without needing to set up a bunch of rules.

GumLoop combines workflow automation with AI-driven data integration. It uses machine learning to connect marketing, sales and analytics tools and automates cross-platform workflows. On top of that, GumLoop can analyse campaign performance data, generate reports and trigger optimised actions across email, CRM and ad platforms without manual effort.

Adobe Marketo Engage uses AI to automate lead nurturing, scoring and customer engagement. Its Predictive Audiences feature identifies high-converting prospects, while AI-powered personalisation tailors messages based on user intent. Working with Adobe Sensei, Marketo can keep content fresh and trigger the next step in a customer’s journey, all based on what people are doing right now.

Salesforce’s Einstein AI helps take the hard work out of marketing by automating tasks across email, mobile and social campaigns. It can predict what customers are likely to do next, automatically group audiences, suggest content and even forecast results. Einstein will make it easier for marketers to plan and optimise campaigns with less manual setup and for stronger results.

Google Ads remains one of the strongest platforms for automating AI marketing campaigns, with features like Smart Bidding, Performance Max and Responsive Search Ads. Its AI engine optimises bids, allocates budgets and selects creative combinations based on live performance data.

If you want to get the most from it, working with a Google Ads agency will help you use all this automation without losing your strategic edge.

Meta keeps pushing AI-driven advertising forward. Currently, the Advantage+ suite automates ad creation, placement and targeting across Facebook and Instagram. In the near future, Meta plans to fully automate the whole process. Businesses will only need to provide an image and budget, then AI will build and optimise the campaign from start to finish.

LinkedIn’s Accelerate tool is all about making life easier for B2B marketers. It automatically recommends audiences, budgets and creative assets based on your goals and past campaign data. As it learns, it keeps fine-tuning its targeting, helping to generate more leads. 

To really nail it, work with a LinkedIn advertising agency that knows how to align automation with your brand.

TikTok is also expanding its AI automation through Smart Performance Campaigns, which create ad creatives, optimise placements and adjust targeting based on engagement data. Machine learning helps ensure your content reaches the audiences most likely to interact or convert.

To make the most of these tools, a TikTok advertising agency can help you combine creative storytelling with automated performance optimisation.

Klaviyo’s K:AI platform can automate the majority of email and SMS marketing grunt work. It suggests the best send times, segments your audience by purchase intent and predicts customer lifetime value. With real-time learning, K:AI ensures your messages land at the right moment across email and SMS.

Iterable’s AI-driven Brand Affinity Model helps marketers predict customer behaviour and automate engagement across multiple channels. It can trigger workflows based on user sentiment, channel preferences and purchase likelihood. Iterable’s AI engine keeps refining recommendations to improve conversion rates and campaign results.

Apollo blends AI with sales and marketing automation to help teams identify, qualify and nurture leads more effectively. Its AI Intent Engine predicts which prospects are most likely to convert, while automation tools send personalised outreach at the best times. With data enrichment and workflow automation combined, Apollo helps businesses scale both outbound and inbound marketing without all the hassle.

A lot of marketing teams are still stuck in manual workflows that take up hours. Then there are campaign managers juggling spreadsheets, setting ad bids manually, tweaking copy or guessing when to send an email. 

The result is  missed opportunities. 

Meanwhile, companies that already use AI automation are skating ahead. Here’s how to get started in your business.

Don’t automate just for the sake of it. Look for the big pain points. This could be slow lead follow-up, inconsistent results or wasted ad spend. 

Just say your team can’t keep up with ad bids across platforms. If so, let AI-powered bidding tools handle that for you.

Before you roll out any new tools, look at your team’s workflow and spot where automation fits. Once it’s implemented, make sure everyone receives basic AI training to understand all of it.

For example, when utilising an AI system for automated follow-ups, your sales team must understand the timing and method of contact with leads. Once it’s all up and running, get your marketing, sales and IT teams talking. Everyone should know how automation supports them day to day.

AI works best when it reacts to what your customers do in real life. Set up triggers that automatically react to what users do. If someone downloads a guide, AI can follow up with a relevant email. If they browse a product, it can show them a matching ad.

This kind of setup means your marketing runs smoothly without extra effort, and customers receive the messages that make sense to them.

AI does its best work when your tools are connected. Link your CRM with your email, analytics and ad platforms so they can share data.

That means you can reach people who are much more likely to buy, which will improve your results. If setting it all up sounds complicated, you can work with an AI adoption company like Rocket, to help integrate everything properly so it runs without a hitch.

AI lets you automatically tailor messages for each segment. Use automation to change up subject lines, calls to action or images based on what users like or how they behave. It’s a simple way to make your marketing feel more relevant.

For instance, eCommerce brands can show returning customers personalised product recommendations, while B2B marketers can adjust messaging based on industry or company size.

Managing ads manually takes time and can be hit or miss. Platforms like Google’s Performance Max and Meta’s Advantage+ can analyse results and move your ad spend to where it works best.

Instead of constantly testing placements yourself, let AI pause ads that aren’t performing, redirect spending to more relevant audiences and even spin up fresh ad copy that converts more leads.

Marketers spend a large portion of their day reporting. AI analytics platforms can automatically collect, clean and visualise performance data from all channels.

You can set up dashboards that update themselves every day. No more copying numbers into spreadsheets. Just open it up and see your cost per lead, click-through rates, conversions, all laid out and ready to go. Some tools even go a step further, predicting which of your campaigns will do best based on what’s been working lately.

While AI can handle much of the workload, human judgement is still essential. Keep humans in the loop to review AI-generated content, check for errors or bias and make sure campaigns match brand standards and compliance requirements. This is even more important in regulated industries, where nothing should go live without a real person’s approval.

Our paid media specialists understand that adding a human touch matters because AI often defaults to a standard tone or style of grammar. With so many brands relying on it, sticking to your brand guidelines, tone and personality is what helps your content feel different and stand out from competitors.

Trying to automate everything at once can overwhelm your team and lead to mistakes. Start with one tool that makes an immediate impact, such as automated lead scoring or optimised email send times. Once your team feels confident with one automation, you can gradually introduce more to build smarter, more efficient workflows.

At Rocket, we’ve seen this approach work well. For example, we built an automated email alert system for bidding that flags when campaigns are overspending or underspending, helping teams react faster. We also use Supermetrics to create live campaign and ad logs so clients can see exactly what’s running at any moment.

The leads to small wins that boost faith in AI and give you the data needed to make choices about additional automation tools in the future. Over time, you’ll start to see these improvements resulting in stronger performance and ROI. That’s how you can really make AI work for your marketing team. 

AI’s changing the way brands connect, create, and drive results. So, what’s coming up? 

• AI-driven search and discovery is taking over: Tools like ChatGPT, Gemini and Perplexity are where people go to find answers now. Getting your brand noticed on these systems matters just as much as ranking high on Google. (Read more in our guide: The Impact of AI on SEO)
• Hyperpersonalisation is finally real: That copy-paste marketing style is outdated. Now you can get content, offers and experiences built just for you, exactly when you want them with AI tools that are getting better at their craft every day.
  
• Trust and transparency will lead the way: People care about trust. They want brands to be upfront, especially since AI’s pretty much everywhere these days. Honest brands that own up to using AI ethically  will be the ones people stick with.
  
• Predictive and autonomous optimisation: Marketing tools are getting smart enough to tweak campaigns on their own. They’re watching the data and making changes without you having to lift a finger.
• Stronger human–AI collaboration: People still run the show. AI’s powerful, sure, but the best marketers use it to get more done, not to lose their own creativity or gut instincts. People who mix AI with real empathy and smart thinking will lead the pack.

Not every AI fad is worth chasing. Choose one thing to automate that aligns with your goals and start there. Make sure your team feels good about using AI too. That’s where it all starts.

And let’s be clear, automation isn’t here to take anyone’s job. People still matter. It’s about freeing marketers up so they can focus on what they do best: creative ideas, smart strategy, real relationships and genuine learning.