AI marketing automation: Smarter campaigns, faster execution, better results

Brands today have no shortage of data, customer expectations, or goals they want to achieve. For marketing teams aiming to scale personalization, improve customer retention, and boost engagement, AI marketing automation is a powerful breakthrough.

AI marketing automation is an advanced approach that not only streamlines tasks, but uses predictive insights to personalize customer journeys, optimize campaign performance, and free marketers from manual guesswork.

In this guide, we'll discover what AI marketing automation really means, how it evolved from simpler rules-based systems, and how platforms like BrazeAI™ are helping marketers achieve smarter campaigns, faster execution, and better results.

Contents

• What is AI marketing?
• How AI for marketing automation works to streamline campaigns
• Key capabilities and use cases of AI marketing automation tools
• Implementing AI marketing automation: Best practices for marketers
• Common misconceptions about AI in marketing automation
• Future trends shaping AI in marketing automation
• Why BrazeAI™ stands out among AI marketing automation tools
• FAQs about AI marketing automation

What is AI marketing?

AI marketing automation refers to software solutions that combine traditional marketing automation capabilities, like campaign scheduling, segmentation, and triggered messaging, with artificial intelligence (AI) and machine learning. Instead of relying solely on predefined rules, AI marketing automation tools learn from customers as they change to dynamically personalize interactions and recommend the best next actions for each customer.

Where traditional automation often relies on what a customer did yesterday, AI-powered marketing automation can adjust as they change and predict what they'll do tomorrow.

This smarter approach lets marketers:

• Predict customer behaviors (like churn or conversion likelihood)
• Personalize content, timing, and channels as customers evolve and move in and out of lifecycle stages
• Enhance targeting precision for better ROI
• Optimize campaign execution without manual intervention

How AI for marketing automation works to streamline campaigns

AI marketing automation removes friction throughout all stages of both the brand’s and the customer’s journey. Instead of relying on hard rules or waiting on post-campaign analysis, AI takes real-time customer behavior, historical patterns, and predictive insights and uses them to guide what happens next.

Here’s how the process typically works behind the scenes:

1. Data collection: AI pulls in behavioral, transactional, and engagement data from multiple channels—like email, mobile, web, in-app—and sources.
2. Pattern recognition: Machine learning models identify trends across this data: Who’s likely to convert, who’s slipping away, which products resonate.
3. Decisioning: Based on those patterns, the system determines the best message, timing, and channel for each customer, without needing manual rules.
4. Execution: Campaigns are delivered automatically, adapting in real time as users respond.
5. Continuous learning: With each interaction, the AI can get smarter and refine its predictions to improve performance over time.

For marketers, this workflow means less time spent configuring logic or combing through dashboards and more time focusing on creative, strategy, and experimentation.

AI vs. traditional marketing automation: What's changed?

Traditional marketing automation tools rely on fixed logic, For example, “If a customer does X, then trigger Y.” These systems are only as good as the rules you write and the time you have to maintain them. For example, edge cases and other exceptions require manual setup and ongoing optimization.

AI-powered automation shifts that burden. Instead of requiring marketers to map every possible journey, machine learning models recognize behavioral patterns, predict outcomes, and decide what to do next—in real time.

Here’s how the shift looks side-by-side:

This shift reduces manual work, improves agility, and makes it possible to personalize across massive datasets—without rebuilding every journey from scratch.

Benefits of AI in marketing automation

Yes, AI brings speed and precision, but it also takes on monotonous and manual tasks that can strain a marketer. Here are some of the deeper benefits of AI in marketing automation that go beyond the obvious.

Smarter experimentation, on autopilot

AI doesn’t need weeks of testing to spot what’s working. It adjusts content, timing, and strategy on the go, so you can run constant experiments without constantly managing them.

Strategy that adapts in real time

Instead of locking campaigns into predefined flows, marketers can define goals (like retention or upsell) and let AI figure out how best to achieve them, adapting paths based on live engagement signals.

Frees up humans to do human work

When AI handles the execution and optimization, marketers can focus on creative, brand storytelling, and new campaign ideas, not manually adjusting campaigns or rebuilding logic.

Surface-level insights become deep discovery

AI confirms what you suspect but also can surface patterns and segments you hadn’t thought to look for. That opens the door to new strategies, not just better-tuned versions of the old ones.

Key capabilities of AI marketing automation tools

AI marketing automation is only as good as the tools behind it. BrazeAI™ was built to help marketers move from manual workflows to intelligent, adaptive campaigns that improve with interactions. Here’s how it works:

Upday: 528K users reactivated with Predictive Churn

Utilize machine learning models to identify customers at risk of churning before it happens. This proactive approach allows marketers to trigger re-engagement campaigns tailored to individual behaviors, prioritizing resources toward users most likely to return.​

Use case: Upday, an independent, free news app, wanted to re-engage inactive users. They leveraged Braze Predictive Insights to target users who hadn’t started a session in 30 days, identifying that push messaging was the most likely channel that users would re-engage with. It led to them reactivating 528k users.

BlaBlaCar: 30% lift in books with Action Paths

With Action Paths, marketers define a goal—such as a completed purchase or feature activation—and BrazeAI™ dynamically selects the best message, channel, or timing based on real-time user behavior. This adaptive approach streamlines multi-step journeys without manual logic.​

Use case: BlaBlaCar, a carpooling platform, implemented Action Paths in Braze Canvas to automate cross-channel journeys, sending personalized messages to people at optimal times, based on different actions they had taken, like booking a trip or searching for a carpool. This strategy led to a 30% increase in bookings and a 48% uplift in click rates. ​

AI Item Recommendations: Predict what they’ll love

Recommend content, products, or offers that each customer is most likely to engage with, based on their behaviors and preferences. This predictive personalization can enhance conversion rates without additional creative lift.​

The Fork: Creative refresh with AI Copywriting Assistant

Braze AI Copywriting Assistant, powered by OpenAI, helps marketers swiftly generate new creative copy for engagement campaigns. This tool aids in brainstorming, speeding up time to launch and maintaining brand consistency.

Use case: The Fork, a restaurant reservation platform, utilized the AI Copywriting Assistant to diversify their messaging, finding new ways to communicate concepts and inspire fresh approaches. Raffaella Accogli, Global CRM Manager, Activation at The Fork, says “I felt like I always used the same words, the same expressions, the same concept. With the Braze AI Copywriting Assistant, I can find a way to talk about the same concept using different words. And, it provides inspiration to develop new approaches.”

KFC South Africa: Faster visuals with AI Image Generator

The Braze AI Image Generator empowers marketers to create campaign imagery quickly by inputting brief descriptions. This tool helps reduce dependencies on in-house design teams and accelerates campaign launches.

Use case: KFC South Africa created holiday campaign images using the AI Image Generator, enabling rapid development of visuals aligned with their brand. ​

Collectively, these tools enable marketers to deliver personalized, timely, and effective campaigns, enhancing customer engagement and driving measurable results.

Personalized Variant

Braze Personalized Variant is designed to determine the message for each individual based on their unique behaviors, preferences, and attributes. It automates personalized messages to each individual intended to increase engagement and conversions for each campaign.

Personalized Paths

Personalized Paths automates journeys so that each customer receives the message copy, creative, channel, offer, and more they’re most likely to engage with throughout their journey—all with a simple toggle.

Implementing AI marketing automation: Best practices for marketers

AI can feel complex from the outside, but when it’s built into tools marketers already use, it becomes far more approachable. Whether you’re part of a large team with data science resources or a lean CRM crew, the path to AI-powered automation starts with a few focused shifts in how you plan, build, and launch campaigns.

Optimizing your AI strategy with data science support

If you have access to analysts or a data science team, you can go beyond plug-and-play and shape your AI tools to your business. That might look like:

• Training custom models to predict specific behaviors that matter to your brand
• Setting up experiments to test model outputs against business-defined goals
• Analyzing model performance over time and tuning strategies based on real outcomes

The magic here isn’t just in the tech—it’s in the collaboration. When marketers and data specialists work together, AI becomes a strategic lever, not just a tool.

Getting started without a dedicated data science team

No data science? No problem. Platforms like Braze come with intelligence already built in:

• Use pre-trained models like Predictive Churn without writing code
• Tailor the journey to each customer with Personalized Paths and Personalized Variant
• Personalize experiences with AI Recommendations and Connected Content

Focus on one or two clear use cases, like onboarding, re-engagement, or upsell flows, and build from there.

General best practices for success

No matter your team size or tech stack, these principles can help you get more from AI automation:

• Start small, scale fast: Choose one high-impact use case to prove value, then expand.
• Stay close to your goals: Let customer outcomes–not shiny features–guide your AI use.
• Test and learn constantly: AI thrives on feedback. Use testing to shape and sharpen performance.
• Collaborate across teams: Involve product, data and support teams early. AI works best when it’s aligned with the full customer experience.

Common misconceptions about AI in marketing automation

AI has earned a lot of buzz. And with that buzz comes a few persistent myths. Let’s clear the air.

“AI will replace human marketers”

AI doesn’t replace strategy, storytelling, or creative thinking—it enhances them. Tools like BrazeAI™ are designed to handle repetitive decisions and surface insights faster, so marketers can focus on big-picture goals and brand voice.

“You need a data science team to use AI”

While advanced teams can do more with custom models, many AI marketing automation tools come ready to use. Features like Predictive Churn and AI Recommendations are plug-and-play, built for marketers, not machine learning engineers.

“AI is only for enterprise companies”

You don’t need millions of users or a massive tech stack to benefit from AI. Smaller teams can start with narrow, high-impact use cases—like optimizing onboarding flows or personalizing product recommendations—and scale from there.

“You can’t trust AI to make decisions”

Good AI doesn’t operate in a black box. BrazeAI™ surfaces explainable insights and gives marketers control, so you can test, tweak, and oversee outcomes while still moving faster than before.

Future trends shaping marketing automation AI

As technology evolves, so does the opportunity to create richer, more responsive brand experiences. Here’s our predictions for what’s on the horizon.

Hyper-personalization, powered by predictive modeling

We’re moving beyond broad segments. Future AI models will dig deeper into real-time behaviors, emotional cues, and intent signals, delivering content and timing so tailored, it feels truly individual.

Creative collaboration between humans and AI

AI won’t replace your creative team, it’ll become part of it. Expect more intuitive tools that help marketers test messaging angles, generate visuals, and brainstorm content when it's needed, while staying true to brand voice and identity.

Dynamic journeys that shape-shift in real time

Static workflows are fading. The next wave of journey orchestration will be fully fluid, driven by evolving goals, user context, and AI logic that can rebuild a path mid-stream based on performance.

AI as a strategic partner

The future holds more strategic marketing. AI will help teams identify new opportunities, test ideas faster and shift from campaign planning to lifecycle thinking.

For marketing teams ready to evolve, an AI toolkit will help define the next generation of brand loyalty and business growth.

Why BrazeAI™ stands out among AI marketing automation tools

BrazeAI™ combines real-time intelligence, marketer-friendly design and deep cross-channel orchestration in a way that few platforms can match.

Here’s what sets it apart:

Built for action, not just analysis

BrazeAI™ generates insights and turns them into outcomes. Whether it’s selecting the right message variant, surfacing churn risks, or recommending the next best product, insights can be activated inside your campaign workflows.

Designed for marketers, not machine learning engineers

No complex setup. No data science team required. Tools like Predictive Churn, Action Paths, AI Recommendations, and the AI Copywriting Assistant are intuitive and ready to use, helping marketers launch smarter campaigns faster.

Fully integrated with real-time engagement

AI capabilities are embedded within Braze Canvas for journey orchestration. That means insights can be applied across email, push, in-app, and more, without jumping between systems or waiting on syncs.

Personalization without compromise

From dynamic content to image generation, BrazeAI™ helps marketers create 1:1 experiences at scale, without overloading creative teams or sacrificing brand quality.

FAQs about AI marketing automation

How is AI used in marketing automation?

AI is used in marketing automation to analyze customer data, predict outcomes, and determine the best next action for each user. This can include sending the right message at the right time, recommending products, detecting churn risk, and optimizing entire customer journeys without manual setup.

What are examples of AI-powered automation tools?

Examples of AI-powered automation tools features like predicting churn, recommending products, and automatically personalizing journeys as customers change.

How does AI improve personalization and targeting?

AI improves personalization and targeting by using real-time behavior and historical data to understand what individual customers are likely to do next. This allows marketers to serve content, offers, and messages that are more timely, relevant and effective–without relying on rigid segments or rules.

What is the difference between traditional and AI-based automation?

The difference between traditional and AI-based automation lies in flexibility and intelligence. Traditional systems rely on predefined rules and static segments. AI-based automation can adapt in real time, learn from customer behavior, and continuously optimize campaigns to improve results with less manual effort.

Forward-Looking Statements

This blog post contains “forward-looking statements” within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995, including but not limited to, statements regarding the performance of and expected benefits from Braze and its products and features. These forward-looking statements are based on the current assumptions, expectations and beliefs of Braze, and are subject to substantial risks, uncertainties and changes in circumstances that may cause actual results, performance or achievements to be materially different from any future results, performance or achievements expressed or implied by the forward-looking statements. Further information on potential factors that could affect Braze results are included in the Braze Annual Report on Form 10-K for the fiscal quarter ended January 31, 2025, filed with the U.S. Securities and Exchange Commission on March 31, 2025, and the other public filings of Braze with the U.S. Securities and Exchange Commission. The forward-looking statements included in this blog post represent the views of Braze only as of the date of this blog post, and Braze assumes no obligation, and does not intend to update these forward-looking statements, except as required by law.