The recipe for successfully implementing AI in marketing only has a few components, but they’re all essential to get the end product right. First, you need a culture of experimentation and flexibility; like an oven heated to the proper temperature, that culture will be your foundation for success.
Second, you’ll need to bring AI considerations into your strategic planning approach. Think of this like mixing all your ingredients together properly. AI needs to be aligned with strategic goals, not just thrown on top of the pile of things you want to do next week.
With both these foundations in place, marketers can blend in the final piece: effectively experimenting with AI. Just like a perfect recipe can be ruined with too much time at high heat, a lack of experimental rigor can derail the best laid AI plans.
Over time, by tracking metrics and continuously optimizing, AI can be a recipe for serious ROI for your entire organization.
We know AI is already revolutionizing every aspect of our work. For marketers, it’s changing how strategies are developed, improving efficiency, enhancing customer engagement, and on and on.
But chances are you’re hearing about all the ways AI can benefit your marketing more than you’re actually experiencing those benefits.
Surveys show that most marketers are implementing AI in some capacity, but it’s still mostly experimental and scattershot.
Sadly, this is a tale as old as time. A new technology comes along and everybody needs some time to understand the best way to implement it (penny farthing bikes anyone?) so they hedge their bets.
This is a particularly big challenge for larger organizations that may have more complex processes, compliance issues, and set ways for doing things.
That same research we just cited actually shows that 44% of companies are waiting for more established solutions before implementing AI. That’s hardly surprising when we have so many examples of terrible uses of AI in marketing to caution us from moving too quickly.
But waiting too long can be just as risky as jumping in too soon; marketers have to find the right balance between innovation and risk.
Fortunately, there are ways to start getting real value from AI in marketing without ending up on a “worst of” compilation. By taking a human-driven and thoughtful approach, you can begin implementing AI into your workflows and seeing genuine ROI for you and your entire organization.
The first thing to remember is that AI is a tool like any other. Just like a great car can efficiently and comfortably take you to your destination… or to the bottom of your nearest lake, AI itself isn’t a silver bullet, regardless of how it's used. How you implement it makes an enormous difference.
That begins with aligning AI initiatives with your overarching business goals. Whether you want more robust lead generation, faster content creation, more personalized customer engagement, or something else entirely, AI should be taking you toward a clear objective.
You’ll want to start by thinking about your current capabilities, strategic goals, data infrastructure, and organizational culture. This understanding needs to be the foundation of your AI integration approach.
So instead of beginning to integrate AI into your marketing piecemeal, you start by bringing it into a quarterly planning session. This gives time and space for concerns to be raised, questions to be asked, and will generally produce a more thoughtful and impactful approach.
For example, if you simply tell your marketers to begin using AI, they might use it effectively, or they might generate poor quality work and compliance headaches. This approach is more likely to amplify your existing weak spots rather than solve challenges or open new opportunities.
Compliance scares far too many marketing functions away from AI, but there are ways to approach implementing AI that won’t give your compliance team an ulcer.
First, understand what particular laws and regulations apply to your work. That might mean GDPR, CCPA, HIPAA, CAN-SPAM, etc. Here it can be helpful to work with someone like a compliance team to make sure you know what applies before you start designing experiments.
Then, you may want to consider addressing questions of bias or explainability.
These won’t always present real issues, but it’s worth thinking about them before fully implementing AI to get ahead of any potential problems. That said, you should also put together a basic response plan in the event you do have an incident like a data breach, compliance violation, or other AI error.
Of course, no matter what rules apply to your marketing department, everyone using AI should know to never input sensitive information into an AI tool.
If your organization is large enough to build an in-house solution, however, you can potentially use such tools with sensitive information.
In any case, some training and guidance in compliance and data governance is essential before implementing AI in a marketing function.
Armed with a solid understanding of your strategic goals and relevant compliance issues, you’re ready to select the right AI tools for your specific needs. (Note: The suggestions below are merely suggestions! AI tools and their capabilities are changing week by week, so research what’s available whenever you’re ready to get started.)
As of writing (early 2025) these are some of the best AI tools available for specific marketing use cases.
Once you’ve selected the tools you’ll use, you can begin integrating them into your marketing workflows. Here are some examples of how you can do that.
One of the easiest ways to implement AI in marketing is simply to automate basic tasks.
For example:
While AI can handle many tasks on its own, often its greatest impact can be enhancing the capabilities of human marketers.
These are some ways it can do that:
AI’s ability to quickly analyze information to make personalized recommendations at scale makes it a valuable tool for enhancing customer experience and moving us closer to one-to-one marketing.
Here are some ideas for how AI can do that:
Just note that these are just a few suggestions based on the capabilities of today’s AI tools; be sure to consider what’s available when you’re looking at implementing AI for yourself.
Because its capabilities are changing so quickly, fully implementing AI in your marketing requires constant experimentation and adaptation. The best way to reliably make sure that happens is by building an Agile mindset and culture within your marketing function.
First, Agile culture is built around continuous improvement.
Teams come together every few weeks to discuss what’s working, what isn’t, and brainstorm ideas for improvement. Those ideas are then rigorously tested before the next meeting.
This system of continuous improvement is ideally suited for implementing AI, because it creates a culture and structure for regularly testing and improving its use.
Another key way Agile ways of working are ideally suited for implementing AI is their focus on stakeholder value. It’s easy for marketers to use AI in ways that save them time, but end up producing worse outcomes for the organization.
Focusing on understanding what stakeholders like leaders and customers want and using AI to deliver that value helps ensure marketers remain focused on implementing AI in impactful ways.
A classic mistake organizations make when implementing AI for the first time is leading with the AI itself. In effect, this leads to cases where shiny new tools are plugged into the same old ways of working, resulting in poor results.
Instead, by leading with a culture shift around Agile experimentation, you can get marketing teams ready to effectively use AI to achieve strategic goals. That culture shift comes from following Agile principles.
Agile principles that will help in implementing AI
These principles were developed long before AI came to marketing, yet they’re ideally suited for the task of implementing AI in marketing today.
They encourage marketers to adapt AI to their unique needs and capabilities instead of simply following what others have done. They encourage rapid but considered response to change, adapting to new AI capabilities through experimentation.
But building an AI-ready Agile culture starts from the top.
All the elements of an AI-ready culture, from experimentation to flexibility, require confidence.
If marketers are worried about whether a particular use of AI is going to get them fired, they’re not going to feel comfortable fully implementing AI in their work. Such confidence begins with leaders setting an example.
That example should include using AI themselves, but also being open and honest about the process. Leaders should talk about mistakes and lessons learned, and make it clear that everyone is learning and adapting to this new technology together so they can establish psychological safety within their organization.
In addition, the servant leadership style is tremendously useful during times of rapid change.
By focusing on supporting teams working on implementing AI instead of simply commanding them to, leaders get:
Leaders also play an important role coordinating AI efforts between IT, marketing, and other departments to ensure cohesive implementation.
But setting an example is only the first step.
Training and education is vital for leaders and team members alike.
While training in Agile fundamentals or leadership will help equip marketers to effectively use AI, targeted training built around implementing AI in marketing is ideal.
That initial training can offer foundational principles and skills around things like experimentation, flexible strategic planning, and customer-centricity. AI-centered training can then build on that foundation by offering things like AI ethics checklists, templates, skill maps, and integration guides.
From there, it’s time to begin implementation.
This is where the vast majority of your time and efforts (around 70% in fact) should be focused!
Plenty of strategies for implementing AI sound great on paper, but falter when applied to your specific circumstances. That’s why most of your time and efforts should be spent actively adapting and implementing these strategies to your workplace.
Even when you find something that works, you can’t become complacent.
No strategy for implementing AI in marketing is going to work indefinitely. AI technology and the business goals marketing serves are both changing at breakneck speed.
Keeping up with those changes requires consistent measurement and optimization of AI-driven marketing processes.
So look back at the key metrics you tied to your strategic goals and track them rigorously. Structure experiments to see how AI impacts them and get into a pattern of regularly testing ideas and implementing new learnings.
Remember, this is a continuous process, not something you’ll finish in a few months. AI advancement isn’t going to slow down, so your optimization around it can’t either.
Implementing AI in small ways into existing marketing processes is quite easy. The challenge comes with wider-scale AI integration.
Here, it’s more important to think strategically about what you want AI to achieve, compliance, tools, etc. Depending on the size, complexity, culture, and level of regulation in your industry, that can be a difficult process.
The best way to approach implementing AI is with strategic goals in mind. This enables you to focus your efforts on maximizing the impact of AI on your organization.
Experimentation is also crucial, both to understanding the impact AI is having and ensuring your use evolves along with AI’s capabilities.
The first phase of implementing AI is considering your strategic goals.
Next, you’ll want to think about compliance and regulatory barriers that might impact how you implement AI.
After that, you can begin testing and experimenting with using AI to achieve your goals.
That final step should then repeat with time as you further hone and refine your approach.
First consider the goal of the project. Then, look at whether and how AI can help in achieving that goal. For example, by automating processes, analyzing large amounts of data, or simply answering important questions you may have.
Once you’re ready to start implementing AI in your projects, be sure to track metrics to understand its effect. Then, iterate and experiment to improve that performance over time.
While AI is set to replace some jobs centered around low-skill and repetitive tasks, within marketing it’s set to enhance the capabilities of individual marketers. For example, by automating analysis, managing campaigns, and generating basic content AI can augment and accelerate critical marketing work.
The foundation of a successful strategy for implementing AI in marketing begins with culture.
From leaders down to team members, you need people who are ready to be open, creative, and experimental in determining the most effective way to use AI to achieve strategic goals.
Armed with the right culture, the next step is considering AI implementation in your strategic planning. Think about your most important strategic goals and share them with teams who can begin experimenting with using AI to achieve them.
At that stage, it’s all about testing, learning, and optimizing.
If you’re feeling stuck at any stage of this process, our team can help answer your questions and get your team moving forward towards AI success.