Using AI for marketing efficiency: Dos and don'ts

Let’s get one thing straight: AI is not wiping out your entire marketing team (unless there's a job doing manual data entry for 8 hours a day—then, maybe). But what it is coming for? Your team’s wasted time, bloated production timelines, painfully slow feedback loops and other bottlenecks.

And honestly, we’re into it. Because operational efficiency is kinda our bread and butter. From shaving hours off campaign production to automating the kind of low-value tasks that make your soul quietly leave your body, AI has real potential to *supercharge* how marketing teams work.

But as with all powerful tools, it’s not just about using AI—it’s about using it well. So, let’s talk best practices.

✅ Dos: How to use AI for marketing efficiency

1. Do: Automate repetitive, low-value tasks

   With the right AI tools and AI agents, you and your team and skip the grunt work and get straight to the good stuff.

   Less of the routine, loading-the-dishwasher-type tasks like scheduling, tagging, and data entry (because sigh, they do need to be done), and more time freed up for strategy, creativity, and generally good marketing sh*t that doesn't hand out headaches or boredom.

   Example prompt: "Create a monthly content calendar based on these campaign themes and auto-schedule posts for LinkedIn and Twitter"
   

2. Do: Speed up content workflows

   
   Processes are never perfect—we know it, you know it, your aunt's dog's mum knows it.
   
   There is always room for improvement, and if it's an improvement by way of speed that you're looking for (which we can imagine, is one of your three wishes at least), AI can help. Not only can it pick up on the repetitive, automated tasks, AI tools can cut down on production time of drafting emails, ad copy, and campaign messaging.
   
   The best bit? You won't sacrifice the quality of content (but only if you make sure human review is in the workflow).
   
   Example prompt: "Generate three variations of Facebook ad copy for a B2B SaaS product with a professional but bold tone"
   
   
   

3. Do: Data analysis and reporting

   
   Save money on your own and your team's next opticians trip by getting AI to do the data crushing for you. AI tools can quickly (and with no complaints or human error) process large volumes of performance data, and identify key trends and actionable insights to help with decision-making.
   
   Because decision-making is nothing if you've not got the data to back the buy-in.
   
   Example prompt: "Analyze these last 6 months of campaign data and identify the top-performing channels and content formats"

4. Do: Get experimentation suggestions

   
   We're living in a culture of experimentation. Why? Because we're in competitive times, and our audiences are always looking for the next big thing. We've got to capture their attention, and keep their attention with our marketing efforts. This takes testing, learning, and testing some more.
   
   Use AI to (pretty rapidly) come up with new variations, suggest improvements to existing content, and make iterations based on any performance data you input into the tool.
   
   Example prompt: "Write two alternate versions of this email CTA to A/B test for higher conversions"
   
   

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5. Do: Boost cross-team collaboration

   
   Ah, the age-old problem of misalignment with other teams. causing confusion, clashes, and duplicated work. But yes, AI can indeed help with enhancing cross-functional collaboration across your company.
   
   Use your AI tool to automatically generate campaign briefs, meeting recaps, creative outlines, and other types of relevant documentation. This way you can make handovers, catch-ups, and overall alignment way more streamlined, and move faster as a result.
   
   Example prompt: "Summarize this kickoff call transcript into a one-page campaign brief with goals, timeline, and deliverables"

❌ Don'ts: How NOT to use AI for efficient marketing

1. Don't: Confuse speed with strategic value

   Risk: Speed and faster content production is all well and good, but don't go prioritizing fast outputs over meaningful outcomes or quality content. Repeat after us: It 👏 ain't 👏 worth 👏 it.

   
   Solution: Instead, Use AI to accelerate execution—but (please) always tie outputs back to business goals and customer needs with human strategy and oversight.

2. Don't: Over-automate without change management

   
   Risk: If you start using AI across your content creation workflow without well-thought-out change management, you may face issues like resistance from your team, broken or inconsistent workflows (an Optimizely worst nightmare, FYI), and a lack of clarity around responsibilities and accountability.
   
   Solution: Involve your team in AI adoption, and make sure you provide training and align tools with clear process changes—so you don't make your martech stack even messier.
   
   

3. Don't: Rely on AI for campaign strategy

   
   Risk: As much as AI can save you time, it cannot strategize for your marketing team or brand better than you can. With no real input, you risk generic campaigns with no differentiation or strategic depth.
   
   Solution: Keep strategy human-led; only use AI for inputs and execution support... not final decision-making, you got that?
   
   

4. Don't: Go without AI governance or human oversight

   
   Risk: Inconsistent messaging, brand damage, or compliance issues are three things you don't want, right? But they're three things you're going to get if you don't have a savvy AI governance framework in place.
   
   Solution: Make sure you've set strict guardrails for your AI usage and content production—define what AI can and can’t do within your marketing org, and ensure human QA is built into your workflow.
   
   

5. Don't: Assume AI will solve process problems for you

   
   Risk: If it seems like your marketing team is broken then layering automation over the top of inefficiency is going to cause you more issues.
   
   Solution: Audit and streamline your marketing processes first, then use AI to scale what’s already working, or what can be automated.

AI for marketing efficiency best practices

• Start small: Focus on quick-win use cases first, then scale once you’ve proven the value.
• Keep humans involved: Always include human review to ensure quality, brand alignment, and trust.
• Embed into workflows: Integrate AI into existing processes instead of layering it awkwardly on top.
• Involve your team: Get buy-in early by training, testing, and sharing wins across the team.
• Define clear rules: Set guardrails for when, how, and where AI should be used to avoid chaos.

Using AI for marketing efficiency: What's next?

True AI magic happens when marketing teams use it with intention: to remove friction, save time, and create space for higher-value work (the kind that actually gets the results you're looking for).

By following these best practices—and avoiding the common pitfalls—you’ll be in a much better position to boost efficiency without sacrificing strategy, creativity, or control.

Check out our full content series that explores how to use AI at every stage of the content and marketing lifecycle—from planning and ideation, all the way to reporting and repurposing. Dive in here:
AI across your content lifecycle.

Because AI is only as good as the process it supports... and we’re here to help you build a damn good one.