The 5 Top AI Challenges in Marketing (and How to Solve Them)
AI was supposed to make life easier.
Your team’s churning out more content than ever—but half of it reads like polished-up garbage. It’s actually taking longer to manage, edit, and approve. You’ve got tools for everything, but workflows are breaking. Everyone’s experimenting, but no one’s aligned. And somewhere along the way, “efficiency” started turning into extra work.
Sound familiar?
You’re not alone. As AI shifts from shiny new toy to everyday tool, marketers are coming across a new wave of problems. The challenges of AI in marketing aren’t just technical—they’re organizational, strategic, and (at times) downright frustrating.
In this post, we’re breaking down five of the most common AI challenges in marketing—plus what to actually do about them.
1. You’re using AI, but your content still sounds like everyone else’s.
AI has made it easier to create more content, faster—but that speed often comes at the cost of originality. Many brands are unknowingly publishing bland, robotic material that blends into customers increasingly crowded feeds instead of standing out. If your content isn’t reflecting your brand voice, it’s not AI’s fault—it’s yours.
How to fix it:
Codify your brand voice (and teach it to the AI)
Document your brand tone, values, vocabulary, and personality traits. If it isn’t clearly defined, then AI isn’t going to stand a chance trying to replicate it. Create a simple brand voice guide with examples of on-brand content, and feed it directly into your prompts (or use it to fine-tune custom GPTs).
Stop settling for first drafts
AI is fast-but it isn’t one-prompt-and-done. Whether you’re drafting a campaign brief, summarizing research, or using an AI article generator for content creation, treat the output as a starting point, not a finished product. Layer in nuance, specifics, and personality. Ask yourself: “Would only our brand say it this way?” If not, keep editing.
Ditch general prompts
Prompts like “write a blog post about SEO trends” are guaranteed to sound like everyone else (and get flagged as poor quality content by the SERPs). Instead, provide AI with specifics on your audience, tone, stance, preferred structure, and past content examples.
2. You’ve added five new AI tools (and broken three workflows)
AI tools promise efficiency—but too many marketers are piling them on without a plan. The result? A cluttered tech stack, broken processes, and teams spending more time switching between tools than actually driving results. What was supposed to streamline your work is now slowing it down.
How to fix it:
Audit your stack
List out every AI tool in use across teams. What does the tool do? Who’s using it? What problem is it solving? You might discover you’re paying for tools with overlapping functions, or worse, tools that no one’s using effectively. Eliminate overlap and don’t be afraid to cut an underperforming tool.
Automate strategically
Identify high-effort, low-value tasks first. Don’t just add AI onto what you already do. Sketch out your ideal workflows (ex. blog production, campaign planning), then identify the exact steps where AI can save time or add value.
Designate tool owners and document use cases
Every AI tool in your stack should have an internal champion. That person owns training, onboarding, and documenting best practices. Centralize this in a shared AI playbook so your team doesn’t waste time reinventing the wheel.
3. You’re automating the wrong things.
Marketers love efficiency. But, if you’re automating content ideation while still manually pulling reporting every week, something’s off.
Don’t rush into automating whatever looks easiest. Many of the biggest problems with AI in marketing come from trying to automate without clear priorities—focus on what actually drains time or slows down results. Take a step back to map where AI can actually make the most impact for your organization or team.
How to fix it:
Track your team’s time
For one week, have team members log the top 3 tasks they spend time on each day. Yes, you’ll probably get pushback for asking everyone to do this, but it’s critical to be able to spot patterns.
Rank tasks by impact v. effort
Create a simple grid comparing the impact and effort of tasks. Low effort/high impact tasks (like repurposing blog content into social posts) are your quick wins. Avoid automating complex, high-effort processes until you’ve built a foundation.
Create reusable prompt templates
If your team is manually writing new prompts every time, that’s another inefficiency. Build a prompt library for repeated tasks (ex. social caption generation, title variations, post outlines) and store them in a central doc or tool.
4. AI isn’t helping you grow.
Prompting is great, but does it help you find new market opportunities? When you only use AI to rephrase what you already know, you miss its potential to surface what you don’t. AI growth comes from uncovering new customer needs, whitespace opportunities, and better strategic bets (not from just speeding up your blog calendar).
How to fix it:
Shift your AI prompts from “create” to “investigate”
Instead of “write a post about X,” ask “what unmet needs do customers in [niche] have?” or “how are competitors positioning around [trend]?” Use AI as a research analyst, not just a writer.
Feed AI real data.
Input CRM insights, top-performing content, customer reviews, or past campaign metrics. Then ask AI: “What patterns stand out?” or “What’s under-leveraged in our current strategy?” That’s where real opportunity starts to emerge.
Involve AI early in the funnel
Most teams use AI when they’re already locked into a plan. Instead, bring it in during brainstorming, audience mapping, or campaign planning to widen your thinking before narrowing your execution.
5. Everyone’s experimenting and nobody’s aligned
It’s not just about using different tools—it’s that every team has a different vision of what AI is for. Content sees it as a speed hack. SEO wants better scale. Product wants to automate support. And leadership just wants to say “we’re using AI” in board meetings.
Without a shared north star, AI efforts drift. One team’s success story doesn’t ladder up. Another team’s failures get repeated. Everyone’s moving—but not together. This isn’t a tooling issue. It’s a strategic alignment issue.
How to fix it:
Define your AI mission
Get leadership and team leads together and agree on the role AI should play in your marketing org. Is it about speed? Personalization? Cost efficiency? Innovation? You don’t need one answer—but you do need clarity.
Make “why” part of every AI rollout
Every new experiment or tool should be introduced with a one-sentence purpose: “We’re using this to [XYZ].” That clarity helps teams prioritize, track value, and evaluate success on the same terms.
Align on shared use cases
Instead of each team choosing their own adventure, align around 2–3 cross-functional priorities where AI can make the biggest difference—like campaign production speed, multilingual SEO, or first-draft automation.
Want to take it further?
If you’ve started tackling these problems, feel stuck on what to try next, or need help moving forward, join Spotlight on October 29 in Amsterdam.
Mastermind sessions are where marketers dive into actionable tactics while networking with experts. These small, expert-led roundtables are designed to help you tackle real challenges, get tailored advice, and walk away with next steps you can put into practice immediately.
Here are some recommended sessions to overcome the toughest problems with AI in marketing:
Problem: You’re using AI, but your content still sounds like everyone else’s
→ Solution: Stefan Maritz (CXL) – Let’s Build a Custom GPT for Your Brand Voice
Problem: You’ve added five new AI tools (and broken three workflows)
→ Solution: Luis Guzmán (n8n) – Five Levels of AI Adoption to Succeed in Marketing
Problem: You’re automating the wrong things
→ Solution: Jeremy McDonald (Kaizen) – Pioneering Marketing Through AI: Automation Techniques to Maximise Output
Problem: AI isn’t helping you grow
→ Solution: Kevin Indig – How to Identify Market Growth Opportunities With AI
Problem: Everyone’s experimenting and nobody’s aligned
→ Solution: Liz Lohn (Financial Times) – Building AI-Powered Products: Strategies to Turn Innovation Into a Growth Driver
Tip: And if you work in SEO, Semrush’s first-ever bootcamp on October 28 will help you design smarter, faster workflows and automate large-scale SEO tasks using Semrush’s latest AI tools. You can become a Semrush expert and take your SEO strategy to the next level.
AI isn’t going anywhere—but the way we use it has to evolve.
Most marketing teams aren’t short on tools. They’re short on strategy, alignment, and clarity about where AI can truly make a difference. Whether your content feels off-brand, your workflows are getting messier, or your automation efforts are misfiring, it’s not too late to course-correct.
Start by fixing the foundations: define your voice, streamline your stack, choose what to automate (and what not to), and align your teams around a shared AI mission.
