The Good, the Bad, and the Ugly of AI in Marketing

We’re in an exciting era where AI can supercharge personalization, targeting, and decision-making—but let’s not get lost in the hype. The good? AI is transforming marketing efficiency, letting us scale campaigns with precision we never thought possible. The bad? Over-reliance on automation is making some brands lose their human touch. The ugly? Ethical blind spots around data privacy and misuse of AI tools are creating real trust issues with customers.

5/8/20244 min read

I've seen plenty of shiny tools & tech come and go in marketing, but Generative AI is different. It’s not just another trendy tool—it’s a game-changer. That said, like anything transformative, AI has its good, bad, and downright ugly sides. Here’s what I’ve noticed using it in marketing.

The Good

To be honest: AI is revolutionizing marketing. It’s not just about automating processes - it’s driving deeper insights, faster results, and more efficient strategies across Market Research, Media Production, and Analytics.

Market Research

Gone are the days of siloed research. AI has enabled us to seamlessly merge industry-wide trends with account-specific intelligence. No more guesswork—you know what matters to your prospect. For example, if you’re targeting the CISO of an asset management firm, AI can track regulatory changes, like new SEC cybersecurity rules. But it goes further—you can see how competitors are playing, identify the firm’s tech stack, and even pinpoint the potential pain points.

AI Agents take it up a notch by autonomously gathering and analyzing this data across multiple sources in real-time. They can pull in regulatory updates, competitor insights, and prospect activities. Your market research gets done while you focus on strategy.

Tools like Perplexity are streamlining research, while Crayon Data and ZoomInfo help uncover competitor strategies and account details. Now imagine AI Agents proactively delivering those insights to your dashboard, highlighting what you need to act on.

Cleaner, Sharper Content

Once you’ve got the insights, AI steps in to help you tighten and personalize your content. Whether it’s refining tone, fixing grammar, or optimizing structure—no more embarrassing typos.

AI Agent can take this further by dynamically creating and refining content based on audience engagement. They can adjust your messaging in real-time, using feedback loops to continuously improve content relevance.

With AI-driven research and AI Agents at work, we’re moving from surface-level personalization to deep relevance. Now, when you’re targeting the same CISO concerned about cybersecurity compliance, your outreach isn’t generic—it’s data-backed, highlighting how competitors are tackling similar issues and how your solution can solve their exact challenges.

Jumpstarting Creativity

We all hit creative blocks—it’s inevitable. That’s where AI steps in. Whether it’s for ad copy, campaign frameworks, or new content formats, AI offers fresh perspectives to get the ideas flowing again. AI Agents can from the past campaigns and optimize creativity, providing suggestions that are more aligned with your target audience.

Here’s how some marketing leaders I work with are leveraging AI:

Ad Copy Refresher: AI tools like ChatGPT quickly generate multiple variations of ad copy, allowing your team to pinpoint messaging that resonates and drives engagement. This helps you move from idea to execution faster.

Idea Generation: Tools like Jasper analyze industry trends and buyer intent, delivering tailored content ideas that align with your business goals.

Visual Concepts & Inspiration: Struggling with design alignment? Canva provides data-backed, visually compelling designs that maintain brand consistency while speeding up production. Now tools like Leonardo.Ai and Gamma are quickly becoming essential for marketers, simplifying the creation of visually engaging images and presentations. Marketers can now generate high-quality, tailored visuals and dynamic presentations with minimal effort, enhancing creativity and speeding up content production.

Optimized Frameworks: AI takes the guesswork out of campaign design, building automated frameworks for email and drip campaigns optimized for conversion. AI Agents can autonomously adjust these campaigns based on performance—constantly learning from your data and fine-tuning messaging, timing, and delivery to maximize impact.

The Bad

The Dreaded AI-Powered Email Cadences

AI can churn out email sequences like a machine, but that’s the problem—many of these emails feel robotic. Just because AI can generate endless cadences doesn’t mean we should hit “send” on all of them. A flood of automated emails erodes trust, rather than building it.

Data Dependency

Here’s the hard truth: AI is only as good as the data it’s trained on. Poor-quality data leads to inaccurate insights, irrelevant messaging, and wasted marketing spend. It’s like driving with a broken GPS—if your data is flawed, your marketing will miss the mark. This is why investing in clean, reliable data is non-negotiable. Without it, AI not an asset.

Accountability

Another concern: who’s responsible when AI goes wrong? If flawed AI leads to biased targeting or insensitive campaigns, can we blame the algorithm? Absolutely not. At the end of the day, marketers are responsible for the outcomes—good or bad. We can’t just hit “go” and walk away.

The Ugly

Now, here’s where things get really messy.

When AI Feels Too Robotic

Just because AI can do more doesn’t mean it should. One of the worst missteps is over-automating to the point where your messaging feels lifeless. With too many touchpoints, AI-generated content risks becoming robotic, void of any human empathy. Sure, it’s functional, but does it move anyone? No. AI needs to be guided by human intellect.

The Ethics of AI Data

How confident are we that the AI tools we use are trained on responsible, bias-free data? We don’t always know. It’s not just about creating engaging content; it’s about ensuring that what we produce is ethically sound and free from discriminatory bias. If we’re not careful, AI could perpetuate harmful stereotypes or exclude certain groups, undermining the very integrity of our marketing efforts.

AI Spam 2.0

If marketing teams treat AI like a shortcut to more clicks and faster sales, we’ll quickly find ourselves on the “ugly” side of automation—spamming inboxes, diluting our brand, and losing real connections. AI shouldn’t be about more—it should be about better. Leaders need to resist the temptation to automate everything and focus on using AI to enhance, not replace, human-driven marketing.

At the end of the day, whether AI becomes a force for good, bad, or ugly in marketing depends entirely on us, the humans behind the machine.

If we use AI thoughtfully, balancing automation with empathy, it can elevate marketing strategies and create deeper connections. But the moment we sacrifice quality for speed, AI becomes dangerous. Leaders must draw the line, instill strong governance, and ensure AI is used ethically to drive meaningful impact—not just faster outputs.

The possibilities are endless, and honestly, I can’t wait to see where this takes us next—because we’re only scratching the surface of what’s possible.

The ability to move from reactive to proactive marketing is a game-changer.

How do you feel about AI in marketing? Do you see more good, bad, or ugly? Let me know—I’d love to hear your take!