Why AI Marketing Automation Fails: The Truth About AI Funnels, Agencies, Campaigns, and Websites

When AI started to go mainstream, the market soon became crowded with amazing new tools and software to help businesses and marketing agencies utilise AI. In fact the number or AI marketing automation tools has been growing faster than any other software industry segment. However,the quality of the tools, just like the quality of the first AI platforms, were far below what was expected of them after the hype. In this piece we will cover the good, the bad, and the ugly of AI marketing tools as well as their uses. 

 

Introduction: The Promise vs. Reality of AI Marketing Automation

According to WebFX, “43 percent of businesses are put off by inaccuracies or biases of AI content”. Given that the technology is still new, this is likely to be the more educated and experienced marketers, while a large proportion of users might not even be aware of the errors AI produces. 

 

I remember when the first JVZoo offer hit my inbox and I was first intrigued then disappointed. After all, it all sounded good, but the websites and copy created were just mediocre. And LMNts Marketing doesn’t settle for that. We cannot, as we work mainly with SMEs who don’t have the budget to compensate for the mediocre copy. The system picked awful images, the functionality and logical flow of the site wasn’t there, and the copy sucked. 

Fast forward to today, and I can report that Divi’s AI builder has significantly raised the bar. It can certainly be used for brochure sites, but not for custom designs that we work on. A good starting point with regards to the latest design trends. But it will not create a useful copy, for sure. 

 

Other AI tools that promised the world were ad managers, keyword research tools, and copywriting software. They were all far from perfect, and it often took people longer to correct the issues than to create the project. 

 

Here’s an example from Britanny Johnson and Tim Menzies from SE and Ethics:

“These new AI tools have many glaring problems. For instance, here is a small example (less than four lines of code) where human expertise found fixes to coding errors that were overlooked by AI. In this example: 

• ChatGPT offered a seemingly authoritative endorsement regarding some code. 
• Human programmers, naturally suspicious, ran some tests and found errors in that code. 
• When ChatGPT tried to fix the error, it went into a nonterminating loop. So AI could not fix the problem. 
• But when we asked for advice on stats.stackexchange.com, a human quickly found the correct fix”

 

I have recently started trialling a few new CRM systems as I hate admin. Assigning tasks and invoicing is the worst nightmare. I thought AI could do it. Nope. To an extent Freedcamp seems to be working great on certain tasks, but you’ll need to train it. However, I arrived to this conclusion after trying 16 AI tools for marketing agency management. Yes, I have tried the mainstream ones, after Plutio became buggy. I wasn’t happy with any of them. 

 

As a conclusion: most AI tools are overhyped. They are harder to train and implement than it says on the box (this is nothing new). If you don’t learn how to use them, and cannot customise them to your needs, they are just as useless as a Ferrari for someone who cannot drive. Or one without an engine. 

 

That said, many marketing agencies hype up their services with almost unbelievable claims, too. Next, I will explore the dangers of overpromising in marketing as well as overusing AI without supervision. 

 

 

Understanding AI Marketing: What These Tools Promise vs. Deliver

Let me make it clear: AI marketing automation is not new In fact, it has been around for a long time. We have used AI for predictive marketing about ten years ago. We tracked user behaviour to send behaviour based emails to users, to recover abandoned carts, and to retarget people who clicked on ads. It’s nothing that is revolutionary or groundbreaking. 

 

AI marketing automation is utilising global knowledge to automate and optimise certain marketing tasks that normally require manual research and decision making. 

 

The core components of AI marketing include the research, the targeting, task automation, report building, and decision making (optimisation) to deliver better results. Some AI tools focus on design, others on keyword research and SEO, while more complex ones include all of the above. 

 

AI has been implemented by some of the largest companies around the world, including Meta and Google. My Gemini on my Google Workspace can create a white paper on any related topic from my existing documents on my drive, in seconds. It will not be perfect, but about 80-90 percent there. Meta AI can improve your targeting (so they claim) and Google’s Performance Max campaigns are powered by AI. You get real time answers about marketing trends from Grok, and you can auto-generate images for your blogs. 

 

Some of the most popular ai marketing tools in the market include Canva (don’t use their image creator with text: it will jumble the letters up), ChatGTP, Zapier, Jasper, and the AI-powered versions of Hubspot and Copy.AI which has sent a few websites tumbling due to the latest Google algorithm updates. The problem was not AI use; it was the lack of usefulness and originality. If you’d like to learn more about AI and SEO, this article is still relevant. 

Marketers have embraced AI in the beginning and considered it a “Holy Grail” of artificial intelligence digital marketing. The problem is not with using them; the problem lies in the lack of experience in marketing and using these tools. And that’s why we no longer have employees, but I have explained that in my LinkedIn Newsletter.  

AI marketing automation tools are just like a sophisticated machine. Loads of options, great features, but if you don’t know how to operate them, they are useless. Using AI marketing tools without marketing experience can quickly turn into a disaster. You need to have the knowledge and experience to operate the machine, and AI is even more complicated than the most sophisticated ultrasonic aircraft. This reminds me of the countless number of clients we have worked with who have bought a ClickFunnels or Kartra subscription and waited for the miracles to happen. They didn’t. 

 

 

An Overview of AI Marketing Automation and Funnel Tools Available as of 2025:

As a summary, Apollo.io is great at lead generation, but not that good at automating tasks. Dashly and Hubspot can manage your inbound funnel but you have to learn to use them. Zoho’s Zia and Salesforce’s Einstein are on the pricey side, and they are good at predictive analytics, making them shine as the most comprehensive AI tools for marketing. However, they are tailored to the news of larger organisations, and smaller enterprises might not be able tot take advantage of all the features.

If you know about the limitations of each AI tool, you will be able to work with them. But it’s a learning curve. 

And that brings us to complex systems and AI: funnel building AI tools for marketing and their benefits and failures.

 

 

Why AI Marketing Tools Fail in Funnel Creation: Broken Lead Generation Promises

Human psychology and empathy are missing from AI tools, making them kind of useless when it comes to customer profiling. They tend to generalise instead of being specific. For our SME clients, at least, as they are laser focusing on a specific audience instead of going out wide like Unilever. 

 

 

Of course, we can feed AI tools our ideal client profile sheet and data, and it will give us a few tips and overview. Don’t get me wrong. But we need to tweak and tailor the recommendations and prompts further to get a better result. And then still revise them. Without human interaction, AI funnel builders are a waste of time. 

I recently created a few posts about cold outreach tools that are powered by AI. They are horrible. They use a generic language, don’t include any research or personalisation, and are sometimes broken, often using the wrong language, tone, or even name. 

 

AI tools for marketing are often seen as the “Magic Button” for companies, but – as I have explained a few times before – it simply doesn’t exist. You need to have an input based on your experience and your knowledge. And – as a marketing agency – we need to have the information from our clients. For example, these specific ones:

 

• What’s the goal of the campaign
• What are the main pain points of the audience
• What’s the current situation of the company
• Where are customers looking for information
• What is the company’s superpower
• What’s their products and service infrastructure
• What’s worked before
• What is the competition doing right now that might affect the outcomes

 

We always ask these questions during the marketing strategy plan SWOT service, so we can start off with the knowledge that is essential to deliver exceptional results. 

 

One of the main failures of AI funnels is that they over-personalise messages so much that they appear annoying and invasive. In other words irrelevant and insensitive. 

 

Generic templates only work up to a certain level. You need to gather and synthesize information collected by AI tolls in order to create a good marketing funnel campaign. And – to the best of our knowledge – a complex system like that doesn’t yet exist, which means you will still have to have hours of conversations with AI tools in order to get it right. 

For example, Gemini only works with three stages of a funnel. It’s so 1990!

 

Often when I use AI marketing tools, it is the 13th version of the copy, plan, or content plan that will work. I signed up to train AI for the same reason: to learn to catch artificial intelligence marketing tools on hallucination, bugs, and over-pleasing. For example, whenever I ask for an ROI prediction from AI, I often half it before presenting the simulation to the client. AI will overpromise because it is not carrying out the work. But in our business, we are underpromising and overdelivering.

 

Here’s a common mistake I can see when it comes to building a funnel for clients using AI tools: 

They go with the first recommendation and version. 

 

 The AI Marketing Agency Problem: When Outsourcing Goes Wrong

Many people are searching for answers online and believe that AI agencies are the Holy Grail of marketing. They are often disappointed. A software can only be as good as the programmer and the user. 

 

Why Digital Marketing AI Agencies Underdeliver:

It’s not intentional. Those companies probably bought those pieces of software with the best intentions, and invested a significant amount of money to make sure they deliver results. However, in marketing results are never guaranteed. Some campaigns that take ages to set up might flop. Markets change faster than ever, and whatever worked 6 months ago might not work right now. 

That said, there’s a general lack of transparency surrounding AI’s limitations. Of course, these agencies are trying to sell you their services; they will not tell you that it might not work. The same applies to everyone; from a plastic surgeon to a therapist. 

The main problem is the one-size-fits-all approaches ignoring industry specifics. For example, we have a client who is a specialist. For these treatments she offers we need to overcome the bias, unlike other mainstream treatments. Therefore, the buying cycle is longer, while the cost of conversion will be higher, with higher returns due to the higher service charge. Many AI funnel builders would create a generic funnel for the cosmetic industry instead of a specialist one. 

In the case of this client, we also have to find the right balance between saying things as it is and being sensitive about the topic. This is impossible without emotional intelligence ( something AI lacks). 

 

AI Marketing Campaign Failures: When Automation Misses the Mark

Unfortunately, AI does miss some important nuances, and cannot be left unsupervised. From translation errors to perfect deepfakes, there are plenty of examples from the past. Of course, it’s a great tool for creating campaigns, but you have to use your common sense and experience to get AI marketing campaigns right. 

 

Did you know, for example, that Coca-Cola’s AI assisted ads didn’t hit the mark with the audience?

 

Common AI Marketing Tools Campaign Missteps:  

First of all, AI has no cultural sensitivity. It is not “socialised” in any country. It’s neutral. A bit better than your average Asian freelancer who has no idea what a roundabout is, but worse than a real human. 

As a result, it can generalise too much, resulting in inaccurate audience segmentation and targeting. It can basically tell you who needs your services, but cannot tell you which audience has a strong enough pain point to take action. And that’s a huge difference. 

We don’t want to talk to robots. In fact, I always tell my clients that their audience wants to have a “relationship” with them. Unfortunately, these days, most of the social media conversations are reduced to an AI generated post replied to by AI tools. And – believe me when I say this – people today are willing to pay more for real human interaction, especially our clients. 

 

Fixing Failed AI Marketing Automation: Best Practices for Success

There’s no such thing as set-and-forget marketing. It is all about marketing the right way, learning from campaigns, and tweaking them. You can set up a campaign using AI marketing tools, taking on the recommendations. But eventually, you will need to analyse the results and make decisions based on what’s happening. If you have AI built in, it will give you some tips, but don’t take them for granted. 

 

Strategic Approaches to AI Tools for Marketing:

• Evaluate every tool and get to know their strengths and weaknesses. 
• Don’t settle for the first option; add more information to further tweak the campaigns. 
• Make the most out of your human-first ability: critical thinking.
• Feed AI as much information as you can. Make the most out of your sharing apps, and let it learn. 
• Critically evaluate the results regularly to avoid disappointment. 

 

 

The main thing I am saying here is that you need to have a strategy-first approach before tool selection. We are often asked whether companies should use one tool or another. It doesn’t really matter. If your strategy sucks, you will fail either way. If your strategy is good, and your tool can deliver what you want it to deliver, it doesn’t matter what you use. 

Of course, we use ActiveCampaign that has been offering automation for a very long time. They also have an AI template maker that takes the style and colour scheme of the website and creates stunning emails. But we don’t rely on the system to plan our funnels. Balancing automation with human creativity is the best way to make the most out of AI marketing tools. 

For example, Amazon uses AI to give you personalised recommendations and it’s mainly good (unfortunately I share my account with my two daughters, so it is hit and miss sometimes). However, Netflix hasn’t nailed recommendations fully yet; they give me recommendations that straightforward get deleted. 

 

 

AI Marketing Tools Case Studies: Learning from Real Failures

Let me tell you about the one time we asked an employee to set up a Google ad for a client. It is on the trades side of business, and we delivered the strategy on behalf of Digital4Trades. The client provides high end Venetian polished plastering services. Our employee (no longer with us for obvious reasons) took the AI recommendations for granted. As a result, they added keywords like “concrete walls” to the campaign as it was recommended as “relevant” by Google. In other words, they did not think. Thankfully, we reviewed the campaign and found out why it was not converting. 

At another time, we have used Meta’s AI tool to optimise a campaign audience for a client. They were targeting women only, but Meta thought they were smarter, so loads of random men started messaging the client. We discovered this fast and turned off Meta AI, which is probably one of the worst out there, if you ask me. Even Grok, powered by X is better. 

I am not sure whether you heard about the “Willy Wonka Experience disaster. The AI generated marketing material featured something from a dream however, the reality was so far from it that customers were enraged. Here’s an image to show the difference between the AI ad and reality. 

As you can see from the examples above, supervising AI is essential to avoid misleading customers and wasting ad budgets. 

 

 

Conclusion: Mastering AI Marketing Automation Without the Pitfalls

Strategic adoption of artificial intelligence digital marketing is not only recommended, but a must for marketing agencies and professionals. You need to embrace and a human and strategy-first approach, test different tools, and understand how they “think”. For example, you can look at the “thinking and reasoning” behind the LLM (something I have done quite a lot while training them), and find flaws in their logic or knowledge. AI is not always truthful and often tries too hard to please, remember this. 

If you would like to talk to a human-first agency that’s been utilising, testing, and correcting AI tools for over a year, and can add the human element and experience to your campaigns, please feel free to book a quick meeting. We are excited to have a virtual chat over a cup of real coffee made by human hands and craft a winning strategy with you. 

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