Limitations of Artificial Intelligence that Marketers Should Know


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While Artificial Intelligence (AI) has several benefits for marketing, it also has limitations. Marketers must understand these limitations and optimize their marketing strategies accordingly.

According to an article by Authority Hacker, 75.7% of digital marketers now use AI tools for work. These tools may make their jobs easier and deliveries faster. But they lack some major aspects compared to human marketers. These may create hurdles for the marketing strategies to deliver their full potential.

The article below discusses some of the limitations of AI in marketing –

Artificial Intelligence Limitations

Inability to Think Comprehensively and Lack of Creativity

The intelligence of AI systems is limited to their programming algorithms. So, it cannot think beyond what it has been taught. Unlike humans, it cannot make an analysis and independent judgment.

For instance, marketers can generate personalized message ideas through AI platforms. But the systems can’t show empathy and compassion that compels them to connect with brands. It becomes essential for marketers to identify the difference and not rely entirely on AI-generated messages.

Also, AI systems lack the power of creativity. Although AI systems help develop ideas, designs, and unique content, they lack creativity. They are not built to deliver creative marketing assets vital to successful marketing.

According to an article by Authority Hacker, less than 20% of marketers think AI tools will have a negative impact on content quality. With this assurance, many marketers fail to notice the slide in their messaging quality. This may severely impact their marketing strategy in the long run.

AI systems in marketing integrate to provide trending marketing ideas. But to be creative and give originality to ideas requires a human touch. This is where marketers need to manually add creative aspects and ensure the campaigns successfully reach audiences.

Risk of Plagiarism and Duplication

Duplicity issues are a significant limitation of Artificial Intelligence. AI tools may create duplicate content or ideas for marketers. Duplication and plagiarism are common issues with AI that marketers and CMOs must keep a check on.

AI systems also may create a risk of data duplicity.

A customer base record may appear multiple times in the database, complicating the marketing process.

The two or three customer data records can be the same for every marketing quarter. These similarities can have severe implications for delivering the same assets for brands. It may also create a negative impression of the business’s performance.

Data Privacy and Security Concerns

Implementing AI-driven marketing in targeted advertisements and tailored experiences requires huge amounts of customer data. Marketers need to stay very alert of data leakage here. Misuse or unauthorized handling of such personal and sensitive data can lead to security breaches.

Any data privacy breach can result in a loss of trust, damaging a company’s reputation and performance. It can also attract penalties and fines under various regulations. Collecting and using personal data without the customer’s consent can raise questions about AI ethics.

So, marketers must ensure complete transparency for the use of data.

Additionally, AI may be unable to identify special customer groups, which may create issues.

For example, some marketers may use AI based tools to target vulnerable populations, such as children or those with mental health issues. This type of targeting can be seen as exploitative and unfair.

Read about the ethical considerations of Gen AI in Marketing.

Poor Data Quality Affecting Al Algorithm

AI limitations also depend on data quality and quantity. Big data is needed to train AI algorithms, particularly machine learning models. AI models may be unable to produce reliable results with inadequate data.

The data provided to these AI models must be factually correct without biases.

Inaccurate or biased data may hamper the learning ability of the model as it will replicate those biases.

Algorithmic biases can lead to discriminatory practices; such as bias toward a particular race or gender.

Also, providing incorrect data may result in faulty insights and poor marketing decisions. For instance, if the customer data provided to an AI model is old or inaccurate, it will recommend irrelevant products or services. This might damage a customer’s trust in the company, hurting the brand’s reputation.

High Maintenance and Implementation Cost

Every new technology release is expensive for businesses. Platforms with Artificial intelligence software are expensive. If enterprises have implemented AI tools, they need maintenance, which also requires investment. Also, AI software requires regular updates to adapt to the changing business environment.

Marketers need updated tools to deliver and analyze marketing performances. If AI tools are not updated, the best marketing practices may fail to create an impact. Before enterprises install AI systems, they must consider the return on investment carefully.

No One-size-fits-all Solution

Many marketers need to use different AI platforms to perform different marketing tasks. This is a significant drawback of AI. Instead, they must rely on a single AI solution to perform multiple activities.

Marketing leaders must select from many AI marketing tools to optimize and personalize content, paid campaigns, and other assets. It means there is no one-size-fits-all solution when working with AI tools. This results in high pricing, time-taking, and complicated process.

Necessitates Human Supervision

AI algorithms run automatically, but they need human intervention to align them to function. It is one of the main limitations marketers often face. They must plan, design, and run marketing campaigns after AI algorithms are coded. The codes and algorithms also need continuous supervision.

Marketers will need to check if campaigns are aligned. Before running a campaign, marketers need to do AI settings properly, ensuring campaigns go out at the right time. This form of supervision is one of the significant obstacles to marketers using AI platforms.


Artificial Intelligence has changed how businesses operate, allowing them to automate tasks, improve customer experience, and boost revenue. It has enabled high levels of efficiency and speed in marketing strategies. It has also enabled marketing content creators to deliver much higher levels and volumes of content and messaging. All these benefits also come at a much lower cost.

However, these advantages come at a significant cost. AI tools have their own set of limitations.

Firms must consider these limitations carefully to implement AI in their marketing strategies successfully. They need to be completely aware of these risks. They also need to be conscious of the consequences of overlooking these risks.

CMOs and marketing leaders must ensure that they leverage all the strengths AI tools provide to marketing teams. At the same time, they also need to take the necessary steps to remove potential risks so the strategies do not backfire.


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