Marketing and AI: Pros and Cons

Conversations about AI are buzzing all over the business world, with its list of applications growing daily. But according to McKinsey, the impact of AI is projected to be felt most in marketing, where it can analyze vast amounts of customer data and provide insights that can shape marketing strategies.

But some downsides to AI in marketing also exist. Here you’ll find an analysis of the pros and cons of using AI in marketing.

Here are a few interesting statistics to know.

• Global market revenues of AI in marketing are projected to grow from $27.4 billion in 2023 to $107.4 billion in 2028.
• The top 28% of businesses use marketing automation and AI marketing tools.
• Businesses that use AI marketing tools experience a 451% increase in qualified leads.
• 61.4% of marketers have used AI.
• In a study, 19.2% of respondents said they spent more than 40% of their marketing budget on AI-developed campaigns.
• 42.2% of respondents in the same study believe that if AI took over in terms of marketing functions, high-level strategy and decision-making would be the job of human marketers.

AI can quickly analyze customer data to identify preferences and behaviors and offer insights to predict future behavior. It can target customers on the most likely online channels, create an individualized marketing message, and make product recommendations based on customer preferences. This creates highly personalized experiences for each individual customer in real time, offering relevant information that can increase conversions.

Additionally, the data and insights could shape product development plans, enabling companies to adapt their product offerings based on specific customer needs.

It can also help companies to optimize their inventory levels by predicting buying patterns and behaviors. This can lead to significant cash flow improvements.

AI-powered chatbots and virtual assistants can provide instant and personalized customer support, answering questions and offering suggestions based on real customer data. This enables customers’ needs to be met 24 hours a day without the need for manual customer support. This improves the customer experience and increases engagement, which can help to build a connection between the customer and the company.

AI can also automate many repetitive marketing tasks, allowing marketers to focus on strategic initiatives. Such tasks include sending campaign emails, lead analysis, and social media scheduling and posts. The list of potential tasks to be automated will likely grow, as AI startups focus on creating new tools with new automation applications.

AI can offer insights on patterns and trends that can be used to build targeted marketing campaigns by identifying which marketing channels to target and when. It can also identify customer segments and help to create optimized campaigns specific to each segment. This can enable marketers to create campaigns that maximize their return on investment.

AI algorithms can identify and prioritize high-quality leads, allowing marketers to target those leads and personalize strategies to reach them. AI can also automate the lead nurturing process so that communications are timely and relevant. By targeting the most likely prospects and personalizing the follow-up process companies can, again, maximize their ROI.

Of course, the collection and use of personal data raises privacy concerns. While customers are seeking a highly personalized experience with the companies they do business with, they don’t like the idea of their personal data being collected and analyzed.

AI data analysis also brings the risks of data breaches and unauthorized access to customer information, which raises customer privacy concerns even more. Such data breaches can be financially devastating for businesses, creating a need to improve cybersecurity measures when utilizing AI tools.

The most frequently discussed downside of AI in marketing is the lack of a human perspective. Empathy is often an important element of marketing strategies and messages, which AI lacks. AI can also not define and communicate a brand’s identity like a human can, which can negatively impact a company’s brand image. Additionally, AI cannot identify cultural differences and nuances when creating personalized messages.

AI is also being used by some marketers for content creation. Content marketing is a critical part of a marketing strategy, and the content needs to “speak” to the target market to create engagement and connection. AI-produced content is generic, lacking opinions and a human perspective, and does not promote that necessary connection.

In terms of the customer experience, AI chatbots make the user experience feel impersonal, which can decrease engagement. Even though the chatbot can offer personalized answers and suggestions, the customer still knows that they’re talking to a robot.

While AI can analyze the past preferences and behaviors of customers, preferences can often change quickly. If marketing decisions are solely based on AI algorithms without considering real-time customer feedback or market trends, marketing campaigns can lose relevance. AI can also not react to unlikely scenarios, which can lead to inaccurate predictions and insights. Humans, on the other hand, can react and adapt strategies based on current preferences and behavior.

Additionally, AI has the potential to misinterpret the data that it analyzes or fail to gain important insights that could be gained by human marketers.

AI algorithms also lack contextual understanding and may not be able to interpret nuances or subtle cues. They may misinterpret sarcasm, humor, cultural references, or specific language nuances, leading to inaccurate responses or irrelevant marketing messaging.

The initial investment and ongoing maintenance costs for AI technology can be significant, which may prevent small businesses from getting into the AI game. These businesses then may be left behind if they are not able to advance their marketing strategies to keep up with larger competitors.

The integration of AI systems with existing marketing infrastructure and processes can also be challenging. Integrating AI tools with existing infrastructures may lead to issues with data integration and data quality. The existing data may be fragmented or stored in different formats, making it difficult to leverage therefore, data cleansing, normalization, and standardization may be necessary to ensure compatibility, which also comes with a significant cost.

While AI can vastly improve marketing strategies based on real data, it brings some challenges as well. To mitigate these challenges, it’s important to strike a balance between AI-driven automation and human expertise in marketing. Human marketers can provide valuable insights, creativity, and intuition that AI algorithms lack. It’s crucial to leverage AI as a tool to enhance decision-making rather than replace human judgment entirely.

About the author

Carolyn Young is a seasoned professional with over 25 years of experience in various business roles, such as bank management, marketing management, and business education. She has a proven track record in writing business plans for companies with diverse products and business models, aiding in the successful launch of several startups.

She is also a reputable author, credited with multiple entrepreneurship textbooks used internationally in university curricula. Titles of her work include Introduction to Entrepreneurship, Social Entrepreneurship, Entrepreneurial Finance, and Lean Accelerator. She played a critical role in the development of an online learning platform by Venture Highway, serving as their Director of Product Development.

Moreover, Carolyn showcases a deep understanding of financial business writing, demonstrated through the numerous financial whitepapers and a technical manual for CFOs that she has written.